1. Before Determining Communication Methods, We First Need to Establish Categories for Types of AI Use

To kick things off, participants worked on a general framework for the various ways AI is —or could be —used in journalism. Four main categories emerged. Because the public interacts with each of these aspects differently, what —if anything —gets communicated about the use of AI should be considered for each context. 

1. Operations: How news organizations implement AI systems and technologies in their internal processes and workflow. As Karen Mcluskie described it, “streamlining the workflow of pretty much anybody connected to the newsroom. It can be used for business intelligence and other things that run the business of news.”
2. Distribution: The platforms and processes that bring content to an organization’s audience and to the public more broadly. For example, personalizing content and providing recommendations for users based on their prior behavior.
3. Editorial and Contextual: Editorial and contextual uses of AI such as helping with story-writing or the use of internal AI chatbots that cull through the newsroom’s archives to add historical context. Sometimes, these uses result in public-facing AI-generated content, but not always. 
4. Investigation: Investigative uses of AI that help journalists examine large amounts of data, cull through historical documents or  identify an image or a quote.

In thinking about each context, it is valuable to differentiate between whether AI use is wholly new or if it is additive. Was a form of this practice being done using pre-AI — or pre-GenAI — technology? Is it a use of technology that the public is already familiar with or used to? If so, how does that affect how we define responsible communication?

Another aspect to evaluate is the level of editorial and human oversight involved. As Verena Krawarik shared, “If the automation level is very, very low … like spell check … this is nothing we have to disclose,” but, on the other hand, “if you are up for a totally automatic process and pushing content out without editorial human oversight at the end, please label it.” 

Finally, it is important to realize that journalistic uses — even when widely used and understood by journalists — may be quite different from the public’s knowledge and/or experiences with AI. How these uses are explained to the public becomes even more important and may require additional description and articulation. Automated production of video formats, transcription of audio and large language model (LLM) summaries of stories are just a few examples of AI uses specific to journalism.

2. Meaningful Communication Relies on Journalists First Being Skilled in and Comfortable with Technology

Journalists’ ability to make reasoned decisions about the value of a technology — and communicate about it to the public — requires enough technical facility to both try something out and understand how it works. 

Many newsrooms face a lack of openness to — let alone excitement for — new technologies or even change more broadly. Resistance to technology and change can leave journalism behind other industries in adoption and experimentation with technology (including AI), thereby negatively impacting the industry. It is the responsibility, Agnes Stenbom shared, “of the media companies to equip ourselves with those technical skills” to better understand AI tools and how they can be used.

It also became clear through discussion at this session, that pressure to innovate cannot come solely from the business side of the organization. Having the business side push to integrate AI tools often fails. Journalists tend to see these motivations as purely for “cost saving” or “efficiency,” rather than for empowering journalism producers. Instead, it is important that journalists feel the potential value of these technologies and discover uses themselves. As Gábor Kardos shared, “It’s not just about whether we sell it right internally, [journalists] need to explore it. So the way we try to sell it, so to say, is we try to elevate the successes that [journalists] achieve themselves.” Several attendees agreed that having hands-on experience with AI tools is critical for understanding how these technologies can improve existing workflows and benefit journalists. The need for greater technological knowledge, skill, and — thereby — confidence was also raised in CNTI’s convening in Mexico City on Online Safety and Security, suggesting a wide breadth of benefits. 

But how do we do it? Attendees shared their own experiences with bringing artificial intelligence into news organizations, lessons learned and suggestions for generating new ideas and interest in this technology. One recommendation stood out the most:

Journalists might consider viewing generative AI as a “sparring partner,” in which journalists bounce ideas off of them, use them to lightly edit sections of a story or even iterate several article titles for journalists’ consideration. In other words, AI systems can be viewed as a helpful assistant for journalists. Thus, news organizations can develop ways in which, as Ludovic Blecher put it, “tech[nology] is here to serve and not to replace.” Part of this process can be facilitated by news organizations developing internal technical expertise about how to build, update and implement AI models. If one hesitation among some journalists has been relying too much on technology for their core work, this could be a way of shifting the perspective. “[T]he true power of AI,” Richard Gingras offered, “is, how do we use it to allow us to do things that were very hard to do, particularly in the fast process of breaking news?” 

Progress Depends on Improved Relations between Journalism and Technology Companies: In addition to a general resistance to new technologies, there is a strong distrust of technology companies, stemming from issues as wide-ranging as control of information, content moderation, copyright concerns, a lack of transparency in algorithmic structures and worries over further economic imbalance. Relations tend to be especially tense in North American and Western European markets. These tensions, which are discussed in several of CNTI’s issue primers, were prominent in this discussion, much as they were in other discussions CNTI has hosted. It is critical that we work to improve these relationships (an effort central to CNTI’s mission).

One step technology companies, especially those building AI models, could take is to be more transparent about how journalism content is used and how AI models are built. Not only is this a central element of tension between journalism and technology companies, it is also important for the relationship journalists build with the public. Varun Shetty shared that, “We need to do a really good job of better explaining to both our partners and the public how these models work, what they really do, what they don’t do. One of the things that I spend a lot of time discussing with news partners and other media partners is the fact that these models aren’t queryable databases. They are reasoning engines.” One key takeaway from a series of focus groups CNTI held earlier this year on public thoughts about uses of AI in journalism is that the public needs to know that journalists can vouch for the AI model being used and the content in it. That, in turn, requires journalists to have access to more of that information. Indeed, recent research shared in this session on journalists’ perceptions of AI tools developed by outside technology companies found that many have ethical concerns stemming in part from the lack of transparency being provided by AI model developers. 

It is also important to think about the value of content in the AI era, including journalistic content utilized by AI companies to build their systems. As Madhav Chinnappa stated, “I would counsel the Big Tech companies and the regulators to not fall into that trap of thinking about how it used to work … the point is that we’re in a different age and how that value exchange works is really important because I think what we should be optimizing for is the health of the information ecosystem.”

Journalists can help by sharing their experiences at a global scale. Some geographic areas — often those with fewer financial resources — express more excitement about new technological tools, including AI. Akintunde Babatunde shared one example from West Africa, in which an AI transcription tool, Dubawa, is used by journalists to quickly turn audio interviews from different languages into English text. Journalists in these settings are coming together “with technology professionals, with data scientists … to share learnings,” said Akintunde. Journalists worldwide can learn from one another about what technological resources can be used to tell their stories and the best ways to do so. 

Finally, as new uses emerge, technology companies, policymakers and the journalistic community need to work harder to ensure equal access to the benefits of AI spanning different types of newsrooms and global regions. The major capital requirements for developing AI capacity and rapid developments in AI may — and often do — leave many volunteer and lower-revenue news organizations behind. As Lexie Kirkconnell-Kawana stated, “One of the things I think we should be thinking about is how we ensure that there is cross pollination across the sector, that the larger organizations are able to support the smaller ones and are able to cooperate and share that IP and share the use cases that are emerging from it.” 

3. We Can Learn a lot about AI Use and Labeling from Other Industries

In a point that applies to so many parts of society and life, there is much to be learned from what has come before and what colleagues elsewhere are trying. There may be journalistic applications, for example, in predictive AI modeling projects in the scientific community. Scientists are working on a “digital twin” of the Earth, Destination Earth (or DestinE), to model future environmental impacts of climate change. The news industry could apply similar methods “to help us model out what is the future of news, and what is the future of trust? What is the future of value and engagement?” said Kristen Davis. The predictive power of AI has so far been underutilized in the news industry. 

Other attendees referenced applying methods they learned from the public services industry. In France, for example, agents use AI to help answer citizens’ questions. The agents feed the question to an internal AI system and then, based on the AI system’s help, are able to provide answers to the citizen more quickly and often more thoroughly. 

It also may be necessary — or at least helpful — to bring leaders from other sectors to work with journalism organizations as they think about their future. The journalism industry is in a period of rapid transition. These changes in technology likely require professionals and leaders in the industry to rethink journalism. As Agnes Stenbom shared, “… in order to rethink journalism, we have to bring in people who are not committed to the traditional forms of journalism.”

Past and current uses of labels in other sectors can also help in thinking through what would be valuable to the public. Several attendees likened the role of labels and public disclosure of AI use to existing or past examples from the healthcare, medicine, nutrition, food and science industries. Lessons from these industries are valuable resources for understanding best practices — and potential pitfalls — in labeling. As one participant explained, “We’re actually already incredibly well trained using these kinds of labels.” The public has experience with labels and it’s important to build public awareness, knowledge and literacy using concepts that are already familiar. 

Because labels on medication and food items provide valuable information to the public, attendees considered how these types of labels could be adapted to news and journalism content that uses AI. Several remarked that gradation scales, similar to Nutri-Score used in parts of Europe, could provide a spectrum that allows audiences to identify fully human-generated content on one hand, and fully computer-generated content on the other. Content created with the assistance of generative AI but was mainly authored by a human journalist, would fit somewhere in the middle. Yet, formulating/designing these labels and educating the public about them would take time; during the current period of rapid technological development and AI integration, labeling practices may not be able to keep pace with emerging uses.

A similar theme arose during CNTI’s second convening in which the topic of organic standards and labeling were discussed and how segments of the public have come to value organic labels. 

Attention was also drawn to learning from labeling attempts that failed. One example provided by Claire Leibowicz from her forthcoming PhD research at Oxford was California’s Proposition 65, which requires warnings about public exposure to cancer-causing chemicals. The labels were found to be overwhelming and unhelpful by most, but some suggested they were useful since they prompted companies to reduce the use of such chemicals when they first rolled out. Another example provided was the attempt to put novel labels on wine. These labels were unsuccessful because consumers did not understand what the labels meant or what they signaled — an important consideration for news organizations when creating labels. For labels to be effective, the public must (1) understand what they signal and (2) find value in what they signal. 

4. Journalists’ Reporting about AI — and Technology More Broadly — Impact Public Perception and Understanding

Participants also raised the effect that journalistic coverage of AI, and technology more broadly, has on public perception. Some expressed a  sense that much of the coverage to date portrays AI as a negative, threatening technology, using language that cautions against using AI without providing coverage about how it can be useful for many industries.

Alexandra Borchardt summarized, “I think that it’s the responsibility of the media to really cover these things in much more breadth and much more constructively than they do.” Covering the nuance of AI — what it can and can’t do — is important for audiences to understand. While a healthy skepticism is valuable, several felt a fuller picture of the potential benefits and potential harms would serve to create a more informed public — and one that is then open to certain uses inside journalism.

Another way to think about how to cover AI is to consider journalists to be teachers. Journalists have an opportunity to serve as valuable teachers for complex topics like AI — filling a similar role that many held when covering the COVID-19 pandemic. As with COVID-19, building AI literacy needs to involve meeting the public where they are and providing various opportunities to learn about AI based on individuals’ interest and preexisting knowledge. Rayan Temara shared Lie Detectors’s approach of “training local journalists to go into a class and train children, aged 10 to 15, and also teachers on how they can tackle disinformation, how they can resist polarization through digital and media literacy,” which facilitates valuable interactions between journalists and their communities. One innovative educational product brought up at the convening was Minecraft’s AI Literacy program targeted at educators and children. 

Journalists’ role in educating the public is complicated because, as attendees pointed out, the way journalists use AI can be — and likely already is — very different from how the public uses it. “It’s completely and fundamentally different to use AI systems such as ChatGPT or Gemini, where you have lots of processing, and standalone open-source models whose usage by professionals have significantly increased,” said Anastasia Stasenko. For journalists to be able to explain their types of uses to the public, they must first understand AI uses thoroughly themselves. 

The public’s reliance on journalists as a kind of middle person between the individual and AI also came up during CNTI’s recent focus group work. Many participants said they expect journalists to be able to vouch for any work produced by AI that goes into their reporting, and to be able to communicate it clearly to their audiences. 

5. The Research to Date Identifies a Consistent Desire for Transparency but What Transparency Should Look Like is Less Clear

The research community has begun to amass a meaningful amount of data on uses of AI in news. Some studies reveal consistent findings while others present more conflicting evidence, suggesting that this is still a very new and developing technology with a need for continued research.

At the convening, preliminary findings from a Netherlands-based focus group were shared, revealing, according to Sophie Morosoli, that the public has a “strong wish for transparency in the sense that news organizations should be transparent about their use of AI, no matter what.” This finding is supported by Trusting News’s research shared that day by Lynn Walsh which finds that 94% of U.S. news consumers surveyed say they want newsrooms to be transparent about their use of AI and over 90% want to know a human was involved in the process of creating content. These findings also comport with both the Reuters Institute’s survey research and CNTI’s recent series of focus groups in Australia, Brazil, South Africa and the U.S.: the majority of individuals in each country expressed acceptance of news organizations using AI if audiences were informed about its use. The public’s desire for transparency is generally consistent across studies and geographies. 

Felix Simon shared recent preliminary research he’d conducted in collaboration with Benjamin Toff that featured a striking finding: “For our sample of U.S. users, we found, on average, that audiences perceived news labeled as AI-generated as less trustworthy, not more, even when articles themselves were not evaluated as any less accurate or unfair.” Yet, when the authors provided users with the sources used to generate the article, these negative effects diminished. Further research is warranted to better understand how the public interprets labels on AI-generated articles and how to best present this information.

What that transparency — or disclosure — looks like, is another body of research, and one with less of a consistent takeaway. Identifying the most appropriate and useful label remains an open question. 

It is also important to consider potential unintended effects of transparency and labeling. As Claire Leibowicz shared, “People interpret AI or not [AI] symbols or signals as implying something about truthfulness,” which they are not designed to do. Based on the Partnership on AI’s case studies of technology companies like Meta and Microsoft, the public may interpret AI labels as indicating truthfulness even when these labels do not imply anything about integrity or factuality.

We may see an analogue across these various research findings to the implied truth effect, in which warnings about misinformation have been shown to increase trust of news stories which did not receive warnings. That is, people may incorrectly assume that content without an AI label (but in which AI was used) is fully human-generated. The public may learn the value of labels and assume the absence of any signal represents inaccuracy or low quality.

The existing research also suggests AI labeling may require unique geographic and linguistic decisions which raises the question of whether it’s possible to create language-agnostic, global labels recognizable by all. 

Research has also explored how individuals within newsrooms perceive AI tools developed by outside technology companies. Results from the AI, Media and Democracy Lab found many newsroom staff have ethical concerns about using AI. Part of this concern stems from, as highlighted by Claire Pershan, the lack of meaningful transparency being provided by AI model developers. Natali Helberger emphasized the importance of “having a debate on when exactly these tools are, especially when they come from outside companies, trustworthy and safe to use and can be trusted to be in conformity with professional values that are so important in newsrooms.” News organizations also need to continue developing applications of AI with an understanding that these novel tools necessitate testing and likely require human oversight. 

Even as research continues to develop methods for achieving transparency, as one participant stated, “If we don’t have a shared definition of what journalism is, it’s going to be really hard to have shared definitions of where transparency is needed.” The concept of journalism was recently addressed in a CNTI focus group essay and remains relevant to AI labeling.

6. Visuals, Colors, Words: The Details of the Design Matter, and May Need to be Localized

As we delved into possible designs, views differed on what would be most appropriate and most effective. The bullet points below synthesize the various areas of discussion. 

• Should the disclosure and/or label come from the news provider or an outside, independent agency? There were differing views about the role of institutions to oversee disclosure and enforcement of labeling AI-related content. Sophie Morosoli’s focus group research finds that participants desired labels “linked to a certain sense of institutional accountability … that there is an external institution that can be held accountable. So if you use this label, you know that certain values and certain standards are in place.” Yet, not all participants at the convening agreed that an outside institution should be responsible for providing this service and that news organizations’ personal brand is important for building trust.
• A gradient scale model. As discussed above, some in attendance suggested disclosure of AI uses could follow a gradient scale model. On one end of the spectrum is the absence of AI involvement and on the other end is the absence of human involvement. This approach provides users with a better idea of the degree to which AI was used in news and journalism products, but it also requires the public to understand the gradations and underlying scoring. Public understanding would likely necessitate training, and the scoring itself would require updates as AI technologies continue to develop.
• Should designs include text or not? Another area of discussion centered on whether transparency and disclosure designs should feature text or merely images. While certain design aspects likely necessitate text to explain how AI models and tools were used in the development of a news product, other design aspects can be textless as long as the public understands what the images mean in context. For example, people are unlikely to read several lines of disclaimer text on their produce but will check for labels identifying it as organic or fair trade.
• Labeling “AI for good.” Related considerations are when and how uses of AI to protect the public  need to be disclosed. One participant shared the example of a news organization that used synthetic media to alter the faces of individuals who were sharing personal experiences of sensitive matters (e.g., alcoholism or abuse). This allowed first person involvement in the story without compromising their identity.
• Labeling human-generated content instead. An intriguing possibility was raised by Dan Nechita, who, during his time in the European Parliament, worked on the E.U.’s AI Act. He contended that, “[o]ne of the solutions will be to actually label human-generated content — to label authenticity.” Those who use generative AI with “ill intent” are not going to label their content; thus, in an information environment that stresses the importance of labeling AI-related content, their lack of labeling “will give them, in a sense, validation for their content,” shared Dan. His perspective aligns with a variation of the implied truth effect. It will be important to consider the implications of labeling AI-generated content given the possibility that not all AI-generated content will be tagged as such.
• Yet, as Lexie Kirkconnell-Kawana pointed out, “we can’t rely on this presumption that human-generated journalism is any better than AI-generated journalism, because there’s certainly still lots of malpractice and wrongdoing and poor practice that goes on across the industry as well.” 

7. All in All, This is a Time of Seismic Societal Change in Journalism and Beyond

Karen Mcluskie highlighted the profound uncertainty surrounding AI’s long-term societal impact. Drawing parallels to past technological revolutions, she noted that such advancements often reshape the “human operating system” in ways that become obvious only in hindsight, but are nearly imperceptible in the moment. Relatedly, Krishna Sood shared Microsoft’s perspective that the “transformative potential of AI is akin to electricity, and so hopefully, that starts to reframe the thinking as to whether you should fear it, the questions you should ask about it, and how you should adopt it within your organization.” 

Karen emphasized that governments today have a critical role in expanding our “imagination horizon” to anticipate AI’s effects. She observed that we already foresee challenges like disruptions to the labor market and the proliferation of misinformation, but she was particularly intrigued by the unknowable impacts from a world of computer-generated digital content. “What happens to the human operating system,” she asked, “when we are imbued and surrounded by image and video of other humans that is not real?” It is worth considering the implications of these changes.

For journalism these changes mean rethinking the role journalism plays in society and the services it provides. As Dan Nechita remarked, “I really believe that the survival of the [journalism] industry will rest on its ability to do something that AI cannot do.” The context he highlighted was that, at present, AI models lack creativity: “It’s [the risk] not even about discriminatory or false, or misinformation or disinformation or hallucinations. It’s also about uniformizing … the body of knowledge and the essence of truth.” 

The modern newsroom may also require, as some expressed, newsroom leaders who embrace technological experimentation to understand where these technologies can be immediately useful and where further research and testing are needed. Ludovic Blecher emphasized that, with effective executive direction, AI integration in news production can empower journalists to create more meaningful content. “I think it’s good sometimes,” he said, “to sell AI by explaining to your newsroom that it will help them to get rid of the boring tasks and focus on what matters the most.”

Governments’ role may also need to adapt to a new era. Even as governments actively consider bills and regulations, today’s fast changing, digital world may necessitate new kinds of regulatory structures.

Finally, in all of this work, it is critical to be forward-thinking — which includes understanding younger generations and their news habits. Younger generations are consuming information in unique ways that we all need to pay more attention to. As Helena Martins from Google stated, “One of the things that is on the top of our minds … is how to reach Gen Z because they have a completely different way of consuming and seeking information.” 

AI development is dramatically shaping the information environment and forward-thinking is needed to understand how these changes will affect news consumption and interactions with journalistic content.

Next Steps & Additional Information

CNTI is excited to build on the convening with a variety of next steps. One is the formation of a research working group to provide a further distillation of what the global research adds up to across the areas of AI transparency, disclosure and labeling — particularly for news and journalism.

Another next step is to continue work on design options, possibly with another working group. CNTI espouses a global approach to research and it is critical to understand how design approaches will work across different regions, cultures and languages. We encourage individuals interested in being a part of either group to contact CNTI at info@innovating.news. 

This convening, co-hosted by Thomson Foundation, is the third in a series of convenings CNTI is hosting on enabling the benefits of AI while also guarding against the harms. It is just one of many initiatives within the larger work CNTI, an independent global policy research center, does to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. Please visit our website: www.cnti.org to see more of CNTI’s work and sign up to receive updates, and, as always, please contact us with questions and ideas.

See the Appendix below for numerous valuable resources shared by participants of this event as well as other acknowledgements.

Appendix

About this convening

CNTI’s cross-industry convenings espouse evidence-based, thoughtful and challenging conversations about the issue at hand, with the goal of building trust and ongoing relationships along with some agreed-upon approaches to policy. To that end, this convening adhered to a slightly amended Chatham House Rule:

1. Individuals are invited as leading thinkers from important parts of our digital news environment and as critical voices to finding feasible solutions. For the purposes of transparency, CNTI publicly lists all attendees and affiliations present. Any reporting on the event, including CNTI’s reports summarizing key takeaways and next steps, can share information (including unattributed quotes) but cannot explicitly or implicitly identify who said what without prior approval from the individual.
2. CNTI does request the use of photo and video at convenings. Videography is intended to help with the summary report. Any public use of video clips with dialogue by CNTI or its co-hosts requires the explicit, advance consent of the subject.
3. To maintain focus on the discussion at hand, we ask that there be no external posting during the event itself.

To prepare, we asked that participants review CNTI’s Issue Primers on AI in Journalism, Algorithmic Transparency and Journalistic Relevance as well as the report from CNTI’s second convening event.

Resources Shared by Participants

Participants at our convening event shared a number of helpful resources. Many of these resources are aimed at (1) developing AI literacy, (2) learning how to implement AI technologies in newsrooms and (3) developing an understanding for how the public perceives AI use in news. These resources are presented in alphabetical order by organization/sponsor below. 

The AI, Media and Democracy Lab released a recent report in collaboration with the Associated Press that examined how employees in the news industry view and use AI in their daily work. The researchers find that ethical concerns (e.g., having generative AI produce articles) rank highly among individuals in the news industry. 

Verena Krawarik, of the Austrian Press Agency (APA), shared research with colleagues that develops a taxonomy for how AI can be used in the media industry — and the levels of human oversight required to manage these applications. The authors devise six levels of AI automation and assess over 35 different applications (e.g., text summarization, text-to-speech, business decision support, etc.) based on their usage and technological sophistication.

A transcription tool for African journalists, Dubawa Audio Platform, was discussed as an example of how technological tools are assisting journalists in the region to more quickly deliver information to the audiences. The platform was initiated by a Friend of CNTI, the Centre for Journalism Innovation and Development (CJID). 

Alexandra Borchardt shared the European Broadcasting Union’s 2024 report titled “Trusted Journalism in the Age of Generative AI.”

Felix Simon shared a recent column that considered how AI labels may affect audiences’ trust in and perspectives toward news organizations as well as the potential limitations of a “human-in-the-loop” approach to implementing AI tools. 

Human Native AI recently released a helpful overview for learning AI terminology. These concepts and technologies are rapidly developing, so understanding the nuances between key terms is important for having informed, evidence-based conversations. 

One of the takeaways from the Brussels conversation was the need to develop internal expertise about AI within newsrooms. Microsoft has developed partnerships to assist with AI adoption and has also joined collaborative fellowship programs for U.S. news organizations. 

Mozilla has produced a report on AI transparency that was released in the lead up to the E.U.’s AI Act. The authors find that many technology organizations developing AI models and tools do not provide meaningful transparency to end users.

Partnership on AI provides several resources including policy recommendations for AI labeling and important considerations when disclosing AI-related content to audiences.

Relatedly, Trusting News’s 2024 research on AI labeling and disclosure reveals large majorities of the U.S. public desire transparency about uses of AI in news.

We appreciate all of our participants for sharing these resources with CNTI. 

About CNTI

The Center for News, Technology & Innovation (CNTI), an independent global policy research center, seeks to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. CNTI’s cross-industry convenings espouse evidence-based, thoughtful but challenging conversations about the issue at hand, with an eye toward feasible steps forward. 

The Center for News, Technology & Innovation is a project of the Foundation for Technology, News & Public Affairs.

Acknowledgements

CNTI sincerely thanks the participants of this convening for their time and insights. We are grateful to Thomson Foundation, the co-sponsor of this AI convening, and to our venue, Résidence Palace. Special thanks to Caro Kriel, Federica Veralda, Kaspar Loftin and Angela Watt for their support, and to Tanit Koch for moderating such a productive discussion. CNTI is generously supported by Craig Newmark Philanthropies, John D. and Catherine T. MacArthur Foundation, John S. and James L. Knight Foundation, the Lenfest Institute for Journalism and Google.

CNTI is generously supported by Craig Newmark Philanthropies, John D. and Catherine T. MacArthur Foundation, John S. and James L. Knight Foundation, The Lenfest Institute for Journalism and Google.

El medio ambiente: Múltiples tipos de violencia

La violencia contra la prensa en México se presenta de muchas formas, que van desde acoso sexual, acoso en línea, difamación, hasta espionaje y amenazas, y lo llevan acabo una variedad de actores que incluyen al crimen organizado, autoridades [gubernamentales], movimientos civiles y ciudadanos. La violencia contra los periodistas y la prensa cambia entre el mundo digital y el físico, y los ataques en un contexto a menudo conducen a ataques en el otro. 

Los participantes también hablaron de la naturaleza impredecible de muchos ataques citando casos en los que un periodista podría ser atacado después de un acto aparentemente benigno como tomar una fotografía del vehículo o persona “equivocada”. Además, debido a que la mayoría de los periodistas en México necesitan tener dos trabajos para pagar sus cuentas, a menudo se explica que un ataque es el resultado de algo hecho en el otro trabajo y no en el periodístico. Esta imprevisibilidad genera un estado de miedo entre los periodistas y subraya la capacidad del gobierno para ejercer su poder de manera arbitraria.  El índice de impunidad según datos de organizaciones como Amnistía Internacional, el Comité para la Protección de Periodistas y Propuesta Cívica es más del 95%.  

La naturaleza de esta violencia varía según las diferentes formas en que los periodistas realizan su trabajo en México. En algunas regiones y localidades, los periodistas escriben sus historias a mano, las cuales luego son distribuidas dentro de las comunidades locales, lo que aumenta el riesgo de enfrentar amenazas físicas y violencia.

“En algunas zonas muy marginadas, hay periodistas que escriben boletines a mano y los distribuyen. Ese es el periodismo que se hace en algunas regiones. Y es importante considerarlos porque, como se mencionó aquí, este tipo de periodistas son los que corren mayor riesgo de sufrir ataques.”

En el ámbito digital, una preocupación importante es la seguridad de los datos personales de los periodistas. En enero de 2024, la información personal de más de 300 periodistas, proveniente de una base de datos gubernamental —que contenía direcciones personales, identificadores de pasaporte, números de teléfono y más— fue filtrada en línea. Las autoridades mexicanas están investigando la infracción. Asimismo hay varios casos en los que el presidente saliente de México ha realizado doxxing (exposición de información personal) a periodistas durante transmisiones en vivo. Existe preocupación por el uso del spyware Pegasus para monitorear las acciones e investigaciones de los periodistas. Estas amenazas cibernéticas se están volviendo más severas y difíciles de combatir a medida que los agresores avanzan tecnológicamente.

Pasos recomendados

Uno de los objetivos principales de las reuniones del CNTI es identificar pasos colaborativos y accionables que periodistas, tecnólogos, sociedad civil y responsables políticos puedan tomar de manera conjunta.

“Todo  esto requerirá coordinación y colaboración entre varias organizaciones si queremos comenzar a crear los resultados que queremos para los periodistas.”

Varios de estos pasos surgieron de esta discusión.

Mejorar la alfabetización digital y ciberseguridad de los periodistas

Surgió un fuerte consenso en torno a la necesidad de un mayor conocimiento digital y de ciberseguridad entre los periodistas. Este tipo de conocimiento requiere dedicación por parte de los periodistas y sus empleadores a un nuevo tipo de capacitación que busca construir conocimiento continuo y comodidad con la tecnología, las formas de utilizarla para su protección y las formas en que las prácticas y programas actuales pueden incorporarla. Algunos lo describieron como “capacitación al estilo de primeros auxilios” y “ciber higiene”. Actualmente, muchos agresores son más avanzados técnicamente que los periodistas a los que atacan, lo que deja a los periodistas sin escudos digitales para protegerse. 

Un participante dijo:

“Existe una importante falta de conocimiento sobre cómo los periodistas deberían usar dispositivos y software para protegerse a sí mismos y a sus fuentes. […] Muchos periodistas son freelancers o fixers y tienen aún menos oportunidades de asistir a seminarios o cursos. Son más vulnerables que aquellos que trabajan en redacciones o como corresponsales para medios nacionales o internacionales.”

Y otro sugirió: 

“El primer lugar donde deberíamos implementar mecanismos de alfabetización mediática es dentro de los propios medios, especialmente para los periodistas. Es algo ridículo, pero los periodistas en este país, reporteros, fotógrafos y especialmente columnistas, suelen carecer de habilidades críticas de alfabetización mediática…”

Un desafío adicional en México, y probablemente en otras partes del mundo, es que muchos periodistas utilizan dispositivos antiguos (como celulares, computadoras portátiles, de escritorio, etc.) que no pueden ejecutar el software de seguridad cibernética más actualizado. Además, muchos periodistas en México, especialmente los freelancers, utilizan dispositivos personales para su trabajo profesional. En estas situaciones, los datos personales (como información familiar) y los datos profesionales (como fuentes) coexisten en el mismo dispositivo, lo que aumenta el riesgo y las consecuencias de que sus dispositivos sean comprometidos.

La creación de conocimientos más profundos y continuos también podría ayudar a aliviar parte de la naturaleza dual de la tecnología que muchos sienten. Si bien los periodistas en México encuentran beneficiosa la tecnología para su trabajo (por ejemplo, les permite compartir contenido de inmediato y comunicarse con fuentes), también puede ponerlos en riesgo. Por ejemplo, existe evidencia de que periodistas mexicanos han sido blanco del spyware Pegasus utilizado por miembros del gobierno y el ejército mexicanos.

“Por un lado, la propia tecnología les permite hacer su trabajo con mayor calidad, facilitando el trabajo periodístico. Pero, por otro lado, les pone en riesgo. La tecnología en sí misma es un riesgo.”

Los participantes también discutieron la disparidad en la capacitación en seguridad digital que existe entre los centros urbanos poblados de México y otras zonas del país. 

“La mayoría de los periodistas fuera de las principales capitales de México y fuera de los principales medios de comunicación en estas ciudades saben poco o nada sobre herramientas para protegerse digitalmente. Y algo relacionado con esta falta de formación no es sólo saber protegerse de ataques, sino que también hace que muchos compañeros periodistas ni siquiera hagan un uso adecuado de la tecnología.”

Es importante destacar que esta capacitación no puede ser un esfuerzo único. Para ser efectiva, todos los miembros de la prensa deben actualizar continuamente sus prácticas de ciberseguridad. Y las propias organizaciones de noticias, como señaló un participante, deberán impulsar parte de este cambio al fomentar una cultura que acepte la alfabetización digital continua y la ciberseguridad como un requisito para ejercer el periodismo.

“Capacitar a un periodista para protegerse no es una cosa de una sola vez. Asegurarse de que tengan las herramientas adecuadas en sus dispositivos no es algo que se haga una sola vez. Es un esfuerzo continuo.”

Los esfuerzos por la resiliencia cibernética también deben ser integrales. No solo deben enseñar a los periodistas sobre las herramientas disponibles, sino también cómo usarlas de manera efectiva.

“La ciberseguridad hoy debe ser parte de las actividades rutinarias. De esta forma, las instituciones y empresas deben crear una cultura de seguridad de la información y adoptar las medidas adecuadas.” 

Afortunadamente, una organización no tiene que hacer esto sola. Los esfuerzos de colaboración con organizaciones internacionales, así como con organizaciones dentro de México, pueden facilitar la adopción de protocolos y prácticas de ciberseguridad.

“Tenemos que trabajar en colaboración con los modelos que tenemos, formar al formador, localizar, contextualizar, pero también apoyarnos en las nuevas tecnologías.”

Ampliar la investigación para proporcionar contexto y comprensión del problema

Otra recomendación fue expandir la investigación sobre las condiciones actuales de los periodistas, así como un examen del panorama general de la violencia en México.

Los participantes recomendaron recopilar mejores datos sobre las condiciones actuales en México relacionadas con la violencia, experiencias específicas de los periodistas y sus hábitos tecnológicos. Es difícil conocer el alcance de las amenazas a la seguridad de los periodistas en Centro y Sudamérica debido a la escasez de encuestas o bases de datos completos sobre las experiencias de los periodistas. Realizar más investigaciones permitiría una mejor comprensión de las amenazas a la seguridad que enfrentan los periodistas y proporcionaría métricas para medir el impacto de las protecciones.

“Lamentablemente no contamos con estudios como los del Centro de Investigación Pew en Estados Unidos, que brindan información sobre los hábitos tecnológicos de los periodistas o sus condiciones laborales, como cuántos han sido despedidos desde la pandemia y cuál es su situación actual. Existe una importante falta de conocimiento sobre cómo los periodistas deberían utilizar dispositivos y software para protegerse a sí mismos y a sus fuentes.”

Investigaciones adicionales también pueden ayudar a comprender el complejo panorama de la violencia en México. Los participantes discutieron cómo la violencia contra la prensa en México es parte de “ecosistemas de violencia” más amplios y cómo la investigación debe adoptar un enfoque integral para comprender el panorama de la violencia en el país. 

“Es crucial entender la violencia contra el periodismo en México dentro de estos ecosistemas de violencia, donde grupos armados no estatales y aparatos estatales a menudo convergen… es esencial estudiar estos ataques no de forma aislada dentro de la profesión periodística sino dentro de sus contextos más amplios de violencia. Solo entonces podremos desarrollar estrategias conjuntas que tengan un mayor impacto en la prevención y respuesta.”

CNTI compartió con los participantes que contribuiremos a investigaciones adicionales en esta área a través de una encuesta global a periodistas. Esta encuesta buscará, en parte, obtener un conocimiento más profundo sobre los desafíos de seguridad y protección en línea que experimentan los periodistas. Pronto habrá más información sobre esta iniciativa.

Mayor desarrollo de herramientas tecnológicas y uso de inteligencia artificial

También se hizo un llamado a construir herramientas tecnológicas más fuertes, prácticas e integrales para protegerse contra ataques en línea. Tales herramientas, junto con una mayor alfabetización digital, pueden ayudar a que los beneficios de la tecnología superen los daños.

Por ejemplo, muchas de las herramientas y métodos existentes para disminuir las amenazas online y offline contra los periodistas son reactivos y no proactivos. Por lo tanto, los periodistas se quedan respondiendo a ataques y abusos en línea y constantemente jugando a “ponerse al día”. 

“Una cosa que siempre he notado es que todas estas organizaciones e iniciativas son reactivas. Preguntan qué hacer después de que algo ya sucedió. Poco trabajo se hace en mecanismos que puedan prevenir estas situaciones.”

¿Qué tipo de herramientas podrían ofrecer acciones y métodos más proactivos? Una mayor colaboración y pruebas sobre la mejor manera de implementar medidas proactivas para proteger a los periodistas merecen ser una prioridad. Uno de esos esfuerzos compartidos en el evento es el trabajo realizado por Dromómanos Desarrollar herramientas asistidas por IA para identificar, rastrear y denunciar abusos y amenazas en línea dirigidas a periodistas que trabajan en Centroamérica. 

También se habló más ampliamente sobre los desarrollos en inteligencia artificial (IA). La IA no es un foco central en México como lo es en otros entornos noticiosos del mundo. Sin embargo, están comenzando las discusiones e implementación de herramientas de IA. Un asistente destacó la importancia de considerar cómo las tecnologías de IA pueden utilizarse para proteger a los periodistas, particularmente a aquellos que cubren temas sensibles, en lugar de limitar su aplicación a la automatización y eficiencia.

“Creo que las organizaciones periodísticas también deberían preguntarse cómo están utilizando la adopción de la información y la tecnología dentro de sus propias organizaciones para sus equipos de periodistas. Porque, por ejemplo, en materia de inteligencia artificial, mi impresión es que muchos medios de comunicación se están apresurando a ver cómo pueden adoptar la inteligencia artificial para automatizar procesos, generar contenidos y crear mejores métodos de distribución. Pero creo que es necesario que haya una mejor discusión dentro de los propios medios con sus periodistas en términos de cómo esto también los beneficia en cuestiones de su propia seguridad y cómo pueden usar la tecnología para cubrir temas delicados.” 

Explorar opciones regulatorias

Una dinámica particularmente desafiante en México es que el gobierno mexicano, y en particular líderes de alto perfil como el presidente saliente, han jugado un papel importante en el ataque a periodistas. Esto hace que la regulación sea un camino problemático que podría no solo fallar en su objetivo, sino incluso ser contraproducente. Muchos participantes han compartido que llevan décadas trabajando hacia protecciones legislativas sin ninguna mejora en la seguridad de los periodistas en México. Un ejemplo es el Mecanismo de Protección para Personas Defensoras de Derechos Humanos y Periodistas del gobierno federal. Está diseñado como un medio para proporcionar protección de seguridad a los periodistas que han recibido amenazas y/o han sufrido ataques. Algunos periodistas que reciben protección han criticado el programa por su efectividad debido a preocupaciones de que algunos miembros del personal de seguridad se enfrenten a conflictos de interés, mientras que otros ven sus solicitudes de protección denegadas.

Sin embargo, aún existe la sensación entre muchos de que debemos continuar intentando desarrollar regulaciones para la privacidad y seguridad digital que minimicen el abuso potencial. Las regulaciones se consideran un punto de referencia crucial. Incluso con el gobierno como parte del problema, hubo acuerdo en que se necesita algún tipo de regulación impuesta por el gobierno, aunque sea arriesgada.

“Regular es un riesgo, especialmente en países como este. Pero no regular es un peligro porque deja abierta la puerta a un trato indiscriminado por parte de quienes están en el poder.”

“Si bien contamos con marcos legales para la protección de periodistas tanto a nivel federal como local, aunque mal implementados y operativos, falta un marco regulatorio específico para la protección de la privacidad y la seguridad en el mundo digital…” 

Parte del deseo de una mayor regulación para apoyar a los periodistas surge del reconocimiento de que las regulaciones sirven como puntos de referencia que los periodistas, académicos y funcionarios gubernamentales, entre otros, pueden utilizar para promover la protección de la prensa.

“Es necesario tener marcos regulatorios, marcos normativos, aunque a veces no sean aplicables, pero es importante que existan y que sigamos presionando y exigiendo que las autoridades los implementen.”

También es fundamental que cualquier enfoque considerado reconozca y cubra el diverso espectro del periodismo en el país. Como compartió un participante, las áreas fuera de las principales zonas metropolitanas son “invisibles” cuando se trata de comprender las necesidades de los periodistas. En algunas áreas rurales del país, por ejemplo, los periodistas crean boletines informativos manuscritos para los lectores de su comunidad, lo que requiere diferentes tipos de protección en comparación con los enfoques de periodismo impulsados por la tecnología.

“Cualquier respuesta que intentemos elaborar para resolver este problema debe considerar una cosa, y es que no existe el periodismo mexicano. No existe un solo periodismo mexicano. […] En ese sentido, cualquier medida que se proponga, se discuta, necesariamente debe entender que debe haber una perspectiva regional. Es decir, entender que cada región tiene diferentes desafíos económicos, políticos y sociales.”

Reconocer la importancia del Estado

Varios compartieron la perspectiva de que para que el periodismo sea protegido y apoyado, el gobierno mexicano debe estar involucrado. Esto es una perspectiva delicada, dado que los funcionarios gubernamentales continúan amenazando y reprimiendo a la prensa, como compartir información de contacto personal de periodistas durante transmisiones en vivo. Sin embargo, los asistentes subrayaron que, a menos que el Estado priorice una prensa libre y protecciones para los periodistas, todo el valioso trabajo que se está realizando para fortalecer la prensa será insuficiente.

“Cualquier medida que podamos proponer juntos, la academia, las ONG y el periodismo, nunca reemplazará la responsabilidad del Estado. No podemos reemplazar la responsabilidad del Estado.”

A menudo el Estado – en múltiples niveles de gobierno – es un actor importante a la hora de atacar a periodistas y a la prensa. Los participantes expresaron la tensión que existe actualmente en México entre el gobierno y la prensa. El Estado actúa como árbitro con autoridad para hacer cumplir la protección de los periodistas, mientras que al mismo tiempo los periodistas son amenazados por actores oficiales del Estado. 

“Para nosotros, la continua militarización significa que es poco probable que cambie la tendencia de violencia contra periodistas y defensores de los derechos humanos.”

Ésta es una situación compleja y difícil. La presidenta entrante de México, Claudia Sheinbaum, asumirá el cargo el 2 de octubre de 2024. Es de esperarse que siga muchas de las mismas políticas que su predecesor, el presidente saliente Andrés Manuel López Obrador, pero también posiblemente tomar una postura menos hostil hacia la prensa. Si bien algunos de los asistentes se mostraron cautelosamente optimistas sobre la posibilidad de mejorar la relación entre el presidente y la prensa, esto aún está por verse y muchos creían que la situación actual no mejoraría notablemente. 

Incrementar la presión de la comunidad global

También se ha subrayado en numerosas ocasiones el importante papel que la comunidad global — incluidas las organizaciones gubernamentales internacionales, los estados nacionales y las organizaciones no gubernamentales — debe desempeñar en la protección de la seguridad de los periodistas.

La comunidad global debería aumentar su presión para responsabilizar al gobierno mexicano (y a otros gobiernos que atacan a la prensa o no defienden las protecciones) por su fracaso en apoyar y proteger a los periodistas. La presión externa tiene el potencial de influir en (1) qué regulaciones se consideran dentro de un determinado país y (2) lo que los líderes están dispuestos a decir para denigrar a la prensa.

“Entonces, creo que no debemos detener la presión internacional; debemos seguir aplicándolo y es importante apoyarlo.”

La comunidad global también puede proporcionar ejemplos importantes e impulsos morales al continuar llevando casos a los tribunales y reforzando las protecciones mediante victorias legales. Como compartió un participante, los casos contra funcionarios políticos que atacan a periodistas están produciendo resultados positivos porque crean precedentes legales. Estos resultados ayudan a fomentar la protección de los periodistas incluso más allá de los límites geográficos de un caso particular.

“Creo que la regulación es sumamente importante porque no sólo podría prevenir parte de estos ataques, sino que crea un espacio institucional y judicial para acciones legales. Y las victorias legales son extremadamente importantes. Dan ejemplo. Estamos viendo esto en el caso de María Ressa. Estamos viendo el caso de Patrícia Campos Melo en Brasil. Patrícia es una periodista brasileña que ha sido atacada sistemáticamente por Bolsonaro. Ha ido ganando caso tras caso. Y ha sido extremadamente importante hacer que otras figuras políticas lo piensen dos veces antes de atacar a un periodista.”

También se necesitan mejores formas de conectar a los periodistas de todo el mundo entre sí. Los periodistas pueden aprender unos de otros, compartir experiencias, herramientas y técnicas para mejorar la seguridad física y digital, generar apoyo moral y más. 

Generar apoyo público para el periodismo

Muchos de los pasos recomendados anteriormente serán menos efectivos sin el apoyo del público. El público debe preocuparse por el periodismo y la seguridad de los periodistas, algo que muchos participantes sintieron que no es el caso actualmente. Un reciente informe del Instituto Reuters para el Estudio del Periodismo encontró que sólo el 35% de los adultos en México confían en los medios de comunicación la mayor parte del tiempo.  

“Creo que el hecho de que nuestra profesión sea cada vez menos querida y apreciada por la sociedad también ha contribuido a la falta de simpatía y a la falta de comprensión sobre los riesgos…”

Un factor que contribuye a esta falta de reconocimiento y confianza puede ser la creciente polarización política en la sociedad y las formas en que se puede vincular a la prensa. 

“Por lo tanto, la función de vigilancia es desafiante para la gente, porque siempre asocian a los periodistas con la política, que no tiene una buena reputación, por así decirlo.”

La divulgación local en nombre de los periódicos locales y regionales se consideró un primer paso fundamental para establecer conexiones con el público. Los participantes discutieron la necesidad de que el público confíe en los periodistas y los vea como un recurso importante para mantenerse informado sobre los acontecimientos actuales. 

Un participante compartió:

“Creo que ahí es donde deberíamos prestar más atención a la hora de informar sobre el crecimiento. Está ahí, en los pequeños periódicos locales. Es el inicio de la relación con la comunidad…”

Dijo otro:

“No es que la gente carezca de acceso a la información; más bien, a menudo optan por desconectarse de él porque también lo perciben como inútil”.

Otro individuo compartió la importancia de desarrollar relaciones con las audiencias para comprender lo que necesitan del periodismo. Esta recomendación requerirá que las organizaciones de noticias y los periodistas formen relaciones más cercanas con sus audiencias, un tema complejo descrito en el informe del CNTI manual del último número.

“Entonces creo que debemos entender mejor quiénes son nuestras audiencias, cómo consumen información, porque, en última instancia, todo periodismo es local. Todo el periodismo se consume localmente. Entonces, ¿cómo conocemos mejor a estas audiencias, las entendemos mejor, cómo las acercamos y fortalecemos ese vínculo?”

Atraer talento joven 

Los asistentes también consideraron el desarrollo de los periodistas. La situación actual en México ha llevado a muchos jóvenes a evitar la profesión. Se mencionaron numerosos factores para explicar esta evasión, principalmente relacionados con la falta de seguridad y los bajos salarios.

“No es culpa de la academia que no haya jóvenes que quieran estudiar periodismo. Es culpa de los medios de comunicación [propietarios], que han empobrecido la profesión. Porque de verdad ¿quién quiere ser periodista hoy con estos riesgos, con un salario de 3, 5, 8 mil pesos mensuales, sin seguridad social para la mayoría, y abandonado por sus propios medios cuando son víctimas de agresiones? Es muy difícil para las escuelas de comunicación atraer a jóvenes que quieran ser periodistas en estas condiciones.”

Otra preocupación fue cómo la capacitación que reciben los periodistas en los programas educativos no los prepara para los requisitos actuales del periodismo en México.

“Creo que la conexión entre la academia y la industria del periodismo, al menos por lo que veo en México, se está debilitando. Mi percepción es que dentro del mundo académico, los académicos que nos dan tantos consejos en la industria del periodismo no saben qué hacer con los estudiantes. No saben formar un carácter muy cambiante, muy diverso, en un proceso complejo ante un mercado laboral con enormes retos por delante.”

Conclusión

Esta reunión, en colaboración con la Organización Editorial Mexicana, discutió muchos de los desafíos de seguridad online y offline que enfrentan actualmente los periodistas en México. Esto se basa en otros trabajos del CNTI en esta área, incluidos manuales temáticos sobre amenazas cibernéticas y abuso en línea frente a los periodistas, mesas redondas en el Congreso Mundial Abraji, columnas y más.  El CNTI también está abordando las preocupaciones de seguridad de los periodistas con su iniciativa “Defining News”. Esta iniciativa incluirá una encuesta global a periodistas para comprender mejor, en parte, los desafíos en línea que enfrentan. Más adelante este año se publicará más información sobre esta iniciativa. 

Reuniones como esta son solo una de las muchas iniciativas dentro del trabajo más amplio que realiza el CNTI, un centro independiente de investigación de políticas globales, para fomentar medios de comunicación independientes y sostenibles, mantener una Internet abierta y fomentar conversaciones informadas sobre políticas públicas. Por favor visite nuestro sitio web: www.cnti.org para ver más del trabajo de CNTI y suscríbase para recibir actualizaciones y, como siempre, contáctenos si tiene preguntas e ideas.

Finalmente, consulte el Apéndice a continuación para obtener una lista de los participantes en este evento, así como otros reconocimientos e información. 

Appendix

Sobre la convocatoria

Los encuentros interindustriales del CNTI promueven conversaciones basadas en evidencia, reflexivas y desafiantes sobre el tema en cuestión, con el objetivo de construir confianza y relaciones continuas, así como algunas aproximaciones acordadas a la política. Con ese fin, este encuentro se ajustó a una versión ligeramente modificada de la Regla de la casa Chatham:

1. Se invita a personas como pensadores destacados de partes importantes de nuestro entorno de noticias digitales y como voces críticas para encontrar soluciones viables. Para efectos de transparencia, CNTI enumera públicamente todos los asistentes y sus afiliaciones. Cualquier informe sobre el evento, incluyendo los informes de CNTI que resumen las conclusiones clave y los próximos pasos, puede compartir información (incluidas citas no atribuidas) pero no puede identificar explícita o implícitamente quién dijo qué sin la aprobación previa del individuo.
2. El CNTI sí solicita el uso de fotografía y video en los encuentros. La videografía está destinada a ayudar con el informe resumido. Cualquier uso público de videoclips con diálogos por parte del CNTI o sus copresentadores requiere el consentimiento previo y explícito del sujeto.
3. Para mantener el enfoque en la discusión en cuestión, solicitamos que no haya publicaciones externas durante el evento en sí.

Como preparación, pedimos a los participantes que revisaran los Issue Primers de CNTI sobre abuso en línea y amenazas cibernéticas. 

Acerca del CNTI

El Centro de Noticias, Tecnología e Innovación (CNTI), un centro de investigación de políticas global e independiente, busca fomentar medios independientes y sostenibles, mantener un internet abierto y promover conversaciones de políticas públicas informadas. Los encuentros interindustriales del CNTI promueven conversaciones basadas en evidencia, reflexivas pero desafiantes sobre el tema en cuestión, con miras a pasos viables hacia adelante.

El Centro de Noticias, Tecnología e Innovación es un proyecto de la Fundación de Tecnología, Noticias y Asuntos Públicos.

Agradecimientos

CNTI agradece sinceramente a los participantes de esta reunión por su tiempo y sus ideas, y agradecemos a la Organización Editorial Mexicana (OEM), copatrocinador y anfitrión de esta reunión. Un agradecimiento especial a Francisco Torres Vázquez y Martha Ramos por su apoyo y a Alejandro Jiménez por moderar una discusión tan productiva.

CNTI cuenta con el generoso apoyo de Filantropías de Craig Newmark, Fundación John D. y Catherine T. MacArthur, Fundación John S. y James L. Knight, el Instituto Lenfest de Periodismo y Google.

The Environment: Multiple Kinds of Violence

Violence against the press in Mexico comes in many forms, such as “sexual harassment, online harassment, defamation” as well as spying and threats, and is carried out by a range of actors including “organized crime, [government] authorities, civil movements and citizens.” Violence towards journalists and the press flows between the digital and physical worlds with attacks in one context often leading to attacks in the other. 

Participants shared examples of how many attacks are unpredictable in nature. They cited instances where a journalist might be targeted after a seemingly benign act such as taking a photo of the “wrong” vehicle or person. Additionally, because most journalists in Mexico need to work two jobs to pay their bills, an attack would often be explained as the result of something they had done in their non-journalistic job. This unpredictability instills a state of fear among journalists and underscores the government’s ability to exercise its power arbitrarily. The rate of impunity — according to data from Amnesty International, the Committee to Protect Journalists and Propuesta Cívica — is over 95%. 

The nature of this violence varies with the different ways journalists do their work across Mexico. In some regions and localities, journalists handwrite their stories which are then delivered within local communities, increasing the risk of encountering physical threats and violence.

“[I]n some very marginalized areas, there are journalists who write newsletters by hand and distribute them. That is the journalism that is done in some regions. And it is important to consider them because, as mentioned here, these types of journalists are the ones at greatest risk of suffering attacks.” (from Spanish)

In the digital realm, one major concern is the security of journalists’ personal data. In January 2024, over 300 journalists had their personal information from a government database — containing personal addresses, passport identifiers, phone numbers and more — leaked online. The Mexican authorities are investigating the breach. There are also several instances of Mexico’s outgoing president doxxing journalists during live broadcasts. Concerns also surround the use of Pegasus spyware to monitor journalists’ actions and investigations. Cyber threats are becoming more severe and difficult to combat as the aggressors become more technologically advanced.

Recommended Steps

A major goal of CNTI’s convenings is to identify actionable, collaborative steps that journalists, technologists, civil society and policymakers can take in tandem.

“All of this is going to take coordination and collaboration among a number of organizations if we’re going to start creating the outcomes that we want to create for journalists.”

Several such steps emerged from this discussion.

Improve Journalists’ Digital and Cybersecurity Literacy

Strong consensus emerged around the need for deeper digital and cybersecurity knowledge among journalists. This kind of knowledge requires journalists and their employers to dedicate themselves to new training that builds ongoing knowledge of and comfort with technology, the ways to use it for their protection and the ways current practices and programs can compromise it. Some described it as “First Aid style training” and “cyber hygiene.” Currently, many aggressors are more technically advanced than the journalists they target, leaving journalists without digital shields to protect themselves.

One participant said:

And another suggested: 

An additional challenge in Mexico, and likely other parts of the world, is that many journalists are using older devices (e.g., cellphones, laptops, desktops, etc.) incapable of running the most up-to-date cybersecurity software. Furthermore, many journalists in Mexico — particularly freelancers — use personal devices for their professional work. In these situations, personal data (e.g., family information) and professional data (e.g., sources) live on the same device, increasing the risk and consequence of their devices being compromised.

The continuous building of deeper knowledge could also help alleviate some of the conflicted feelings many have about technology. While journalists in Mexico find technology beneficial for their work (e.g., allowing them to share content immediately and communicate with sources), it can also put them at risk. For example, there is evidence that members of the Mexican government and military have targeted Mexican journalists by using Pegasus spyware.

Participants also discussed the disparity in digital safety training that exists between populated urban centers in Mexico and other areas of the country. 

Importantly, this training cannot be a one-time effort. To be effective, all members of the press must continuously update cybersecurity practices. And news organizations themselves, as one participant remarked, will need to drive part of this change by shaping the culture to accept continuous digital literacy and cybersecurity as a requirement for practicing journalism.

Cyber resilience efforts must also be comprehensive. They need to teach journalists about the tools available to them as well as how to use them effectively. 

Fortunately, no organization has to do this alone. Collaborative efforts with international organizations, as well as organizations within Mexico, can facilitate the adoption of cybersecurity protocols and practices.

Expand Research to Provide Context and Understanding of the Problem

Another recommendation was to expand research about the current conditions for journalists as well as an examination of the broader landscape of violence in Mexico. 

Participants recommended gathering better data about current conditions in Mexico related to violence, experiences specific to journalists and their technology habits. It is difficult to know the scope of security threats to journalists across Central and South America because there are so few comprehensive surveys or databases of journalists’ experiences. Conducting more research would allow for a better understanding of the security threats facing journalists and provide metrics to measure the impact of protections.

Further research about journalist safety can also increase understanding of the complex landscape of violence in Mexico. Participants discussed how violence against the press in Mexico is part of larger “ecosystems of violence” and how research needs to take a comprehensive approach to understand the broader landscape of violence in the country. 

CNTI shared with participants that we will be contributing to further research in this area ourselves through a global survey of journalists. This survey will seek, in part, to gather deeper knowledge about the online safety and security challenges experienced by journalists. More information about this initiative will be forthcoming.

Further Develop Technological Tools and Use Artificial Intelligence

There was also a call for building stronger, more practical and comprehensive technological tools to guard against online attacks. Such tools, along with greater digital literacy, can help the benefits of technology outweigh the harms. 

For example, many of the existing tools and methods to decrease online and offline threats toward journalists are reactive rather than proactive. Thus, journalists are left to respond to attacks and online abuse and to consistently play “catch up.” 

What kinds of tools could offer more proactive actions and methods? Further collaboration and testing about how best to implement proactive measures to protect journalists deserves priority. One such effort shared at the event is work done by Dromómanos to develop AI-assisted tools to identify, track and report online abuse and threats directed at journalists working in Central and South America. 

Developments in artificial intelligence (AI) were also talked about more broadly. AI is not as much of a central focus in Mexico as it is in other news environments around the world. However, discussions about and implementation of AI tools are beginning. One attendee raised the importance of considering how AI technologies can be used to protect journalists — particularly for those covering sensitive issues — instead of limiting their application to automation and efficiency.

Explore Regulatory Options

A particularly challenging dynamic in Mexico is that the Mexican government has played a major role in targeting journalists, including high-profile leaders like the outgoing president. This makes regulation a challenging strategy. Regulation could not only fall short of its intended goal but also backfire. Many participants shared that they have been working toward legislative protections for decades without seeing any improvement to the security of journalists in Mexico. One example of these efforts is the federal government’s Mechanism for the Protection of Human Rights Defenders and Journalists. It is laid out as a means for providing security protection to journalists who have received threats and/or experienced attacks. Some journalists receiving protection have critiqued the program on its effectiveness, raising concerns about some security personnel who have conflicts of interest, and/or having their applications for security denied.  

Nevertheless, there is still a sense among many that we need to continue to try to develop regulations for digital privacy and security that will minimize potential abuse. Regulations are viewed as a crucial reference point. Even with the government as a part of the problem, there was agreement that some form of regulation enforced by the government — albeit risky — is needed. 

Part of the desire for more regulation to support journalists stems from the recognition that regulations serve as benchmarks that journalists, academics, government officials and others can use to advance protections for the press.

It is also critical that any approach acknowledges and includes the diverse spectrum of journalism in the country. As one participant shared, areas outside of the major metropolitan locations are “invisible” when it comes to understanding the needs of journalists. In some rural areas of the country, for example, journalists craft handwritten newsletters for readers in their community which require different kinds of protections than technology-driven approaches to journalism.

Recognize the Importance of the State

Several participants shared the perspective that for journalism to be protected and supported, the Mexican government must be involved. This is a tenuous prospect given government officials’ continued threats and admonishments toward the press — like sharing the personal contact information of journalists during live television broadcasts — but attendees stressed that unless the State prioritizes a free press and protections for journalists, all of the valuable work being conducted to bolster the press will fall short. 

Often the State — across multiple levels of government — is a major player in targeting journalists and the press. Participants voiced the tension that currently exists in Mexico between the government and the press. The State serves as an arbiter with the authority to enforce protections for journalists, while at the same time journalists are threatened by official actors of the State. 

This is a complex, difficult situation. The incoming Mexican president, Claudia Sheinbaum, will assume office on October 2, 2024. She is expected to pursue many of the same policies as her predecessor, outgoing president Andrés Manuel López Obrador, but possibly take a less hostile posture towards the press. While some in attendance were cautiously optimistic about the potential for an improved relationship between the president and the press, many believed the current situation would not markedly improve.

Increase Pressure from the Global Community

Also stressed many times over is the important role the global community — including international government bodies, nation states and non-governmental organizations — needs to play in addressing journalist safety. 

The global community should step up its pressure to hold the Mexican government (and other governments that attack the press and/or do not uphold protections) accountable for failing to support and protect journalists. External pressure has the potential to shape (1) what regulations are considered within a given country and (2) what the leaders are willing to say to disparage the press. 

The global community can also provide important examples and morale boosts by continuing to take cases to court and bolstering protections through legal victories. As one participant shared, cases against political officials who target journalists are yielding positive results because they create legal precedent. These results foster protection for journalists even beyond the geographic bounds of a particular case. 

We also need safe ways for journalists to connect with each other around the world. Journalists can learn from each other, share experiences, tools and techniques for improving digital and physical safety, build moral support and more. 

Build Public Support for Journalism

Many of the recommendations above will not be as effective without the support of the public. The public needs to care about journalism and the safety of journalists, which many participants felt is currently not the case. A recent report by the Reuters Institute for the Study of Journalism found that only 35% of adults in Mexico trust the news media most of the time.

One contributor to this lack of appreciation and trust may be the growing political polarization in society and the ways that can be tied to the press.

Local outreach on behalf of local and regional papers was seen as a critical first step towards making connections with the public. Participants discussed the need for the public to trust journalists and view them as an important resource for staying informed about current events.

One participant shared:

Said another:

Another individual shared the importance of developing relationships with audiences to understand what they need from journalism. This recommendation will require news organizations and journalists to form closer relationships with their audiences — a complex topic outlined in CNTI’s latest issue primer.

Attract Young Talent

Attendees also considered how to better develop new journalists. The current situation in Mexico has led many younger individuals to avoid the profession. Several factors contribute to the trend — mostly related to the lack of safety and low financial compensation.

There is also a concern that the training journalists receive in education programs fail to prepare them for the current requirements of journalism in Mexico. 

Conclusion

This convening, in collaboration with the Organización Editorial Mexicana, discussed many of the online and offline security challenges currently faced by journalists in Mexico. This builds on other CNTI work in this area including issue primers about cyber threats and online abuse facing journalists, panel discussions at the Abraji World Congress, columns and more. CNTI is also addressing the security concerns of journalists with its “Defining News” initiative. This initiative will feature a global survey of journalists to better understand, in part, the online challenges they encounter. More information about this initiative is forthcoming. 

Convenings like this are just one of many initiatives within the larger work CNTI, an independent global policy research center, does to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. Please visit our website: www.cnti.org to see more of CNTI’s work and sign up to receive updates, and, as always, please contact us with questions and ideas.

Finally, please see the Appendix below for a list of participants at this event as well as other acknowledgements and information.

Appendix

About This Convening

CNTI’s cross-industry convenings espouse evidence-based, thoughtful and challenging conversations about the issue at hand, with the goal of building trust and ongoing relationships along with some agreed-upon approaches to policy. To that end, this convening adhered to a slightly amended Chatham House Rule:

1. Individuals are invited as leading thinkers from important parts of our digital news environment and as critical voices to finding feasible solutions. For the purposes of transparency, CNTI publicly lists all attendees and affiliations present. Any reporting on the event, including CNTI’s reports summarizing key takeaways and next steps, can share information (including unattributed quotes) but cannot explicitly or implicitly identify who said what without prior approval from the individual.
2. CNTI does request the use of photo and video at convenings. Videography is intended to help with the summary report. Any public use of video clips with dialogue by CNTI or its co-hosts requires the explicit, advance consent of the subject.
3. To maintain focus on the discussion at hand, we ask that there be no external posting during the event itself.

To prepare, we asked that participants review CNTI’s Issue Primers on online abuse and cyber threats. 

About CNTI

The Center for News, Technology & Innovation (CNTI), an independent global policy research center, seeks to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. CNTI’s cross-industry convenings espouse evidence-based, thoughtful but challenging conversations about the issue at hand, with an eye toward feasible steps forward. 

The Center for News, Technology & Innovation is a project of the Foundation for Technology, News & Public Affairs.

Acknowledgements

CNTI sincerely thanks the participants of this convening for their time and insights, and we are grateful to the Organización Editorial Mexicana (OEM), the co-sponsor and host of this convening. Special thanks to Francisco Torres Vázquez and Martha Ramos for their support and to Alejandro Jiménez for moderating such a productive discussion.

CNTI is generously supported by Craig Newmark Philanthropies, John D. and Catherine T. MacArthur Foundation, John S. and James L. Knight Foundation, The Lenfest Institute for Journalism and Google.

1. There is No Silver Bullet for Addressing Harms of AI In News While Still Enabling Its Benefits

Artificial intelligence will impact seemingly every industry, with the news media being no exception. This can be particularly challenging in the news and information space as the use of AI by various actors can sometimes work against informing the public and sometimes work towards it. In either case, new technological developments have added new challenges for separating the real from the fake. And while the media, technology companies and others are making attempts at identifying AI, the group was in agreement that no single solution will be completely effective. In fact, some research finds that current tools, such as labels of AI use, may actually do more harm than good.

So what is being done now to verify or authenticate AI-generated content? To date, the tool that has been furthest developed and has also received the most attention is “watermarking” — a technique where markers get embedded into a piece of content (e.g., image, audio, video, text, etc.) when it is first created. Proponents say watermarks help journalists and the public identify ill-intended changes to content they find online.

Several online platforms have begun implementing their own software and/or rules for asserting the authenticity of content, many of which comply with the Coalition for Content Provenance and Authenticity (C2PA) standard. OpenAI released an update that adds watermarks to images created with its DALL-E 3 and ChatGPT software. Google’s SynthID allows users to embed digital watermarks in content that are then detectable by the software. Other companies like Meta have focused on provenance, with policies that require disclosing content as being generated with AI. Across the technology industry, companies are taking note of provenance and implementing tools to assist users.

While developing these kinds of tools clearly has benefits, the group identified several important considerations and reasons the tools alone should not be seen as a solution in and of themselves:

• Preliminary research finds that labels related to AI in journalism can have an adverse effect on the public. Research examining the impact of content labeling raises several caution flags. First, overly broad labels about false and manipulated information can lead users to discount accurate information, suggesting labels need to be comprehensive and explicit about which content is false. Similarly, additional research on tagging content as AI-generated or enhanced finds, “… on average that audiences perceive news labeled as AI-generated as less trustworthy, not more, even when articles themselves are not evaluated as any less accurate or unfair” and that the effects are more common among people with higher pre-existing levels of trust.
• These types of content labels can also lead to an “implied truth effect” in which false information that is not tagged as such may be interpreted as authentic. Similar findings exist when studying provenance. On the more hopeful side, some findings suggest that the public can appreciate provenance details as long as they are comprehensive — poorly-detailed provenance can lead to users discounting authentic information. To that end, researchers are exploring what specific labels to use in a given context (e.g., AI generated, manipulated, digitally altered, computer generated, etc.) and how users interpret these terms.
• Current labeling techniques don’t differentiate between uses of AI that help inform rather than disinform. Indeed, some content alterations are done to help inform, which current methods of labeling don’t address. One participant shared an  example from Zimbabwe where a newsroom used chatbots to offer information in many more local dialects than Western-trained models could provide. There are also several non-publicly facing innovative AI uses such as fact-checking radio broadcasts or combing through and synthesizing news archives (which offer particular value for local news organizations). The current research suggests that a simple label acknowledging the use of AI risks automatic public rejection of what would otherwise add value to the news product. 
• We need to clarify the intended audience for each label. There is a lot of conversation about the benefit of provenance for the public but, as the group discussed, it may be more crucial for journalists and content creators. Marc Lavallee noted, there is “limited value in any kind of direct consumer-facing watermark or signal” and Richard Gingras said, “the value of provenance is probably more for the world of journalism than it is for the world of consumers.” Consider the example of information cataloged for original artwork. Celeste LeCompte noted, “most of that information is not generally revealed to the public but is rather something that is part of an institutional framework.”
• We need to better understand and articulate the various elements of identification: provenance, watermarking, fingerprinting and detection. In this convening, four similar but distinct forms were discussed. First is provenance, which refers to a “manifest or audit trail of information” to ensure content is “always attributable.” Provenance information is imperfect, however, because it can be input incorrectly or changed by malicious actors. Second is watermarks, a class of identifiers embedded directly into content which is more difficult to remove and considered to be more robust than provenance. A third technique called fingerprinting can serve as a lookup tool, like reverse image searches. Finally, there are what are termed detection methods. These use AI models to detect other AI models, though the development process remains challenging. They are the least robust and, as one participant asserted, more research needs to be done in this area. 

Again, the conclusion is not that watermarks are bad or of no use, but that they need to be fully thought through within the vast array of AI uses and considered as just one tool among many that are needed — which leads to the next takeaway.

2. We Need to experiment with a number of possible tools

As we further develop the efficacy of tools like watermarking, participants encouraged further experimentation with additional ways to help identify and explain various uses of AI content. As one participant remarked, “Doing something is better than doing nothing while waiting for the perfect solution.”

A few ideas shared by participants:

• SSL for AI: SSL, or Secure Sockets Layer, was designed to be an encryption tool for e-commerce, but is now used by virtually every website as a privacy and authentication tool. As one participant stated, there’s no “values determination,” just a determination on the content’s origin. Thus, there are no false positives or false negatives. Could publishers and technologists collaborate on something similar here? 
• Accessible Incentive Structures to Adopt Standards: Another idea was to use incentive structures for journalists and other responsible content creators to adopt certain standards and labeling techniques which could eventually become commonly understood. Search Engine Optimization (SEO), the process by which websites strive to rank higher in Google and other search engines, was offered as an example. While not a perfect corollary (with questions about gaming algorithms and the value of information that is not public facing) SEO, as originated, did offer a strong incentive and was pretty easy to adopt. How might something like that work for identifying AI content? And how could we measure its effectiveness? Getting the incentive structure right so that fact-based content gets promoted while “… inauthentic material or material of unknown provenance is lessened is really the place to focus,” suggested Lavallee. “If we get to a point where basically only bad actors are the ones not willing to use a system like this, I think that’s the threshold that we need to get to in order for it to be effective.”
• Training the public: Continued attention on AI literacy and education is important. As the research (cited above) shows, most of the public seems to distrust any use of AI in news content. A more nuanced understanding is important to allow journalists to use AI in ways that help serve the public. One participant shared information about how media and technology education are included in Finland’s national education plans and how news organizations there have also developed training materials for the general public. Information about how AI is used in news needs to be understandable for a non-technical audience but also allow people who would like further details to have access to that information. As such, per Tove Mylläri, “We believe that educating people to be aware and letting them decide themselves also builds trust.” Understanding what types of training materials are most effective is crucial for increasing knowledge about how AI is used in news. 

One important element for any of these tools, especially (but not limited to) those that are public facing, is communication. The publishers and others who implement these tools need to explain to their audiences and the general public what these tools do. It will take time for them to become recognized, commonly understood and utilized. The “nutrition labels” parallel provides a sense of that timeline. Nutrition labels, noted Anna Bulakh, are now generally understood and serve a valuable purpose, but that took experimentation about what kinds of information the public wanted and it took time for shoppers to become accustomed to them. In fact, it remains a work in progress and also carries with it the important consideration of who decides what goes into the label. News consumers are not yet used to “nutrition labels” for content. “Provenance is providing you with a nutritional label of content [so you can] be aware that it is AI manipulated or not AI manipulated,” Bulakh added. Provenance should be understood to mean information about the source of the material (i.e., the publisher, author, and/or editor) as well as what tools or mechanisms might be relevant to assessing the trustworthiness of the content.

3. The Best Role for Policy: Consider Industry Standards as a Start, Rethink Regulatory Structures, Lead by Example

Government policy and regulation can be critical in promoting and safeguarding the public good. They can also have lasting impact and as such must be thoroughly and carefully approached. Any drafted policy should consider its potential impacts both now and in the years to come. To facilitate this, the discussants laid out several insights:

• Established standards can help build effective policy. One part of the conversation focused on creating industry standards that, at least in some areas, can be used to inform effective legislation and regulation (recognizing these two forms of policy have different definitions which can also vary by country). Standards allow for experimentation and adjustment over time, could be developed for different parts of the system and, as past examples have shown, can then develop into effective policy. Consider, for example, the U.S. Department of Agriculture (USDA)’s development of organic food standards in the 1990s. The 1990 Organic Foods Production Act createdthe National Organic Program which was tasked with developing standards for organic food production and handling regulations. The USDA defines organic as a “labeling term that indicates that the food or other agricultural product has been produced through approved methods. The organic standards describe the specific requirements that must be verified by a USDA-accredited certifying agent before products can be labeled USDA organic.” The creation of this standard, remarked one participant, took time to develop but eventually led some consumers to seek out this type of product especially because they believe it follows specific criteria. Media content could follow a similar process. Once trusted standards are implemented, the public may seek content that conforms to those protocols, which would likely incentivize many industry actors to also use the standards. 
• In supporting this approach, former U.S. Representative & Chair of the Congressional Artificial Intelligence Caucus, Jerry McNerney, suggested that we fund AI standards agencies and, once created, enforce those standards through law, adding that it is important to have “the involvement of a wide spectrum of stakeholders,” particularly given the unique ways journalists are incorporating AI into their work.
• It’s time to rethink what structures of “regulation” should look like today.Several participants agreed we need to rethink what the structure of regulation looks like in an AI-incorporated environment in which developments occur rapidly with technology that is complex. One participant rhetorically asked, “do you really understand what you’re trying to accomplish?” It doesn’t mean we should walk away from complicated issues but we should fully think about the most effective approaches.
• Ethan Chumley offered that there “are close parallels and analogies” to cybersecurity perspectives “if we start to view the challenges of media authenticity and trust in images as a security problem.” Regulation will likely require more updates (1) as technologies evolve and (2) as standards are revised.
• This all takes time! Developing broadly adopted standards that can then develop into policy is time consuming. Bulakh suggests that “every new standard would take around 10 years to be accessible” to tool creators, distribution platforms, content creators and consumers. She points to the Coalition for Content Provenance and Authenticity (C2PA), one of the leading global standards, entering year 5, even though it has not been fully adopted. Another example is HTML standards for websites which, similarly, took many years to develop and are still evolving. We have past examples to use as models for timelines which need to be built in — let’s use them! 
• This is not to say that a standards-first approach is right for all areas. There may well be some aspects of managing use of AI that call for some government oversight more immediately —  though we still need to be sure the regulatory structures are effective and that the policies are developed in a way to serve the public long-term.
• One immediately available step is to lead by example. Many nods of agreement occurred when one participant pointed out that if governments want others to adopt and utilize various standards, rules or policies, they need to do so themselves. Governments can, in the immediate term, “start adopting these standards that are already out there in their own datasets,” said Elik Eizenberg, which would likely create momentum for the private market to follow. One of the most powerful tools governments have, Eizenberg added, is to “lead by example.” In the discussion that followed, another participant added that, conversely, many current policies relating to misinformation have built-in exceptions for politicians. 

4. Successful Standards, Uses & Guardrails Require Technology Companies’ Active Participation

“Journalists [and] media houses cannot cope with these issues alone without technology companies,” remarked one participant to the nodding approval of others. Another person added, “Open standards are developed by technologists. It’s [technologists’] job … to come together to provide access to those tools … and make them more accessible.” Media houses can then communicate and “change consumer behavior.” 

Tanit Koch spoke of the importance of technology companies in helping guard against those with bad intentions: “We need tech companies and not only because of the scale and the speed that disinformation can happen and is happening on their platforms, but simply because they have the money and expertise to match the expertise of the bad actors. We definitely and desperately need more involvement by those who feel a sense of responsibility to create open source tools to help the media industry detect what we cannot detect on our own and all of this full well knowing that the dark side may always try to be ahead of us.”

A separate point was raised about whether there was a role for technology companies, and policies guiding them, in helping users better understand certain risks or benefits associated with the use of certain technologies. “When I take a pill, there’s a warning label,” offered Paul Cheung, but these risks are not as clearly defined in the online space. Thus, consumers “have no information to assess whether this is a risk they’re willing to take.” People may use a certain technology tool or piece of software “because it’s free and fun” without knowing the risk level. And those risk levels likely vary, suggesting a model similar to the U.S. Food and Drug Administration (FDA) or Federal Aviation Administration (FAA) may be a better route than a “one-size-fits-all” approach. 

Understanding these risks relates to the discussion on building trust that occurred during CNTI’s first AI convening. As reported following that gathering:

5. Research, Research, Research

To date, research about labeling AI content (and how users engage with labels) is limited. We need much more data to gain a fuller understanding of the best strategies forward, as well as which strategies are likely to fall short, backfire or possibly work in some areas but not in others. To develop a deeper understanding of what, why and how certain policy and technology approaches work better than others, we need to conduct more studies, replicate findings and build theories. Approaches must also reflect geographic diversity by including researchers representing a range of local contexts and communities and by examining how people in diverse, global contexts are similar and/or unique in their interactions with AI-related news content. For example, U.S./European research that focuses solely on strategies to address internet disinformation would not serve well those places where radio is still the largest news medium. We need to provide the resources and support for this work — starting now.

Several researchers in the room noted that the existing literature does not yet fully grasp how users interact with provenance information or how the tools being developed will influence user behavior. 

Felix Simon shared recent preliminary research he’d conducted in collaboration with Benjamin Toff that featured a striking finding: “For our sample of U.S. users, we found, on average, that audiences perceived news labeled as AI-generated as less trustworthy, not more, even when articles themselves were not evaluated as any less accurate or unfair.” Yet, when the authors provided users with the sources used to generate the article, these negative effects diminished. Further research is warranted to better understand how the public interprets labels on AI-generated articles and how to best present this information.

When it comes to watermarks in particular, “we have some directional indications about efficacy but we do have extremely limited data in this area,” offered Matt Perault. Based on the limited data and research, he presented four key research questions that need to be addressed:

1. Will disclaimers and/or watermarks be implemented correctly?
2. Would users actually observe them?
3. Would disclaimers and/or watermarks have a persuasive effect?
4. What effects would watermark and/or disclosure requirements have on competitiveness and innovation?

Answers to these questions will assist in the development of evidence-based policy.

6. Best Steps for Newsrooms: Innovate With a Degree of Caution

Technology has revolutionized the media many times over (e.g., the printing press, radio, television, the internet, social media, streaming, etc.) with AI being the latest example of an innovation that will change how reporters gather and share information and how consumers take it in.

Panelists made a number of workplace recommendations that would help journalists incorporate AI into their reporting and build a better relationship with their audiences.

• Newsrooms need to embrace AI technology, but do it cautiously. They must be willing to experiment with new tools to see what works for them and what helps audiences better understand the news. Offered Charlie Beckett, “The crisis in journalism at the moment is about connecting the ton of good quality stuff out there to the right people in the optimal way that doesn’t make them avoid the news.” It was further noted that quality reporting requires diligent research and thorough questions and that a similar approach should be applied to the exploration and adoption of new technology. Participants discussed a number of existing and developing technologies that could spur newsrooms to adopt the use of AI to support their work (see sidebar).  
• Conversely, concerns remain about how AI models use journalists’ works. Courtney Radsch asserted, “As we see more generative AI content online, less human-created information, the value of journalism, I think, goes up. So we should be thinking about a model that can allow us to have some say over the system.” The complex pros and cons of methods such as licensing or copyright on the nature and effectiveness of the knowledge ecosystem, including that they can hinder broad distribution and reward quantity irrespective of quality, were mentioned but were covered more in depth at CNTI’s first AI Convening, as written about in the summary report.
• Journalists need to apply layers of transparency in their work, just as they expect from the people and organizations they cover. Innovation and transparency are critical to serving local communities and fortifying the journalism industry for the digital age. But remember that “transparency has multiple meanings, each of which must be addressed.” First, journalists must offer the same level of transparency that they demand of others. At a non-technical level, that means explaining why a particular story is being told at that time. But it also means clearly explaining how AI is used to report, create and produce content including attributions and points of reference in the output of AI-driven answer engines (e.g. ChatGPT, etc.). Research has shown that some responses by AI-driven answer engines can be biased by the articulation of the source material used to feed them. News consumers would benefit from understanding related references and attributions which can help audiences rebuild trust in the media.
• Recognize that there is more to AI than the content being produced. Jeff Jarvisshared his thoughts on the ABCs of disinformation, which a 2019 report by Camille François of the Berkman Klein Center for Internet & Society at Harvard University defined as manipulative actors, deceptive behavior and harmful content. Jarvis summarized, “We have to shift to the ABC framework — that is to say actors, behavior and content,” rather than a singular focus on content. While journalists may be able to identify those seeking to sew harm through diligent research and reporting, it is difficult to persuade news consumers that such people act with malicious intent. 
• Another concept offered was that of “fama,” a Latin word dating back to Europe before the printing press that brings together rumor and fame to form the concept of believing something to be true because it was said by someone the listener trusts. Its modern equivalence is believing in news — or conspiracy theories — because they are uttered by a trusted voice. As noted by Deb Ensor, “We don’t often think about our audiences in terms of their behaviors and how they share or trust or value or engage with their information suppliers.” Those with ill intentions then appeal to this behavior with deceptive tools, such as bots and troll farms to spread disinformation. With the advent of AI, these actors have even more tools at their disposal and journalists need partners in technology and research to keep up.

Next Steps & Additional Information

This is the second in a series of convenings CNTI will host on enabling the benefits of AI while also guarding against the harms. It is just one of many initiatives within the larger work CNTI, an independent global policy research center, does to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. Please visit our website: www.cnti.org to see more of CNTI’s work and sign up to receive updates, and, as always, please contact us with questions and ideas.

Finally, please see the Appendix below for numerous valuable resources shared by participants of this event as well as other acknowledgements.

Appendix

About This Convening

CNTI’s cross-industry convenings espouse evidence-based, thoughtful and challenging conversations about the issue at hand, with the goal of building trust and ongoing relationships along with some agreed-upon approaches to policy. To that end, this convening adhered to a slightly amended Chatham House Rule:

1. Individuals are invited as leading thinkers from important parts of our digital news environment and as critical voices to finding feasible solutions. For the purposes of transparency, CNTI publicly lists all attendees and affiliations present. Any reporting on the event, including CNTI’s reports summarizing key takeaways and next steps, can share information (including unattributed quotes) but cannot explicitly or implicitly identify who said what without prior approval from the individual.
2. CNTI does request the use of photo and video at convenings. Videography is intended to help with the summary report. Any public use of video clips with dialogue by CNTI or its co-hosts requires the explicit, advance consent of the subject.
3. To maintain focus on the discussion at hand, we ask that there be no external posting during the event itself.

To prepare, we asked that participants review CNTI’s Issue Primers on AI in Journalism, Algorithmic Transparency and Journalistic Relevance as well as the report from CNTI’s first convening event. 

Resources Shared by Participants

Participants at our convening event shared a number of helpful resources. Many of these resources are aimed at assisting local newsrooms. We present them in alphabetical order by organization/sponsor below. 

Several news organizations were mentioned for their use of AI in content creation. One that received recognition was the Baltimore Times for its efforts to better connect with their audience through the use of AI. 

Participant Aimee Rinehart shared a blueprint for her CUNY AI Innovation project. This project aims to create a journalism-specific LLM AI model for journalists and newsrooms to use.

A novel radio fact-checking algorithm in Africa, Dubawa Audio Platform, was discussed to show how countering mis- and disinformation can be done in non-Internet-based contexts. The platform was initiated by a Friend of CNTI, the Centre for Journalism Innovation and Development (CJID). The Dubawa project received support from a Google News Initiative grant.  

Information was shared about the Finnish government and academic community’s campaign on AI literacy, Elements of AI. This project aims to raise awareness about the opportunities and risks of AI among people who are strangers to computer science, so they can decide for themselves what’s beneficial and where they want their government to invest. Free educational material also exists for children. Curious readers may also learn about related research here.

The topic of transparency was discussed and a 2022 report by Courtney Radsch for the Global Internet Forum to Counter Terrorism (GIFCT) provides an important overview of transparency across various industries.

A number of participants shared information about technological tools:

• Google’s Pinpoint project helps journalists and researchers explore and analyze large collections of documents. Users can search through hundreds of thousands of documents, images, emails, hand-written notes and audio files for specific words or phrases, locations, organizations and/or names.
• Google’s SynthID is a tool to embed digital watermarks in content to assist users with knowing the authenticity and origin of content. 
• Microsoft’s PhotoDNA creates a unique identifier for photographs using its system. This tool is used by organizations around the world — it has also assisted in the detection, disruption and reporting of child exploitation images. 

Information was shared about Schibsted, a Norwegian media and brand network, organizing the development of a Norwegian large language model (LLM). It will serve as a local alternative to other general LLMs. 

The Tow Center for Digital Journalism at Columbia University released a recent report by Felix Simon titled “Artificial Intelligence in the News: How AI Retools, Rationalizes, and Reshapes Journalism and the Public Arena.” 

A participant shared an innovative use of AI in Zimbabwe in which the AI model has been trained using local dialects. The chatbot is more representative of the users in that region when compared to other general AI language models. 

We appreciate all of our participants for sharing these resources with CNTI.

About CNTI

The Center for News, Technology & Innovation (CNTI), an independent global policy research center, seeks to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. CNTI’s cross-industry convenings espouse evidence-based, thoughtful but challenging conversations about the issue at hand, with an eye toward feasible steps forward.

The Center for News, Technology & Innovation is a project of the Foundation for Technology, News & Public Affairs.

Acknowledgements

CNTI sincerely thanks the participants of this convening for their time and insights, and we are grateful to the University of Southern California’s Annenberg Capital Campus, the co-sponsor and host of this AI convening. Special thanks to Adam Clayton Powell III and Judy Kang for their support, and to Steve Waldman for moderating such a productive discussion.

CNTI is generously supported by Craig Newmark Philanthropies, John D. and Catherine T. MacArthur Foundation, John S. and James L. Knight Foundation, the Lenfest Institute for Journalism and Google.

1. Better Articulation, Categorization and Understanding of AI Is Essential for Productive Discussions.

Cross-industry experts unanimously agreed on the need to work together to better define AI and articulate clear categories of use. This will enable a common understanding and allow for more productive conversations. Right now, that is not happening. As one participant remarked, “We jump into the pool … and we’re not even talking about the same thing.”

An overarching definition of AI: The participants chose not to spend their limited time together writing a precise definition of AI, but they shared definitions they have found to be useful starting points including those from:

• Council of the EU: “systems developed through machine learning approaches and logic- and knowledge-based approaches.”
• AP Stylebook’s AI chapter: separate definitions for “artificial intelligence,” “artificial general intelligence,” “generative AI,” “large language models” and “machine learning.”
• Melanie Mitchell: “Computational simulation of human capabilities in tightly defined areas, most commonly through the application of machine learning approaches, a subset of AI in which machines learn, e.g., from data or their own performance.”

Research backs up the need for, and lack of, clarity around AI. A lack of conceptual clarity around AI, changing interpretations of what qualifies as AI and the use of AI as an umbrella term in practice and policy can make potential violations of law incredibly hard to identify and enforce. Recent legislative activity around AI, including the European Union’s AI Act has been criticized for offering a broad legal definition of “general purpose AI systems,” making it difficult to know what would be included or not included in this scope. Canada’s Bill C-27, similarly, does not define the “high-impact systems” it is regulating. It is important to proceed from shared understandings of the technology at issue and the harms policymakers hope to address. For example, attempting to write laws touching only “generative AI” (e.g., chatbots, LLMs) could inadvertently prohibit processes that underlie a range of technological tools, while applying requirements to broad or vaguely defined categories of technology could lead to legal uncertainty and over-regulation.

Within these definitions are several categories of use that must also be clearly differentiated and articulated. They include: 

The scope of AI: AI is not new – in general nor in journalism – and represents a much broader set of technologies than simply generative AI (GAI) or large language models (LLMs). Nevertheless, one participant noted research finding many burgeoning AI newsroom policies narrowly define AI as GAI and LLMs, which “speaks to the challenges of grasping this set of technologies.”

The type of AI use: It is important to differentiate among the various types of AI use related to news. There are uses for news coverage and creation and, within that, questions around the degree of human vs. AI involvement in published content. There are uses that help with newsroom efficiency and cost savings, such as transcription, that don’t necessarily result in public-facing AI output. There are uses for news distribution and access, such as translation. At least one participant remarked on the tendency, when thinking about LLMs, to limit the scope of its definition to text-based GAI rather than comprehensively conceptualize GAI to include other formats such as XtownLA, which uses AI models for reporting on public hearings.

Who the user is: It is critical to specify who the user is at each point in the process of AI use so that appropriate responsibility, and perhaps liability, can be attributed. Is it newsrooms? Members of the public? Technology or third-party companies? Governments? This articulation is often missed.

The part of the AI system being accessed: A few participants talked about the importance of understanding and differentiating among the different levels of AI systems. The first level is, for example, the LLM being built. The second level is the API or corpus (e.g., all data being used as inputs) of what is in the model or further steps such as reinforcement learning through human feedback (RLHF). Third is the application use level, such as ChatGPT, in which humans do not actually interact with the model itself. Each of these, as one participant noted, should have different policy considerations.

Another pitfall in current discussions occurs when we don’t take time to articulate what is neither a part of AI nor tied directly to its use. This is particularly important when it comes to guarding against harms. Participants articulated the need to distinguish between which issues are attributed to the internet and social media age in general and which issues are linked specifically to AI technologies.

Better understanding of these definitions and categorizations can also help build trust, which several participants named as critical for positive outcomes from AI use and policy development. One participant asked, “How do we generate trust around something that is complicated, complex, new and continuously changing?” Another added, “Trust is still really important in how we integrate novel technologies and develop them and think two steps ahead.”

For Further Consideration

How do we create better knowledge and understanding? If we want this articulation to lead to better understanding and knowledge, how do we get there? How can we make that knowledge more accessible to journalists, researchers and policymakers? What can technology companies do? How can CNTI help distribute this knowledge?

2. Whether a Particular AI Use Is a Benefit or Harm to Society Depends on Its Context and Degree of Use, Making Specificity Vital to Effective Policy.

Whether a particular use of AI is a benefit or a harm to society can depend on several factors, including the degree of use, the strength of protective actions and the subject matter surrounding the use. Effective policy must include specific and context-sensitive considerations. A prime example of this, discussed extensively by the group, is algorithmic transparency. (For more on this topic, see CNTI’s related Issue Primer.)

While there was general agreement on the importance of some level of transparency about how models are built and how newsrooms, journalists or others use AI – and, in most cases, agreement that more transparency is needed than currently exists – participants also discussed instances when transparency might be counterproductive. Is there a point at which the level of transparency carries more risk than value or causes more confusion than clarity – for instance, where “the level of transparency and detail … can actually undermine the security and safety of the models”? Determining where to draw that line is critical but difficult. 

For example, optimal transparency around how AI is used in hiring processes or in making bail recommendations might differ from optimal transparency around the trillions of tokens that go into a LLM. The latter may not be as useful for unrestricted access to the public because of such varying abilities to evaluate this knowledge, and there could be a point at which the benefit of transparency is outweighed by the risk of malign actors abusing these systems. There seems to be clear value, though, in public transparency about whether content was fully AI-generated, was AI-generated with human involvement or came only from a human. 

There were some different opinions about how to – or who should – determine how transparency extends to the broader public. One individual suggested “more transparency is better,” and then journalists can “make choices about how we describe all of this.” Participants agreed that we “have something to grapple with” and must work toward this together. These conversations call for “precision in the way we are discussing and analyzing different use cases so we ensure that policy that is created is specific to a given situation,” the challenge of doing so amid technology’s rapid evolution notwithstanding.

Another discussion surfaced about the benefits of AI that increased through advancements in LLMs, which AI policy may want to protect: transcription and translation. We “almost gloss over some of those [tools like transcription] because they’re such routinized things,” but “it is really the kind of scale of deployment that’s effective and interesting.” Similarly, translation has been used for a long time, but GAI has scaled it to create new opportunities for public use and benefit.

For Further Consideration

As we think about benefits of AI use, what are other AI practices that can be scaled up in ways that bring value to societies more broadly? What methods can be used to help determine how and when a benefit might become a harm, or vice versa?

3. Even When Policy Is Groundbreaking, It Must Also Take into Account How It Relates to and Builds on Prior Policy.

While it is important to focus on clear, specific definitions when constructing new regulations, the group recognized that policy development is a layered process, and it is necessary to consider it in the context of previously adopted policy. So while developing clear definitions around AI matters, existing policy will inevitably impact new policy. 

Take, for example, anti-discrimination law. In many countries, discrimination is illegal regardless of how it occurs, including via AI. The specific definition of AI doesn’t really impact whether its use violates such laws. In a similar example, European Union and Canadian policies influence how AI gets trained and used in the context of data protection. Even if many of today’s AI systems did not exist when data protection laws were written, they still have an effect when it comes to AI. As one participant put it:

While there was clear agreement that definitions are important, at least one participant also asked: Have we reached a time where being clear about which principles should be protected is as important as the definitions themselves? Those principles can be articulated in ways that are technology-agnostic. Would this kind of approach help us create policy that can endure future technological developments? Or perhaps the answer is a nexus point of definitions and principles. 

A core principle for CNTI, and for this convening, is a free and independent press, which is under intense pressure in many parts of the world. Could we look at the various ways in which uses of AI in journalism impact that principle and approach policy development with that lens? 

Perhaps. But as other participants pointed out, that approach can be problematic if it is not done well, and definitions remain essential considerations. For example, a 2023 bill in Brazil proposed changing its Penal Code to include an article doubling the penalty for using AI to commit online fraud without actually defining AI – thus validating concerns about the impact of unclear definitions in legislative policy.

For Further Consideration

When it comes to AI use in journalism, what is the right balance between broad principles and specific definitions? Are there examples of successful regulatory structures that already exist, such as anti-discrimination policies, that can help us strike that balance? 

4. One Policy Goal Should Be to Address Disparities in the Uses and Benefits of AI – and Particularly GAI – as a Public Good.

The importance of greater parity arose many times throughout the day. There are currently numerous global disparities in access to, use of and value of AI models. There was strong consensus that we need to work together on creating equality around AI as a public good, including the use of AI to help close gaps in news access. Inequalities work against the public good, which public policy is intended to protect. Use of and access to AI tools need to be democratized. How can public policy help that? Is this a case where organizational policy is as beneficial as — or perhaps more beneficial than — legislation?

Some specific areas of disparity discussed at the convening include: 

The content in current AI models misses many people and many parts of the world. Certain parts of the world can’t realize the same potential of AI, especially GAI, because a substantial proportion of the world’s languages are not accounted for in LLMs (either because they do not have enough training data to create them or because tools aren’t well-constructed for them). While the practical effect of this disparity is easy to grasp, some less-considered impacts include reduced public trust in AI tools and their outputs. 

GAI models often replicate existing social biases and inequities. Participants questioned the ability of many AI models to “reflect the full breadth of human expression,” noting examples ranging from the generation of photos of engineers as white men to the inclusion of QAnon conspiracy theories in LLM training data. Research supports this skepticism.

AI models, and the companies providing them, are largely exported from only a few countries. In many parts of the world, technological systems like GAI applications are largely imported from a small number of (often Western) companies. This means data used to build the models, as well as the models and tools, are imported from people and entities who likely do not understand the nuances of the information environment of the end users. This has led to greater public skepticism about — and even distrust toward — the implementation of these tools, both in general and in journalism specifically. One participant noted:

News is not a digital-first product in all parts of the world. Print, television and radio are still popular modes of news consumption in many countries. And there remain areas with much less internet accessthan others. So, as there is a push to digitization, “there’s an extent to which AI is still going to end up on the paper in some way, shape or form and we have to think about what that type of signaling may mean.” This raises the question, not yet given much consideration, of how AI use and policy translate to print. 

Discussions should also consider ways policy can support use of AI as a means to help close gaps in news access. There are parts of global society with less access to independent, fact-based news – whether the result of financial downfalls (e.g., news deserts in the U.S.), government control or high-risk environments such as war zones. Could AI be helpful here? If so, how? “We need to look at ways that we can rebuild newsrooms and do so in a way where it’s not just the large players that survive,” expressed one participant, “but local newsrooms survive, that everyone can actually have access to information.”

Wealthier news publishers have a greater advantage when it comes to AI use and licensing. There are currently clear financial advantages for large, well-resourced — and often Western — national and international news outlets. As pointed out by one participant: “Licensing is one way to obtain information, but you need to have funds, you need to have means … those with the biggest purses can obtain data and can possibly benefit more from AI. … That is bad from a public policy perspective because it means we’re not actually democratizing access to model development.” 

The varying relationships between governments and the press must be considered in policy discussions. In some contexts, policymakers simply may not value the principle of an independent press. In other contexts, such as in Caribbean nations, financial support via government ad spending is critical for the sustainability of media organizations, leading to a hesitance to create friction with their primary sources of funding. If governments do not trust media organizations’ adoption of AI tools, their actions can create economic problems for publishers or journalists.

For Further Consideration

What roles should legislative versus organizational policy play when it comes to addressing disparities in the use of AI as a public good?

5. Both Inputs and Outputs, at All Stages of Building and Using AI, Need to Be Considered Thoroughly in Policy Development.

The last portion of the day was intended to be focused on copyright law, but many of the points raised during the discussion have broader policy implications. This section summarizes these points first, then makes note of considerations specific to copyright and AI in journalism.

A substantial and, as some participants noted, justifiable amount of attention and litigation has focused on the inputs of AI systems, particularly on what data models are being trained on, especially when it comes to news content. Less attention has been paid to the other end of the equation: these systems’ outputs. As one participant noted, there is only one ongoing case related to AI outputs. There was a general acknowledgement that policy and policy discussions must consider the totality of the system. 

Two key issues emerged around AI outputs: ownership and liability. Both issues connect to copyright law and will likely be addressed in courts and public policy. One participant outlined three potential policy approaches:

1. No AI-generated output is copyrighted and, thus, everything is in the public domain. This is the current policy approach in countries like the U.S.
2. Some form of copyright of AI-generated output is recognized, as long as there is some degree of human intervention, and the human would receive the copyrights.
3. AI-generated output receives short protections (e.g., 10 to 15 years) that could be registered to those who want to profit from transformative works.

Each option carries critical implications that are often lost in debates around AI inputs. Where is the cutoff point for AI-generated content? At what point in the editing process do we recognize content as having been transformed by AI and, therefore, no longer protected? Would this include the use of software, such as Photoshop, that have integrated AI tools? What does “human intervention” entail? And, for option three, what would be the duration of short-term protections (an option currently available in countries such as the United Kingdom)? Any policy, the group agreed, needs a clearly defined auditing process that includes evidence of steps taken in the content creation process. 

Participants also discussed the lack of clarity around output protections when it comes to patterns of language that models learn from snippets of words (rather than agreed-upon protections for creative expression like written articles). This ambiguity underlies other critical questions around issues like disinformation, such as decisions about whether to pull content like QAnon conspiracy theories out of model training data.

Clarity around outputs should be added to (but not replace) conversations about inputs: decisions around what data AI models are, or should be, trained on. As one participant noted, “Sticking to an understanding of the inputs here is important when we describe this interplay between the models and journalism, because journalism very much needs to be rooted in fact-based reporting.” Some suggested that the inputs question is potentially the easier issue to solve outside the bounds of policymaking: “You just pay [for data].” Though, it is not clear where current copyright law would fall on this and, as noted earlier, can lead – and has led – to a winner-takes-most approach where technology companies and news publishers with the most money and resources have the most to gain.

This discussion also included a broader conversation about liability, both within the context of copyright policy and beyond it. Participants noted that one critical area in AI policymaking is about the various layers of responsibility for the application of expression via AI tools including the model itself, its API, and its application (e.g., ChatGPT):

One element that came up at several points is the need for transparency from AI model developers in order to have more open discussions around how to apportion responsibility.

Spotlight on Copyright Law

Opportunities For Further Action

In addition to the areas for further consideration noted above, the convening introduced several potential opportunities for future work, including:

• The important remaining question of definitions of journalism in policy. While time limitations did not allow for a more thorough discussion of this question in this convening, participants noted a need to focus on definitions of journalism in policymaking alongside definitions of AI.
• Mapping the various elements of copyright and intellectual property protection and their impacts on journalism. While CNTI’s Issue Primer on copyright lays out the current state of copyright policy related to journalism, participants discussed the value of better understanding how exactly these laws apply to AI use in news. As one participant noted: “We should not only look at what makes sense for us in the here and now” but also “in contexts where different languages are spoken, where access is a huge problem, where skills are a huge problem, where disinformation has very different connotations … what can be the possible consequences for people who are more vulnerable, less empowered, in a different part of the world, and where the consequences can be way worse.”
• A need to take stock of AI practices (separate from guidelines), and establish a living repository of AI use cases related to journalism. CNTI developed a table of potential AI benefits and harms related to journalism (shown below) as a starting point for this discussion, though this was not an exhaustive list, and there is opportunity to develop it further into a digital resource. Participants also noted the need for an open database or repository of actual AI use cases (including their positive and negative impacts) that journalists and others creating and delivering fact-based news can add to. Some foundational work around this exists.

Appendix

List of Participants

About This Convening

CNTI’s cross-industry convenings espouse evidence-based, thoughtful and challenging conversations about the issue at hand, with the goal of building trust and ongoing relationships along with some agreed-upon approaches to policy. To that end, this convening adhered to a slightly amended Chatham House Rule:

1. Individuals are invited as leading thinkers from important parts of our digital news environment and as critical voices to finding feasible solutions. For the purposes of transparency, CNTI feels it is important to publicly list all attendees and affiliations present. Any reporting on the event, including CNTI’s reports summarizing key takeaways and next steps, can share information (including unattributed quotes) but cannot explicitly or implicitly identify who said what.
2. CNTI does request the use of photo and video at convenings. Videography is intended to help with the summary report. Any public use of video clips with dialogue by CNTI or its co-hosts requires the explicit, advance consent of the subject.
3. To maintain focus on the discussion at hand, we asked that there be no external posting during the event itself.

Participants were not asked to present prepared remarks; rather, this was a thoughtful guided discussion. To prepare, we asked that participants review CNTI’s Issue Primers on AI in journalism and modernizing copyright law.

Resources Shared by Participants

Participants at our convening event shared a number of helpful resources. Many of these resources are aimed at assisting local newsrooms. We present them in alphabetical order by organization/sponsor below. 

The American Journalism Project (AJP), which has announced a new partnership with OpenAI, serves as a useful resource for local newsrooms, bolstering local news projects to ensure all communities in the U.S. have access to trusted information. 

The Associated Press (AP) has launched, in addition to its Stylebook AI chapter, five new tools to improve workflow efficiencies in newsrooms with a focus on automation and transcription services. The AP also has assigned journalists on its global investigative team and beyond to cover artificial intelligence tools and their impacts on communities.

Another resource that organizations may find useful is CrowdSmart’s research on AI and conducting customer interviews, using AI to measure conversations and engage with human subjects, with the benefit of quantifying conversations in real time. 

Google has developed Pinpoint, a digital tool for analyzing and transcribing documents, that organizes and facilitates document collection. The company has also launched its Data Commons resource which enables users to access publicly available data from around the world.

Microsoft’s Journalism Hub shares tools to promote sustainable approaches to local journalism and includes a partnership with NOTA, an journalist-founded AI startup aiming to streamline newsroom processes without replacing journalists. Meanwhile, Microsoft’s open-data campaign aims to address inequalities in access by developing datasets and technologies that make data sharing easier. 

Finally, Respeecher, a novel startup founded in 2018, uses artificial intelligence to generate synthetic speech. The company has partnered with video game developers and motion picture studios to produce voices for characters – both fictional and real. 

We appreciate all of our participants for sharing these resources with CNTI.

About CNTI

The Center for News, Technology & Innovation (CNTI), an independent global policy research center, seeks to encourage independent, sustainable media, maintain an open internet and foster informed public policy conversations. CNTI’s cross-industry convenings espouse evidence-based, thoughtful but challenging conversations about the issue at hand, with an eye toward feasible steps forward.

The Center for News, Technology & Innovation is a project of the Foundation for Technology, News & Public Affairs.

Acknowledgements

CNTI sincerely thanks the participants of this convening for their time and insights, and we are grateful to the Computer History Museum, the co-sponsor and host of this AI convening. Special thanks to Dan’l Lewin, Marguerite Gong Hancock and David Murphy for their support, and to Marietje Schaake for moderating such a productive discussion.

CNTI is generously supported by Craig Newmark Philanthropies, John D. and Catherine T. MacArthur Foundation, John S. and James L. Knight Foundation, the Lenfest Institute for Journalism and Google.