Jefferson Fellow Louise Matsakis practices her
surgical techniques at Queen's Medical Center
in Honolulu, Hawaii.

Journalists gather in Hawaii to learn about AI, peace journalism
12 journalists from the Asia-Pacific region, including the US, gathered in Honolulu this week for the first leg of the 2026 Jefferson Fellowships. This year, the fellows are exploring AI and its impacts.

We’ve heard from experts in a number of domains, from cancer surgeons to State emergency planners to legislators at the state capitol to marine biologists. The cross-cutting theme is that they see AI only as a tool, and that the human element is indispensable. No one said that they plan to replace staff with AI. 

Jeff fellows sail off to Coconut Island to hear about
how the Hawaii Institute of Marine biology
uses AI.

My portion of the program was framing reporting AI in terms of peace journalism. After a PJ 101 lecture (definitions, principles, and examples), I offered the journalists advice on how PJ can transform reporting from panic-driven, jargon-laden, sensational tech journalism into a more socially responsible public discourse.

I shared these tips on bringing PJ’s principles to AI and tech reporting:

1. Reject us vs. them, good guy vs. bad guy, AI as savior vs. AI as destroyer, tech evangelists vs. doomsdayers narratives. Look for the gray area, the nuance, in between the extremes.
2. Report with human rights center-stage, especially privacy, worker’s rights, and the right to live in a clean, safe environment. Prioritizing privacy and digital rights ensures that voices from vulnerable communities are heard—communities that are disproportionately targeted by facial recognition, predatory policing, security cameras, and data exploitation. Prioritize also the environmental impact of data centers, particularly on the marginalized communities where they are often located.
3. Reject corporate or government PR. Fact check, verify claims, and be skeptical of claims that “AI did it” ((e.g. Hugging Face) rather than a company accepting responsibility for AI missteps.
4. Report about algorithmic biases against groups, nations, and regional languages. AI models are often founded on outdated, biased, exclusionary, sexist or racist data that can lead to responses that discriminate against poor or minority communities.
5. Carefully choose words.  Avoid anthropomorphizing AI with misleading terms like "thinking," "feeling," or "sentient." These brush off human accountability and choice. Avoid alarmist language, too—"unstoppable,” “out of control,” “apocalypse,” “doomsday,” “disaster,” “terminator,” etc.

6.      Offer counternarratives that debunk media created myths and misperceptions. Challenge the myth that AI is inherently objective, neutral, or free from human error. Challenge the myth that AI goes rogue on its own.

7.      Report to give a voice to the marginalized—indigenous, poor communities, speakers of regional languages, and rural/isolated/disconnected communities. Avoid elite only sourcing and framing (Big Tech companies and their leadership, venture capitalists, and government cheerleaders). Report on data sovereignty.

I love this group, which is energetic, curious, and fun to work with.

We’re headed to Tokyo tomorrow to continue our study and reporting tour. Stay tuned for details.

State Rep. Julie Reyes Odo gives 
the fellows a tour of the HI state capitol.