E18
September 20, 2024
The stories we tell ourselves about AI
Hosted by
Alix Dunn

The adoption of new technologies is driven by stories. A story is a shortcut to understanding something complex. Narratives can lock us into a set of options that are…terrible. The kicker is that narratives are hard to detect and even harder to influence.But how reliable are our narrators? And how can we use story as strategy?The good news is that experts are working to unravel the narratives around AI. All so that folks with public interest i...

On Computer Says Maybe, host Alix Dunn interviews visionaries and cutting edge researchers to help you wade through the wacky and worrying world of new technology.
Contact us with your feedback and suggestions, or if you’re keen to explore your area in conversation. We have rotating co-hosts and expert guests that help us deep dive into a particular topic. Write to us anytime at team@saysmaybe.com.
Show Notes

Applications for our second cohort of Media Mastery for New AI Protagonists are now open! Join this 5-week program to level up your media impact alongside a dynamic community of emerging experts in AI politics and power—at no cost to you. In this episode, we chat with Daniel Stone, a participant from our first cohort, about his work. Apply by Sunday, September 29th!

The adoption of new technologies is driven by stories. A story is a shortcut to understanding something complex. Narratives can lock us into a set of options that are…terrible. The kicker is that narratives are hard to detect and even harder to influence.

But how reliable are our narrators? And how can we use story as strategy?

The good news is that experts are working to unravel the narratives around AI. All so that folks with public interest in mind can change the game.

This week Alix sat down with three researchers looking at three AI narrative questions. She spoke to Hanna Barakat about how the New York Times reports on AI; John Tanner, who scraped and analysed huge amounts of YouTube videos to find narrative patterns; and Daniel Stone, who studied and deconstructed metaphors that power collective understanding about AI.

In this ep we ask:

  • What are the stories we tell ourselves about AI? And why do we let industry pick them?
  • How do these narratives change what is politically possible?
  • What can public interest organisations and advocates do to change the narrative game?

Hanna Barakat is a research analyst for Computer Says Maybe, working at the intersection of emerging technologies and complex systems design. She graduated from Brown University in 2022 with honors in International Development Studies and a focus in Digital Media Studies.

Jonathan Tanner founded Rootcause after more than fifteen years working in senior communications roles for high-profile politicians, CEOs, philanthropists and public thinkers across the world. In this time he has worked across more than a dozen countries running diverse teams whilst writing keynote speeches, securing front page headlines, delivering world-first social media moments and helping to secure meaningful changes to public policy.

Daniel Stone is currently undertaking research with Cambridge University’s Centre for Future Intelligence and is the Executive Director of Diffusion.Au. He is a Policy Fellow with the Chifley Research Centre and a Policy Associate at the Centre for Responsible Technology Australia.

Transcript