Dennis Yi Tenen on storytelling in the age of AI

In our December xChange Paul Skinner, founder of MarketingKind, interviewed Dennis Yi Tenen to explore what the history of machine learning can tell us about the future of how AI technologies will impact storytelling and culture.

Together we discussed Dennis's book Literary Theory for Robots: How Computers Learned to Write, why he wrote it and what he has learned in the process.

He shared how the challenges that arise with AI are social problems, similar to the challenges we've seen throughout history with each technology change. And as marketers we are well places to help society to adapt in useful ways.

He argues that AI is better understood as a social or collective intelligence rather than a single entity. AI is more representative of an aggregation of human knowledge and technological capabilities rather than an independent godlike character. Dennis says that humans have been automating the writing process throughout history and AI is just the next step.

Dennis suggested it is more useful to focus on specific, actionable issues rather than abstract existential threats of AI. He says that Europe has often been better than the US at getting the balance right between regulation and innovation and we should make sure that we continue to protect information in the public domain.

When asked about the dangers of commoditising the outputs caused by the drive for efficiency in the creative process with AI, Dennis says: "Your body needs to go through the experience of exercise to derive the benefits. Let's extend this to intellectual capacities... Maybe we need to get to the mental gym".

Here is the link to the ChatGPT generated summary for the sequel to Literary Theory for Robots, which Paul mentions and Dennis comments on in the discussion.

Dennis is an associate professor of English at Columbia University, where he also co-directs the Center for Comparative Media. His research happens at the intersection of people, text, and technology. A long-time affiliate of Columbia’s Data Science Institute, formerly a Microsoft engineer in the Windows group and fellow at the Berkman Center for Internet and Society, his code runs on millions of personal computers worldwide.

You can listen to the podcast here or watch the full replay below.