Scott Douglas Jacobsen: I found an article in Mother Jones about AI becoming as powerful as human cognition by 2025 worth reading. The article is from 2013. The article was scaled up in search results somehow. Some parts of it could have been written ten years later. It uses Moore’s law from 2013 to predict that the number of calculations per second in the fastest computers will eventually be on par with the number performed by the human brain. However, since that article was written—more than a decade ago—the estimates for the brain’s computational capacity may have been updated, and we probably have more recent information now. But let’s assume the article from 2013 is correct and that the number of calculations in an AI system is roughly equivalent to those in the human brain. Though, AI does not operate like a human brain.

Rick Rosner: Current AI systems are fairly single-task oriented; they do not interact with the environment in a multifaceted way. Take a language model, for example. It develops small probability nodes around certain characteristics of language and thought by being fed vast amounts of data—much as a graphics AI probabilistically learns the laws of perspective and shading. For instance, understanding that an object closer to the observer will block what is behind it, or learning how human faces work, how many fingers we have, and how they bend). 

A language model uses a similar mechanism to learn how sentences work and how verbs and nouns function. It may not “understand” content in the human sense. Still, we probably process language probabilistically on a localized scale—predicting which word might come next based on prior exposure (for example, if I say “the best,” you might expect “brightest” because you’ve heard that phrase many times, as in “the best and the brightest”). Our thinking might also rely on localized probability models rather than full conscious processing—similar to pseudo-thinking within a language model. The conclusion has remained unchanged for the past few years: AI is powerful but ultimately limited.

Is that reasonable? 

Jacobsen: It’ll be tricky. 

Rosner: Integration will mostly be solved by the systems iterating themselves until they reach a fixed point. For example, give a graphics AI a six-word instruction. It can generate a thirty-second video—or maybe even a whole short film—that may or may not make perfect sense but will relate to the six words you provided. Imagine instructing it to “show a guy haunted by guilt, the protagonist of Crime and Punishment, with his guilt taking the form of ghosts.” That AI would produce a two‑minute video of a man haunted by spectral manifestations of guilt, perhaps even depicting the crime itself, and it would do a pretty good job. That output would be something you could look at and say, “This isn’t total crap.”

Photo by Jakob Owens on Unsplash

Rick Rosner is an accomplished television writer with credits on shows like Jimmy Kimmel Live!, Crank Yankers, and The Man Show. Over his career, he has earned multiple Writers Guild Award nominations—winning one—and an Emmy nomination. Rosner holds a broad academic background, graduating with the equivalent of eight majors. Based in Los Angeles, he continues to write and develop ideas while spending time with his wife, daughter, and two dogs.

Scott Douglas Jacobsen is the publisher of In-Sight Publishing (ISBN: 978-1-0692343) and Editor-in-Chief of In-Sight: Interviews (ISSN: 2369-6885). He writes for The Good Men Project, The Humanist, International Policy Digest (ISSN: 2332-9416), Basic Income Earth Network (UK Registered Charity 1177066), A Free Inquiry, and other media. He is a member in good standing of numerous media organizations.

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