Making Scientists Obsolete? The Impact of Artificial Intelligence on Science
Some thoughts on a recent presentation I gave about ChatGPT and LLMs
In Brief: My most recent Practically Scientific post led to a generous invitation to give a virtual talk at the University of Washington. Along with Scott Murray, I covered the advent of ChatGPT, how it confirms that we are in a new AI-driven technological era, and the deep problems still remaining in AIs such as ChatGPT. What I want to do here is go beyond these topics (which were covered in my previous post) and focus on what I learned from Scott Murray and the great discussion following the presentation.
My main surprise from the University of Washington talk was how positive and optimistic my co-presenter (Scott Murray) and the audience were about AI (artificial intelligence), ChatGPT, and related large language models (LLMs). Here are some useful things Scott pointed out we can already do with ChatGPT:
Use it as a tutor for almost any topic
Write computer code in any language (or translate) using natural language
“Clean up” writing
Write a course syllabus draft
Write a draft of a scientific abstract
Write administrative stuff – emails, mission statements, etc.
Write the content for a lab webpage; write the HTML
Write catchy tweets (or Mastodon posts!)
I acknowledged how useful ChatGPT can be. However, Scott went further, making the claim that LLMs would likely do science better than human scientists in the next 5 to 10 years. I countered that prediction with 50 years before us scientists will be out of a job, based on how difficult science is and how limited LLMs are on fundamental issues of whether a belief is true and basic causal inferences.
Despite a disagreement on timeline we both agreed that LLMs and related AIs would take over science (to the benefit of humanity, but maybe not individual scientists) at some point. That’s a big deal, as such a claim was much more “science fiction” just a few years ago. Speaking of science fiction, someone in the audience linked to this mind-bending piece of science fiction published in Nature in 2000: “Catching crumbs from the table”
Again countering negative takes on LLMs, Scott said someone he knew claimed that LLMs just do “fancy pattern matching”. I’ve heard this criticism a lot, with claims that LLMs are fundamentally different from the human brain. Certainly there are many differences, but I countered that it may be that most of what the human brain does is just fancy pattern matching. In particular, there’s evidence that the human brain (such as the language system) does predictive coding. Of course, prediction is the very approach used to train LLMs, as they are optimized to predict upcoming words based on previous words.
So, it’s possible that the simplistic approach of training models to predict what will happen next (a form of pattern completion) can get us far on 1) understanding human cognition, 2) understanding the human brain, and 3) replicating and expanding upon useful computations the human brain does. Along these links, an audience member (I think the author of this paper) shared a very interesting paper on predictive coding in the brain: “A Sensory-Motor Theory of the Neocortex based on Active Predictive Coding”
Discussion of what’s different about ChatGPT from other LLMs came up, with a brief description of how ChatGPT is a standard LLM (GPT-3) augmented by reinforcement learning feedback from humans. An audience member linked to this excellent blog post illustrating that process: https://huggingface.co/blog/rlhf
Overall, it was a great discussion with a great group of cognitive neuroscientists, psychologists, and computer scientists, and I’m grateful to Andrea Stocco for organizing the event and for inviting me.
For those interested in how I generated the art in this post (above), I used DALL-E. I first used the prompt “paint a beautiful picture of what chatgpt would look like if it were all powerful but friendly”. But it produced some not-so-great images, some of which were off topic. After a couple more tries I decided to ask ChatGPT for help.
Here is that ChatGPT chat:
That second prompt created the art at the top of this post.