Dean's Scholars Seminar
Do Scientists Have Crystal Balls?

Elaine Rich

What happens when accomplished scientists attempt to predict the future of their science? Are they more likely to be right than a typical science fiction author? If they make mistakes, is there a systematic bias:

  1. Are scientists more likely to predict faster or slower progress than actually occurs?
  2. When scientists have been overly optimistic, why did their predictions fail to come true? We can divide the scientists' predictions into two categories: Are scientists any good at answering question 1? Are they any good at answering question 2? Do they even try on question 2?

    We can look at these issues in the context of almost any scientific discipline. I propose that we start with artificial intelligence (AI), although we should look at other areas as well.

    AI is an interesting domain to consider for several reasons. People have been fantasizing about building machines with human-like capabilities for hundreds of years. Now we're close enough to being able to do it that it's tempting to make serious and very optimistic predictions about what we'll be able to do and when. In the seminar, we'll look at many different predictions spread out over the last 100 or more years. Most of the ones we'll look at were written by scientists, i.e., by the people who ought to know. We'll look at what artificial intelligence actually can do and see how good the scientists' crystal balls are. We'll also consider some other less scientific forecasts and see how they compare. Remember Hal?

    We'll find predictions about the future of AI all over the map. The most interesting (although not necessarily the most accurate) ones of course are at the fringes -- both fringes. So we'll see people saying:

    We'll have to look at these two very different kinds of predictions ("it will happen" vs. "it can never happen on principle") somewhat differently. The "it will happen" predictions may fail either because some insurmountable hurdle is reached or because things just take longer than was originally thought. The "it can never happen on principle" predictions may fail if the principles were wrong and the impossible turns out to be possible after all.

    On reserve in the PCL is a collection of books that focus on attempts to predict the evolution of various technologies, with an emphasis on AI. To see a list of the books that are on reserve visit the reserve list site and select our class.

    If you're going to read just two books for this class, I recommend:

    The Big Picture: Prediciting the Future of Science and Technology

    Focus: on Artificial Intelligence