Stephen Wolfram Q&A

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Some collected questions and answers by Stephen Wolfram

Questions may be edited for brevity; see links for full questions.

April 26, 2013

From: Interview by Patrick Tucker, IEET

Given the future of digitized knowledge, the exponential growth in structured and unstructured data that we can look forward to over the coming decades, is it possible that the space of irreducible knowledge, of unpredictable knowledge—while it will still always exist—is shrinking? Would this mean that the space of predictable knowledge is in fact growing?

Interesting question. Once we know enough, will we just be able to predict everything? In Wolfram|Alpha, for example, we know how to compute lots of things that you might have imagined weren’t predictable. You have a tree in your backyard. It’s such and such a size right now. How big will it be in 10 years? It’s now more or less predictable.

As we accumulate more data, there will certainly be patterns that can be seen, and things that one can readily see that are predictable. You can expect to have a dashboard—with certain constraints—showing how things are likely to evolve for you. You then get to make decisions: Should I do this? Should I do that?

But some part of the world is never going to be predictable. It just has this kind of computational irreducibility. We just have to watch it unfold, so to speak. There’s no way we can outrun it. I suspect that, in lots of practical situations, things will become a lot more predictable. That’s a big part of what we’re trying to address with Wolfram|Alpha. Take the corpus of knowledge that our civilization has accumulated and set it up so that you can automatically make use of it.

There are three reasons why one can’t predict the things that can’t be predicted. The first reason is not enough underlying data. The second is computational irreducibility—it’s just hard to predict. The third is simply not knowing enough to be able to predict something. You, as an individual, don’t happen to know enough about that particular area to be able to do it. I’m trying to solve that problem.

We’re seeing a transition happening right now, and more and more things can be figured out in an automatic way. We’re seeing computation that is finally impinging on our lives in a very direct way. There are lots of things that used to be up to us to estimate, but now they’re just being computed for us: a camera that auto focuses, for example, or that picks out faces and figures what to do, or automatically clicks the shutter when it sees a smile—those kinds of things. Those are all very human judgment activities, and now they’re automated.

I think this is the trend of technology. It’s the one thing, I suppose, in human history that has actually had a progression: There’s more technology; there are more layers of automation about what we do.

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