# Video Of The Week: AI and Society

Earlier this week, Kara Swisher interviewed Kate Crawford and Meredith Whittaker, who run NYU’s AI Now Institute.

It is an interesting and thought provoking discussion. I don’t personally love Kate and Meredith’s answers on how society should be thinking about these issues. They feel very “20th century” to me.

But regardless of what you think about their particular take on the issues, I do think we all ought to be paying a lot of attention to AI and its impact on and role in our society. It is important.

1. kidmercury

I think AI is poorly defined and that is the source of most of the problems. Companies like Tesla that get in trouble with AI are doing so primarily because they are trying to get more out of the technology than what is safely possible (or are over promising what can be done). To me it is clear that they should this assume the liability, and should not be able to use “the computer did it” as a legal excuse. If this rationale is accepted it would solve much of the legal and moral disagreements that are surfacing around AI.AI is mostly statistics on steroids. Stats are not a problem and no one would ever say “it is not my fault, it is math’s fault” in response to a statistical error.

1. Richard

Pretty close – there are an infinite (most unknown) unknown functions that can fit the data. If the data set itself is infinite in size, you can never know with certainty they you selected the best function.

1. kidmercury

Yes, but then you shouldn’t over promise in light of what is unknown. And if you do, that error is on you.

2. sigmaalgebra

If for some positive integer n have, for i = 1, 2, …, n, pairs of real numbers (x(i),y(i)), graph them in the usual way, and want a curve to fit them consider, say, let me think a little …:Okay, assume that the x(i) are distinct. For some easier notation, for i = 1, 2, …, n, define polynomialr_i(x) = (x – x(1)) (x – x(2)) … (x – x(n))omitting factor(x – x(i))and define real numbers_i = r_i(x(i))[Here the “_i” is TeX notation for a subscript of i.]So we notice that r_i(x) is 0 at x = x(j), j = 1, 2, …, n except r_i(x) = s_i at x = x(i).That is, more intuitively r_i(x) really is a polynomial and is 0 at all the x points except x(i) and there has value s_i.Also since the x(i) are distinct, s_i is not zero — which means we can divide by it.So, polynomial r_i(x) is cute: It’s zero, makes no contribution, at all at the X axis data points except its particular one x(i).Then define polynomialq_i(x) = y(i) r_i(x) / s_iPresto, bingo, this little puppy polynomial is zero at all the X points except at x(i) is just what we want, our given y(i). We’re getting warm!!!Finally let polynomialp(x) = q_1(x) + q_2(x) + … + q_n(x)That is, we just add up the little puppy polynomials, one for each of our given points. Each little r_i(x) puppy polynomial does its job, gives value y(i) at x = x(i) and at the other points does nothing, gets out of the way, is zero.Done.I figured this out soon after I first heard about the interest in curve fitting. Then I programmed it and discovered that mostly it is a total riot, commonly between the given X axis points heads off for plus or minus infinity, turns around just in time, DOES go through the next point, and then goes wack-o again.So, it’s NOT very useful! As interpolation it’s sick-o!Later I discovered that long ago Lagrange had had the same idea, and the polynomial is known as Lagrange interpolation. Lagrange DID have a lot of better ideas!A better idea is spline interpolation. And it’s also easy enough to do least squares spline interpolation. And can do multivariate spline interpolation, useful, e.g., in the optimal value function of stochastic dynamic programming and maybe in computer aided design, e.g., getting the sheet metal over the rear wheels looking like the bottom of a woman!

2. sigmaalgebra

And nearly all the statistics is shaky. And the statistics is based on probability, and even with the best mathematical foundations of that there is at least one place where have to swallow hard.

1. Pete Griffiths

This is a little vague.

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1. Pete Griffiths

Hmm.Well I did ask.NowI have to think.

3. JamesHRH

Fuckin’ Eh Kid.It’s like Y2K.

2. Guy Lepage

The folks at IIW have been working on this… “This” being reputation for about a decade. They host a bi-annual event at Google’s Computer History Museum. I’m shocked that they have not attended the event with all of the other folks from Google, IBM, Microsoft, Mozilla, etc., etc…Reputation is damn hard and it scares me the most about AI. We need more folks focusing on building reputation systems. I personally see that as the big threat with AI.

3. sigmaalgebra

4. sigmaalgebra

1. Pete Griffiths

This is pretty crazy.

1. sigmaalgebra