Re: [Wittrs] Wittgenstein, Statistics and Judgment
- From: John Phillip DeMouy <jpdemouy@xxxxxxxxx>
- To: Wittgenstein's Aftermath <wittrs@xxxxxxxxxxxxxxxxxxx>
- Date: Fri, 27 Jan 2012 00:37:19 -0500
Regarding the general conflict between the Scientistic mindset of those
who (perhaps suffering "physics envy") embrace statistics to at least
give the impression of "objectivity" (however misplaced such ideas might
be in dealing with some subjects) and the Humanistic view of the
so-called "Social Sciences", Peter Hacker has a superb essay introducing
some of the history of debates of these sorts and how Wittgenstein
relates to them. I'd highly recommend it as the writings of an orthodox
Wittgenstein exegete on this topic.
http://info.sjc.ox.ac.uk/scr/hacker/docs/Humanistic%20understanding.pdf
On Thu, 2012-01-26 at 21:27 -0800, Sean Wilson wrote:
>
> ... I don't have time to do this now. I've got too much on my plate.
> I'd like to maybe help next week. There's no guarantee of that either.
> But it is such a good conversation that I do hope to say something
> helpful. But I do want to quickly note a couple of obvious problems
> with your view in passing:
>
> 1. It really doesn't surprise me that many number crunchers would fail
> to see how Wittgenstein could help people when their "science claims."
> There's not a subject in the world that Wittgenstein couldn't help.
> It's really doesn't benefit our field if scholars harbor such an
> attitude.
>
> 2. The comments about "what expert opinion is" and how you could
> replicate it formally is PRECISELY the kind of thing that Wittgenstein
> is concerned with in several areas of his later work. In saying things
> like "how does one select among connoisseurs," etc., -- aren't we
> really admitting that we haven't a firm grasp on
> what aesthetical judgments are to Wittgenstein, and how they fit into
> his other ideas? I wonder, have you read this stuff -- or are you just
> going off what you intuitively feel that the word "connoisseur" is
> doing in the sentence?
>
> A connoisseur is not a from-the-seat prognosticator. It's not asking
> Terry Bradshaw who will win the football game and comparing that to a
> computer model. This is the thing that is not understood. When you
> poll the law professors about who will win the case, they aren't
> giving you a "connoisseur judgment," at least not in a Wittgensteinian
> sense. If any student would have written that in a paper, it would be
> near the F range.
>
> To have a connoisseur, you must first have a specific behavior that
> becomes celebrated in the culture. There's a learning curve with the
> appreciation of the behavior. Only after the person goes through the
> learning curve (training) does he or she come to fully understand its
> context. The connoisseurs are what keep the context properly
> appreciated. So if the behavior is predicting how a judge would vote,
> I suppose the only true connoisseurs of that activity would be the
> judge's wife (spouse). And there would have to be a learned
> appreciation for this specific behavior.
>
> Try to relate this to Wittgenstein's views on aspect seeing and
> imponderable evidence. The connoisseur understands the behavior the
> way that the mother can understand a child just by looking at the
> eyes. The connoisseur doesn't use or need "statistics" because he or
> she already has superior information. He or she has developed the
> ability to "aspect-see." The rest of us, of course, have no choice but
> to rely on whatever information we can. We're are neither the judge's
> spouse nor the child's parent. The difficulty comes when some of us
> throw away the stats to make our own hunches. The question of whether
> this is good or bad is ultimately a function of how good the
> information is versus how insightful the person might be at "seeing
> something." I threw away a linear regression about approval ratings
> because I didn't think its picture of account more helpful than the
> one I had formed by watching and studying presidential elections. The
> fallacy here is to
> say that I threw away "science" for something inferior. Surely I did
> not.
>
> Note also that if the behavior in question is what constitutes good
> legal casuistry, there are connoisseurs here -- Ronald Dworkin
> probably being the best. Legal judging is clearly an "aesthetic" in a
> Wittgensteinian sense, as my book will shortly show. We must be
> careful about one thing: not all supposed connoisseurs are good at
> their craft. Just as you can get a bad haircut or a bad tailor, so too
> can you get a bad judge or philosophy-of-law scholar. (Or a bad parent
> or poor spouse). It's not enough that a person be in the position of
> connoisseur; to do the job right, they must be good at it.
>
> So, if you ever do build a true connoisseur simulator (with AI), it
> would have absolutely nothing to do with the fact
> that connoisseur judgment plays the role that it does in our life.
> Wittgenstein isn't against you building anything. He's mostly
> concerned that, when you make claims, you aren't confused.
>
> I've got to go to bed and I can't do any more of this for a while.
> Let's talk about it next month. It would really be a good panel!
>
> (P.S. Sent to Wittrs -- careful when hitting reply all)
>
> Regards and thanks.
>
> Dr. Sean Wilson, Esq.
> [spoiler]Assistant Professor
> Wright State University
> Personal Website: http://seanwilson.org
> SSRN
> papers: http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=596860
> Wittgenstein
> Discussion: http://seanwilson.org/wittgenstein.discussion.html[/spoiler]
>
> ________________________________
> From: Daniel Katz <katzd@xxxxxxxxxxx>
> To: LAWCOURT-L@xxxxxxxxxxxxxxxxxxx
> Sent: Thursday, January 26, 2012 2:26 PM
> Subject: Re: On Prediction ...
>
> My prior thoughts were aimed at trying to put to this list an honest
> discussion point as to where we believe the next major advance in
> going to come in judicial politics.
>
> Turns out that Wittgenstein is really NOT likely to be the answer to
> this question.
>
> For example, how does one select among connoisseurs, etc. What is
> the
> switching rule to decide whether it is time to now longer believe a
> connoisseur, etc. The challenge has been put forth before and I will
> put it forth again
> ---
>
> Can you leverage any insight from Wittgenstein to develop a model
> (qualitative, quantitative, etc. ) that can outperform EITHER crowd
> sourced AND/OR the best algorithmic approach available.
>
> If you can, than Wittgenstein has something to contribute to this
> conversation. Indeed, if Team Wittgenstein would like to enter the
> tourney - I am sure that Josh Blackman over at FantasySCOTUS would
> be
> happy to take your entry: http://www.fantasyscotus.net/
>
> Returning now the thrust of my thoughts:
> Crowd sourced prediction offers lots of potential with the caveat that
> we need some second order rule that looks to the specific contours of
> the information environment, etc. In other words, crowds can be
> stupid (particularly at pricing rare events.)
>
> I just want to say that I really do believe that expert opinion is a
> very interesting topic ... IF we are going actually analyze the
> specific data streams and weighting scheme over data that allows them
> to succeed than we have something to add to a much broader
> conversation. Indeed, that is what has been happening in many other
> fields during the new "Soft AI Revolution."
>
> On the flip side, there are a number of lab groups across the academy
> that have been working for several years at developing / testing a
> variety of different prediction algorithms including but not limited
> to the classification trees, neural networks, etc. (Note the class
> of techniques are a little bit "up market" from sort of simple linear
> regression model).
>
> Best,
> Dan
>
> >>> "Peppers, Todd" <peppers@xxxxxxxxxxx> 01/26/12 1:42 PM >>>
> Folks:
>
> I truly enjoy this listserv, and find most of the postings to be truly
> informative, but I cannot stomach another discussion/debate about ole
> Ludwig Wittgenstein. Could we perhaps hold the discussion about
> "connoisseur judgment" off-line?
>
> Respectfully,
>
> Todd Peppers
>
> Dr. Todd C. Peppers
> Henry H. & Trudye H. Fowler Chair
> Associate Professor
> Public Affairs
> P: 540-375-2417
> F: 540-375-2405
> peppers@xxxxxxxxxxx
>
> -----Original Message-----
> From: Sean Wilson [mailto:whoooo26505@xxxxxxxxx]
> Sent: Thursday, January 26, 2012 1:34 PM
> To: LAWCOURT-L@xxxxxxxxxxxxxxxxxxx
> Subject: Wittgenstein, Judgment & Statistics
>
> Greetings Jeff.
>
> First, thank you for those references. It will take me a few days to
> digest them. I'm trying to finish up my book, for good, because I have
> manuscript submission deadlines approaching. But I would enjoy a
> discussion in here about Wittgenstein's idea of "connoisseur judgment"
> and how it compares with those who base judgment purely upon
> statistical inference -- and what, in fact, that even means. My guess
> is that each camp has information deficits relative to one another. It
> would be a cutting edge discussion: one that could deserve its own
> conference panel. Let me digest these sources of yours and offer some
> thoughts about how a proper understanding of connoisseur judgment
> could help these conversations, if it can.
>
> I'll try to get some thoughts together by next week.
>
> But thank you once again for the references.
>
> (P.S. Sent to Wittrs)
>
> Regards and thanks.
>
> Dr. Sean Wilson, Esq.
> Assistant Professor
> Wright State University
> Personal Website: http://seanwilson.org
> SSRN papers:
> http://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=596860
> Wittgenstein Discussion:
> http://seanwilson.org/wittgenstein.discussion.html
>
> ________________________________
> From: Jeffrey Segal <jeffrey.segal@xxxxxxxxxxxxxx>
> To: LAWCOURT-L@xxxxxxxxxxxxxxxxxxx
> Sent: Thursday, January 26, 2012 8:46 AM
> Subject: polls and elections
>
> Sean Wilson wrote yesterday that he prefers "connoisseur judgments"
> over linear regression models. Unfortunately for Sean's argument, a
> substantial volume of literature shows that quantitative assessments
> clearly outperform qualitative judgments. See most notably, Philip
> Tetlock's "Expert Political Judgment: How Good is it? How Can we
> Know?" demonstrating across the board that simple algorithms
> outperform expert judgments and Daniel Kahneman's "Thinking, Fast and
> Slow" on the same point.
>
> Closer to home, Robyn Dawes demonstrates that even improper linear
> models outperform qualitative faculty judgments on prospective
> graduate students (Dawes, Robyn M. "The robust beauty of improper
> linear models in decision making, 34 American Psychologist 571 (1979)
> (showing that even improperly (i.e., evenly) weighted linear models
> outperform expert judgments of an admissions committee over the
> eventual quality of graduate students), and really close to home,
> Andrew Martin's computer out-predicted law professors in the law
> professors' areas of expertise in a series of Supreme Court
> decisions. Andrew D. Martin, Kevin M. Quinn, Pauline T. Kim, and
> Theodore W. Ruger. 2004. "Competing Approaches to Predicting Supreme
> Court Decisionmaking."2 Perspectives on Politics761.
> On the merits of Sean's point, my Stony Brook colleague Helmut Norpoth
> has a linear prediction model based on the New Hampshire primary
> showing that incumbents with challengers lose--Truman '52 (who dropped
> out after a weak New Hampshire showing), Johnson '68 (ditto), Ford
> '76, Carter '80, and Bush '92)-- whereas incumbents without strong
> primary challengers win (Ike 56, LBJ 64, RMN 72, RWR 84, GWB 04, and a
> prediction for BHO in 12). See
> http://www.huffingtonpost.com/helmut-norpoth/new-hampshire-primary-for_b_1200199.html
>
> Sincerely,
>
> Jeff
>
> Jeffrey Segal
> Distinguished Professor and Chair
> Department of Political Science
> Stony Brook University
> Stony Brook, NY 11794
> phone 631-632-7662
> fax 631-632-4116
> jeffrey.segal@xxxxxxxxxxxxxx
> http://www.sunysb.edu/polsci/jsegal/
>
> 2011-2012 Contact Information
> Senior Visiting Research Scholar
> Center for the Study of Democratic Politics
> 314 Robertson Hall
> Princeton University 08544
> phone 609-258-7941
>
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