Just to bring it back to R, I want to point out that what many R programmers do
is not that different. If you develop some skills at analyzing some kinds of
data and have a sort of toolchest based on past work, then a new project along
similar lines may move very quickly. After a while, you may put out a package
that allows even novices to do a decent job as the code handles so many of the
details or provides default options you can over-ride.
So if an AI has the ability to use the same tools you provided, and applies
them properly, is there much difference?
I have seen EXPERTS do horribly when yanked just outside their field of
expertise. They may use a tool outside the bounds it was designed for, as an
example, or pick an unfamiliar model that is not applicable or optimal.
The problem with AI is compounded as some kinds of peer feedback may be missing
while other things have not yet been programmed well that allow some
selectivity and so on.
But if a simple regression often works well enough, why can't an AI use it too?
I will say a lot of what people do in R is cleaning the data and getting it
into the right form. Sometimes humans struggle to detect if say two names are
the same and someone made a spelling mistake. And humans will still get things
like that wrong unless they can go back and consult external resources to see
if say the school has two teachers with similar names or whether all the
students named should be combined under the same teacher for some purposes.
I will point out there is no good reason to think an Ai would necessarily use R
or use base R rather than some of the functions in the tidyverse. I am studying
Wolfram and an amazing amount of work can be done in one liners that rely on
many thousands of built-in functionality. So why would you want an AI to write
assembly code or do it in a language like C but rather pick a language well
suited for whatever task.
-----Original Message-----
From: R-help <r-help-boun...@r-project.org> On Behalf Of Spencer Graves
Sent: Monday, July 17, 2023 3:13 PM
To: Bert Gunter <bgunter.4...@gmail.com>; R-help <R-help@r-project.org>
Subject: Re: [R] Off-topic: ChatGPT Code Interpreter
I don't know about ChatGPT, but Daniel Kahneman won the 2002 Nobel
Memorial Prize in Economics,[1] even though he's not an economist, for
his leadership in creating a new subfield in the intersection of human
psychology and economics now called "behavioral economics".[2] Then in
2009 Kahneman and Gary Klein published an article on, "Conditions for
intuitive expertise: a failure to disagree", which concluded that expert
intuition is learned from frequent, rapid, high-quality feedback.
People you do not learn from frequent, rapid, high-quality feedback can
be beaten by simple heuristics developed by intelligent lay people.[3]
That includes most professions, which Kahneman Sibony and Sunstein call
"respect-experts".
Kahneman Sibony and Sunstein further report that with a little data,
a regression model can outperform a simple heuristic, and with massive
amounts of data, artificial intelligence can outperform regression
models.[4]
An extreme but real example of current reality was describe in an
article on "Asylum roulette": With asylum judges in the same
jurisdiction with cases assigned at random, one judge approved 5 percent
of cases while another approved 88 percent.[5] However, virtually all
"respect-experts" are influenced in their judgements by time of day and
whether their favorite sports team won or lost the previous day. That
level of noise can be reduced dramatically by use of appropriate
artificial intelligence.
Comments?
Spencer Graves
[1]
https://en.wikipedia.org/wiki/Daniel_Kahneman
[2]
https://en.wikipedia.org/wiki/Behavioral_economics
[3]
https://www.researchgate.net/publication/26798603_Conditions_for_Intuitive_Expertise_A_Failure_to_Disagree
[4]
Daniel Kahneman; Olivier Sibony; Cass Sunstein (2021). Noise: A Flaw in
Human Judgment (Little, Brown and Company).
[5]
https://en.wikipedia.org/wiki/Refugee_roulette
On 7/17/23 1:46 PM, Bert Gunter wrote:
> This is an **off-topic** post about the subject line, that I thought
> might be of interest to the R Community. I hope this does not offend
> anyone.
>
> The widely known ChatGPT software now offers what is called a "Code
> Interpreter," that, among other things, purports to do "data
> analysis." (Search for articles with details.) One quote, from the
> (online) NY Times, is:
>
> "Arvind Narayanan, a professor of computer science at Princeton
> University, cautioned that people should not become overly reliant on
> code interpreter for data analysis as A.I. still produces inaccurate
> results and misinformation.
>
> 'Appropriate data analysis requires just a lot of critical thinking
> about the data,” he said.' "
>
> Amen. ... Maybe.
>
> (As this is off-topic, if you wish to reply to me, probably better to
> do so privately).
>
> Cheers to all,
> Bert
>
> ______________________________________________
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> and provide commented, minimal, self-contained, reproducible code.
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