[FRIAM] How soon until AI takes over polling?

[Russell Standish]

Given that most human explanations are post-hoc rationalisations, I
expect that machine learning systems trained to explain the outputs of
other systems might work. I believe some people in the ML community
are trying this, but it is not all that common yet. It is hard enough
to get the black-box predictive models to work as it is.

On Wed, Nov 11, 2020 at 11:05:30AM -0500, David Eric Smith wrote:
> 
> 
>     On Nov 11, 2020, at 8:54 AM, Frank Wimberly <wimberly3 at gmail.com> wrote:
> 
>     Don't some AI systems include subsystems for explaining their reasoning?
> 
> 
> I don’t know how common that is, Frank.  The few people I know who are active
> and skilled deep-learning practitioners have told me (if I have understood)
> that it is rare and limited.  I spent some time looking at the zero-shot
> language translation, as something I wanted to convene at SFI, with the AI goal
> of unpacking what was the “universal language” internal representation, and
> with the linguistics goal of using it in cognate classification and historical
> reconstruction.  Never could get a call-back from any of the google people.
>  But I didn’t think at the time that zero-shot had been unpacked.
> 
> Probably some on this list know much more about the state of play.
> 
> Eric
> 
> 
> 
>     Happy Veterans Day,
> 
>     Frank
> 
>     ---
>     Frank C. Wimberly
>     140 Calle Ojo Feliz,
>     Santa Fe, NM 87505
> 
>     505 670-9918
>     Santa Fe, NM
> 
>     On Wed, Nov 11, 2020, 3:25 AM David Eric Smith <desmith at santafe.edu> wrote:
> 
>         Friam poll:
> 
>         How soon until classical telephone polling is just gone?
>         https://www.nytimes.com/2020/11/10/upshot/polls-what-went-wrong.html
> 
>         If, as boasted, facebook knows when their users are pregnant before the
>         users know, they know who someone supports and whether that person is
>         likely to vote.  
> 
>         At this stage, trying to get accurate statistics from cold calls on the
>         phone seems as quixotic as trying to infer something from the people
>         who read books.  But if there’s anything we can count on, it is that
>         the number of people who don’t leave an internet fingerprint is too
>         small to have any political impact at all.
> 
>         How much effort they put into getting reliable calibrations will depend
>         on what ways they see to monetize it, but the diversity of cash-outs
>         should be nearly inexhaustible, for years to come.
> 
>         So one more thing goes into what is both a black box and a private
>         rather than public box.  It will take over after the first few times it
>         produces much more reliable results, but since we won’t know what it is
>         based on — AIs don’t explain themselves — we will have no ability to
>         extrapolate out of sample.
> 
>         Eric
> 
> 
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Dr Russell Standish                    Phone 0425 253119 (mobile)
Principal, High Performance Coders     hpcoder at hpcoders.com.au
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