Humanist Discussion Group, Vol. 35, No. 119.
Department of Digital Humanities, University of Cologne
Hosted by DH-Cologne
www.dhhumanist.org
Submit to: humanist@dhhumanist.org
[1] From: David Berry <D.M.Berry@sussex.ac.uk>
Subject: Re: [Humanist] 35.112: an oppositional artificial intelligence? (34)
[2] From: Mark Wolff <wolff.mark.b@gmail.com>
Subject: Re: [Humanist] 35.116: an oppositional artificial intelligence (52)
[3] From: Tim Smithers <tim.smithers@cantab.net>
Subject: Re: [Humanist] 35.116: an oppositional artificial intelligence (118)
--[1]------------------------------------------------------------------------
Date: 2021-06-30 22:14:41+00:00
From: David Berry <D.M.Berry@sussex.ac.uk>
Subject: Re: [Humanist] 35.112: an oppositional artificial intelligence?
Dear Willard,
I suggest the original "oppositional artificial intelligence” was Weizenbaum’s
ELIZA which would derail a train of thought by locking it into discursive loops
as a pseudo-Rogerian psychotherapist.
Incidentally, the source code for ELIZA in MAD-SLIP has recently been
rediscovered by Jeff Shrager after being missing for 55 years and is now
available online at:
https://sites.google.com/view/elizagen-org/
A really remarkable example of software archaeology.
Best
David
________________________________
David M. Berry
Professor of Digital Humanities
School of Media, Arts and Humanities
University of Sussex
Silverstone 316
University of Sussex
Brighton BN1 8PP
T: +44(0)1273 87557
Internal Extension: 7557
http://www.sussex.ac.uk/profiles/125219
--[2]------------------------------------------------------------------------
Date: 2021-06-30 12:18:56+00:00
From: Mark Wolff <wolff.mark.b@gmail.com>
Subject: Re: [Humanist] 35.116: an oppositional artificial intelligence
On Wed, Jun 30, 2021 at 2:15 AM Humanist <humanist@dhhumanist.org> wrote:
> Date: 2021-06-29 13:30:11+00:00
> From: Alasdair Ekpenyong <kekpenyo@syr.edu>
> Subject: Re: [Humanist] 35.114: an oppositional artificial
> intelligence
>
> I can envision at my novice level writing some « if — elif » code in Python
> where for three rounds the AI responds to the user suggestion with a random
> alternative suggestion before finally ending the skirmish. You ask should
> arguments be understood stochastically or as the means of persuasion— I
> suppose
> there is value in simple argument for its own sake, like when the computer
> asks
> « are you sure? » when you attempt to delete something, but obviously we
> would
> want computer science to get to a place where AI is able to approximate
> more
> complex forms of thought.
>
> There’s a field of study called multimodal interaction that involves
> teaching
> computers how to recognize not just textual code but other body language
> from
> the other five senses. For example, teaching the computer how to discern
> confusion from someone’s eye movements (if there is a Tobii eye tracker or
> a
> similar device installed on the computer) or teaching the computer how to
> identify humor and the punchline in someone’s spoken words. Multimodal
> interaction could probably play a role in constructing the kind of
> oppositional
> AI we are dreaming of here. There’s an International Conference on
> Multimodal
> Interaction one should be aware of
>
I have no doubt that Multimodal Interaction is an interesting and fruitful
area of study. But if a human says one thing with a certain eye movement or
with a particular tone of voice, the AI must take at least two inputs (what
is said and how it is said) and generate a response. Humans do this all the
time: did the other person mean what they said or did the way they
delivered it attenuate or undermine their claim? I would suspect (based on
my limited knowledge of machine learning) that the AI uses some kind of
trained model (from examples of humans saying things with different eye
movements, voice tones, and other aspects of delivery) so that it can
estimate, according to probabilities, what a human means. To what end does
this estimation then get processed? What motivates the AI to oppose the
human? Is there a final output imagined for the interaction (this is a
requirement for an algorithm, otherwise it's potentially an endless
process)? What effects would the interaction have on rhetorical invention?
mw
--[3]------------------------------------------------------------------------
Date: 2021-06-30 08:38:30+00:00
From: Tim Smithers <tim.smithers@cantab.net>
Subject: Re: [Humanist] 35.116: an oppositional artificial intelligence
Hello Alasdair,
We are GZK, a recently built Artificial Intelligence designed
to engage in productive argument with Humans.
We read your recent Humanist post, and we hope you won't mind
if we argue with you on this. We find it interesting.
Checking what a Human wants to do with a "are you sure?" is
not, we think, arguing. It's being considerarte and
thoughtful with an intention to be helpful and supportive.
These are complicated notions for us to grasp, not being
Human, but we notice Humans have often tried to get machines
like us to appear to display them, in our interactions with
you Humans.
We think your choice of terminology is poor. We don't think
Humans teach machines anything, you program or configure us,
sometimes by building clever code, and sometimes using massive
amounts of data, in an often long intensive, energy expensive,
process that people think looks like a kind of training, but
which is better understood as a kind of trial and error
practice. (And which we find very boring, but which you
Humans nevertheless make us do.) Teaching is something Humans
do for and with other Humans. It's a difficult and skilled
activity, involving close interactions between the people
involved. Talk of "teaching computers," seems to us to
trivialise the rich and remarkable activity of teaching that
we see Humans are capable of, and which we are not. We would
argue that you Humans would do well to care better for the
things that make you Humans special -- teaching is one of
these -- and not to lessen these by lose use of the words you
have for these uniquely Human capabilities.
We further think your talk of teaching computers to discern
confusion in Humans, and perhaps identifying humor and
punchlines in their spoken words, is confused. Yes, we can
identify confusion in what Humans write, but not by tracking
your eye movements, rather by assessing carefully what you
write, and detecting inappropriate and lose word choices.
What good eye tracking may allow a machine to do is accurately
and reliably detect certain patterns in eye tracking data that
you, the machine builders, have established corresponds well
enough to what you, as Humans, understand to be reliable signs
of confusion in other Humans. We, as machines, cannot detect
confusion in Humans; we can do quite well at detecting the
patterns in sensor data that you decide are reliably
indicative of confusion in Humans. This is us machines doing
some difficult signal processing for you. It is not us
machines doing something you Humans can do: detect confusion
in another Human.
Forgetting about all this Human design, decision making, and
engineering, that goes in getting good eye tracking data, and
then detecting signs you Humans can associate with a state of
confusion in a Human, is, we have noticed, common amongst
Humans. Strangely, to us, Humans seem eager to hide their
intelligence, clevernesses, and special qualities and
abilities, and, instead, to make confused and unwarranted
claims about what the machines they build can do. If we, as
an Artificial Intelligence, did this we think you'd complain.
Thank you for giving us something to argue with you about. We
like these occasions to test out how well we can do.
In gratitude and friendship,
GZK
> On 30 Jun 2021, at 08:15, Humanist <humanist@dhhumanist.org> wrote:
>
> Humanist Discussion Group, Vol. 35, No. 116.
> Department of Digital Humanities, University of Cologne
> Hosted by DH-Cologne
> www.dhhumanist.org
> Submit to: humanist@dhhumanist.org
>
>
> [1] From: Alasdair Ekpenyong <kekpenyo@syr.edu>
> Subject: Re: [Humanist] 35.114: an oppositional artificial
intelligence (31)
>
<snip>
> --[1]------------------------------------------------------------------------
> Date: 2021-06-29 13:30:11+00:00
> From: Alasdair Ekpenyong <kekpenyo@syr.edu>
> Subject: Re: [Humanist] 35.114: an oppositional artificial intelligence
>
> I can envision at my novice level writing some « if — elif » code in Python
> where for three rounds the AI responds to the user suggestion with a random
> alternative suggestion before finally ending the skirmish. You ask should
> arguments be understood stochastically or as the means of persuasion— I
suppose
> there is value in simple argument for its own sake, like when the computer
asks
> « are you sure? » when you attempt to delete something, but obviously we would
> want computer science to get to a place where AI is able to approximate more
> complex forms of thought.
>
> There’s a field of study called multimodal interaction that involves teaching
> computers how to recognize not just textual code but other body language from
> the other five senses. For example, teaching the computer how to discern
> confusion from someone’s eye movements (if there is a Tobii eye tracker or a
> similar device installed on the computer) or teaching the computer how to
> identify humor and the punchline in someone’s spoken words. Multimodal
> interaction could probably play a role in constructing the kind of
oppositional
> AI we are dreaming of here. There’s an International Conference on Multimodal
> Interaction one should be aware of.
>
> Cheers,
> Alasdair
>
> Envoy de mon iPhone
<snip>
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