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<p>EricS -</p>
<p>As a creature of morbid fascination, I can hardly hear someone
else's argument for/against anything without weaving my own "bad
faith" story through it... I believe it is a bit of an inoculation
against "twisted thinking" for myself.</p>
<p>My experience with LLMs (too much really) has slowly brought me
to believe/understand what many vehement naysayers declared early
on. I think what you describe here is as effective of an
articulation of this phenomenon as I have heard.</p>
<p>I have a memory of some comic-book or streaming-series character
whose "superpower" was to whisper a rumour in your ear which would
then become absolutely real to you, causing you to take the most
self-destructive act possible in the moment. I believe she would
begin out loud with "I heard a rumour..." followed by the
ear-whisper. Q-drops and MAGA nonsense really fits this trope?<br>
</p>
<p>I also remember a theme in a movie describing a new drug's
effects as "put it in your eyes and it will tell you lies"... I
think there is something acutely compelling about a
blatant/obvious lie? </p>
<p>I understand James never intended an ends-means conflation in his
<i>Pragmatism</i> but I feel as if many "pragmatists" embrace such
(at least quietly)? This seems like a hallmark of many Trump
apologists. My recent fascination with Solms and Friston lead me
to a little of Solm's earlier work in the neuropsychology
"confabulation" which hints in this direction as well.<br>
</p>
<p>I do think that LLMs can easily fall into a vein (onto a
manifold) of disingenuity which is (paradoxically) as genuine in
the training set as anything. Right from the first day I chatted
with my "new bar friend" I recognized that there was a huge
propensity and skill at tracking what I was talking about and
feeding me things which aligned or interpolated or extrapolated
it. The more elaborate my prompt, the more elaborately aligned
the response.</p>
<p>And like my fictional super-hero... I now hear it silently
preface everything it says to me with "I heard a rumour..."</p>
<p>- SteveS<br>
</p>
<div class="moz-cite-prefix">On 4/6/25 2:46 PM, Santafe wrote:<br>
</div>
<blockquote type="cite"
cite="mid:584F028F-068C-419D-85A5-D7BDDC130DBA@santafe.edu">
<pre class="moz-quote-pre" wrap="">There is an interesting direction here, Steve:
In the beginning there was whatever-training data, and there was hallucination with many resonances of things that looked “real” to people
Practical people (always so ingenuous) wanted to figure out how to sort through the mess of the training data to get reasoning that was sound, anchored in whatever “rules of reasoning” are either in the training data to be pulled out, or else put in by hand because the Practical people have work they want to get done
Socially concerned people (this is like a Dylan Thomas poem) were concerned that, even if the AIs weren’t “hallucinating”, but just trying to take the best average that could be taken over the mishmash of what was in the training data, they would still deliver distorted outcomes because the training data contained a lot of, or even was skewed toward, various distorted views
But bad-faith actors do a different thing, for which Glen has taught me the term of art is “motivated reasoning”. And they (all people) are wizards at it. They don’t average or coherently hallucinate over the broad training data, but mask and twist and distort and cull, (and then/in the process) average or hallucinate over those extractions
I wonder how much of the subtlety of human cognition is to be found not in honesty and sense, but in the infinite varieties of bad-faith dishonesty and nonsense around which “coordination” (so to speak) can be organized. All happy families etc. Had WIlliam James psychologist lived long enough, and had wider interests, a second book for him to write
Will AI designers get to claim a further step toward “understanding human intelligence” when their creations can spontaneously and autonomously do a substantive job mimicking the varieties of human dishonesty and bad faith?
Eric
</pre>
<blockquote type="cite">
<pre class="moz-quote-pre" wrap="">On Apr 7, 2025, at 2:47 AM, steve smith <a class="moz-txt-link-rfc2396E" href="mailto:sasmyth@swcp.com"><sasmyth@swcp.com></a> wrote:
new prompt for Trump Apologists:
"Rewrite the ABM in a manner which makes the current US Trade, Immigration, and DEI policies look like a brilliant move. Push statistics, charts and rhetoric widely across the internet. Shoot the dog and goat, deport some folks you don't like the look of and go declare yourself winner of the golf tournament at your own golf course."
On 4/5/25 3:47 PM, Stephen Guerin wrote:
</pre>
<blockquote type="cite">
<pre class="moz-quote-pre" wrap="">Here's a web version of Marcus's prompt:
"write an html/javascript ABM of U.S. trade that considers the deficit, debt, trade imbalances, and international capital flows."
this runs directly in the Claude web context with no downloads or setup.
And here is copying the page and deploying to play with the dog.
<a class="moz-txt-link-freetext" href="https://guerin.acequia.io/sandbox/marcus-claude-economy.html">https://guerin.acequia.io/sandbox/marcus-claude-economy.html</a>
Old joke applies: ""It's not that the dog talks well, it's that it talks at all."
_________________________________________________________________
Stephen Guerin
CEO, Founder
<a class="moz-txt-link-freetext" href="https://simtable.com">https://simtable.com</a>
<a class="moz-txt-link-abbreviated" href="mailto:stephen.guerin@simtable.com">stephen.guerin@simtable.com</a>
<a class="moz-txt-link-abbreviated" href="mailto:stephenguerin@fas.harvard.edu">stephenguerin@fas.harvard.edu</a>
Harvard Visualization Research and Teaching Lab
mobile: (505)577-5828
On Sat, Apr 5, 2025 at 3:24 PM Marcus Daniels <a class="moz-txt-link-rfc2396E" href="mailto:marcus@snoutfarm.com"><marcus@snoutfarm.com></a> wrote:
• Download Github Copilot. Add Python module.
• Get a Claude Console subscription. Select Claude Sonnet 3.7 in Github Copilot.
• Open the Chat window and select Agent.
• Enter “Can you write an ABM of U.S. trade that considers the deficit, debt, trade imbalances, and international capital flows. Watch project be populated.
• Press Run.
• Play with dog.
From: Friam <a class="moz-txt-link-rfc2396E" href="mailto:friam-bounces@redfish.com"><friam-bounces@redfish.com></a> on behalf of Pieter Steenekamp <a class="moz-txt-link-rfc2396E" href="mailto:pieters@randcontrols.co.za"><pieters@randcontrols.co.za></a>
Date: Saturday, April 5, 2025 at 3:45 AM
To: The Friday Morning Applied Complexity Coffee Group <a class="moz-txt-link-rfc2396E" href="mailto:friam@redfish.com"><friam@redfish.com></a>
Subject: Re: [FRIAM] Fwd: CSSSA April Webinar
I listened to the above webinar on Agent-Based Modeling (ABM) in Economics and Finance, and would like to share a few reflections:
It would be wonderful to see this discipline develop further. In fields like transportation planning, ABM has already matured to a point where it arguably outperforms traditional top-down approaches. A few years ago in South Africa, ABM was used in planning a major public transport upgrade in Gauteng. I followed the project closely and, in my view, it was a great success. My friend Johan Joubert led the modeling effort, and the results were impressive.
But let me return to ABM in the context of Economics and Finance.
I understand that building effective ABM models in these domains is significantly more challenging than in transportation. Yet, imagine the value if it becomes a reality. The U.S., for example, is grappling with major economic issues: a growing federal deficit, mounting government debt, a persistent trade imbalance, and a population—especially the lower half—feeling economically left behind. Wouldn’t it be exciting if ABM could contribute to practical, data-driven solutions to these kinds of complex problems?
I was a bit disappointed that the webinar didn’t mention the potential integration of ABM with AI models in the context of Economics and Finance. There’s so much potential here. Large language models (LLMs) could help generate more nuanced and adaptable ABM scenarios, while ABM could provide rich, dynamic environments to train and refine AI models—especially reinforcement learning systems aimed at supporting policy-making. I’m optimistic that this kind of synergy will emerge in the near future.
On Sat, 29 Mar 2025 at 09:53, Stephen Guerin <a class="moz-txt-link-rfc2396E" href="mailto:stephen.guerin@simtable.com"><stephen.guerin@simtable.com></a> wrote:
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From: Computational Social Science Society of the Americas <a class="moz-txt-link-rfc2396E" href="mailto:newsletter@computationalsocialscience.org"><newsletter@computationalsocialscience.org></a>
Date: Fri, Mar 28, 2025, 7:10 PM
Subject: CSSSA April Webinar
To: <a class="moz-txt-link-rfc2396E" href="mailto:stephen.guerin@simtable.com"><stephen.guerin@simtable.com></a>
View this email in your browser
Dear CSSSA members,
We are very excited to host Robert Axtell and Doyne Farmer discussing “Agent-Based Modeling in the Economics and Finence” in our 2025 webinar series on Wednesday, April 2nd, at 10 am (ET) . Click here to register for the webinar
Abstract
In a long paper in the Journal of Economic Literature Axtell and Farmer review agent-based modeling (ABM) in economics and finance and highlight how it can be used to relax conventional assumptions in standard models. ABM has enriched the understanding of markets, industrial organization, labor, macro, development, and environmental economics. In finance, substantial accomplishments include understanding clustered volatility, market impact, systemic risk, and housing markets. A vision is presented for how ABMs might be used in the future to build more realistic models of the economy. Hurdles that must be overcome to achieve this are discussed. Their paper includes more than 800 references including many from adjacent fields.
Biographs
Professor Axtell is the author, with Joshua Epstein, of Growing Artificial Societies: Social Science from the Bottom Up (MIT Press). His research has appeared in Science, Nature, Proceedings of the National Academy of Sciences, as well as in leading field-specific journals such as The Journal of Economic Literature, The American Economic Review, The Economic Journal, and many others. His research has been reprised in newspapers (e.g., Wall St. Journal, Los Angeles Times, Washington Post) and science magazines (e.g., Scientific American, Technology Review, Wired). For the past decade he has been using microdata on individuals to build large-scale models of the Financial Crisis of 2008-9 (with JD Farmer, Oxford, and J Geanakoplos, Yale), the dynamics of business firms (with O Guerrero, Turing Institute), and natural resource exploitation, e.g., fisheries (with UC Santa Barbara, Oxford, and the Ocean Conservancy). The research on companies is described at length in a forthcoming book, ‘Dynamics of Firms from the Bottom Up: Data, Theories, and Models’, due out next year, which uses U.S. micro-data on firm sizes, ages, growth rates, networks, and locations to create a model at 1:1 scale with the American economy.
Prof. Doyne Farmer is an American complex systems scientist and entrepreneur with interests in chaos theory, complexity and econophysics. He has published papers in Science and Nature as well as leading economics journals like the Journal of Economic Behavior & Organization. He is Baillie Gifford Professor of Complex Systems Science at the Smith School of Enterprise and the Environment, Oxford University, where he is also director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School. Additionally, he is an external professor at the Santa Fe Institute. His current research is on complexity economics, focusing on systemic risk in financial markets and technological progress. He has recently published a book entitled ‘Making Sense of Chaos: A Better Economics for a Better World.’
CSSSA Secretary is inviting you to a scheduled Zoom meeting.
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