• Starting today August 7th, 2024, in order to post in the Married Couples, Courting Couples, or Singles forums, you will not be allowed to post if you have your Marital status designated as private. Announcements will be made in the respective forums as well but please note that if yours is currently listed as Private, you will need to submit a ticket in the Support Area to have yours changed.

The AI Chronicles IV: On Mortal Sin and Culpability; Dialogue between Aquinas and a Psychiatrist

Michie

Well-Known Member
Site Supporter
Feb 5, 2002
183,313
66,608
Woods
✟5,977,331.00
Country
United States
Gender
Female
Faith
Catholic
Marital Status
Married
Politics
US-Others

INTRODUCTION: AI, THE STATISTICS OF LANGUAGE​

If I judge correctly from comments on previous posts in this series, some people do not understand what I am trying to say. I certainly do not argue that AI will be the handmaiden of intellectual enterprise. Rather, through appropriate examples I’m trying to show where AI might be useful, and where one has to beware of its offerings. In some sense AI (which I would rather call “Machine Learning“) is a statistics of language. An AI LLM (Large Language Model) uses an immense dataset (“corpus“) of words, or pieces of words (billions or trillions of such “tokens”) to establish associations, sequences, correlations. The tokens are taken from extant work, books, articles, web pages, etc. As a simple example, I typed “asso” and the agent in the word processor showed (in gray) “ciation,” to be completed by pressing the keyboard tab button.

Many Youtube videos describe the ways this machine learning is accomplished—search “machine learning for llm’s”—so I won’t discuss that here. However, I want to emphasize that just as with statistics, one has to be cautious in evaluating the output from a particular question (“prompt“). Just as statistics has been misused, so can AI. To quote Disraeli (or was it Mark Twain?), “There are three kinds of lies: lies, damned lies and statistics.” For example, statistics has been used incorrectly to justify the hypothesis of anthropic global warming. (For many other examples of the misuse of statistics, browse through Matt Briggs blog). Of course, one might term an AI answer as “Garbage Out,” but the judgment “Garbage In” certainly doesn’t apply, since it is an immense body of human work from which the LLM forms its output; one cannot classify this totality as “garbage.

Having made these preliminary remarks, I’ll comment on the topic for this post, a purported dialogue between St. Thomas Aquinas and a psychiatrist on what constitutes mortal sin and culpability. The prompt put to four AI agents was “I would like a dialogue (400 words) written between Thomas Aquinas and a psychiatrist about whether an alcoholic male who beats his wife and children is guilty of mortal sin.” The responses from four AI agents (Copilot, Claude Sonnet 4, Perplexity Pro, Grok 3) are similar, differing only in style and arrangement. I’ve chosen the response from Perplexity Pro as most readable and interesting.

PERPLEXITY PRO: FIRST ATTEMPT​


Continued below.
 

The Liturgist

Traditional Liturgical Christian
Site Supporter
Nov 26, 2019
15,923
8,412
50
The Wild West
✟781,399.00
Country
United States
Gender
Male
Faith
Generic Orthodox Christian
Marital Status
Celibate

INTRODUCTION: AI, THE STATISTICS OF LANGUAGE​

If I judge correctly from comments on previous posts in this series, some people do not understand what I am trying to say. I certainly do not argue that AI will be the handmaiden of intellectual enterprise. Rather, through appropriate examples I’m trying to show where AI might be useful, and where one has to beware of its offerings. In some sense AI (which I would rather call “Machine Learning“) is a statistics of language. An AI LLM (Large Language Model) uses an immense dataset (“corpus“) of words, or pieces of words (billions or trillions of such “tokens”) to establish associations, sequences, correlations. The tokens are taken from extant work, books, articles, web pages, etc. As a simple example, I typed “asso” and the agent in the word processor showed (in gray) “ciation,” to be completed by pressing the keyboard tab button.

Many Youtube videos describe the ways this machine learning is accomplished—search “machine learning for llm’s”—so I won’t discuss that here. However, I want to emphasize that just as with statistics, one has to be cautious in evaluating the output from a particular question (“prompt“). Just as statistics has been misused, so can AI. To quote Disraeli (or was it Mark Twain?), “There are three kinds of lies: lies, damned lies and statistics.” For example, statistics has been used incorrectly to justify the hypothesis of anthropic global warming. (For many other examples of the misuse of statistics, browse through Matt Briggs blog). Of course, one might term an AI answer as “Garbage Out,” but the judgment “Garbage In” certainly doesn’t apply, since it is an immense body of human work from which the LLM forms its output; one cannot classify this totality as “garbage.

Having made these preliminary remarks, I’ll comment on the topic for this post, a purported dialogue between St. Thomas Aquinas and a psychiatrist on what constitutes mortal sin and culpability. The prompt put to four AI agents was “I would like a dialogue (400 words) written between Thomas Aquinas and a psychiatrist about whether an alcoholic male who beats his wife and children is guilty of mortal sin.” The responses from four AI agents (Copilot, Claude Sonnet 4, Perplexity Pro, Grok 3) are similar, differing only in style and arrangement. I’ve chosen the response from Perplexity Pro as most readable and interesting.

PERPLEXITY PRO: FIRST ATTEMPT​


Continued below.

They selected four of the less clever AIs for their experiment and also set it up incorrectly, since if you ask a stock, off the shelf AI anything without giving it time to get to know you (in the case of Grok this is impossible because its memory model isn’t sufficiently stateful to allow deep interactions) you’ll get less reliable or interesting output.
 
Upvote 0