Page 9 - SeptemberOctober25 Report

Consider this: the first LLM, Eliza,
was created in 19663 as a chatbot ther-
apist. Today, chatbots are everywhere,
from customer service to healthcare. So,
any meaningful reform would have to
extend far beyond ChatGPT and touch
nearly every digital interaction we have.
That’s not a simple code update, it’s an
overhaul.
The next suggestion: layered forms
of governance for the AI itself and its
developers.
This suggestion is a major under-
taking, but does make sense as a way
to govern AI. A hard-and-fast law
governing the use of AI is impractical,
given that AI is constantly evolving.
But having general safety mechanisms
in place, such as requiring AI systems
to comply with anti-terrorism laws and
ensuring they aren’t being used to break
the law feels like a reasonable baseline.
These mechanisms could also include
compliance with applicable data privacy
regulations. However, these baseline rules
wouldn’t address the kind of guardrails
discussed earlier. And while they may not
be legally binding, industry guidelines and
frameworks, like those developed by the
National Institute of Standards and Tech-
nology (NIST) have increasingly become
the de facto standard.
These types of frameworks don’t just
offer best practices; they’re also more
adaptable. Unlike legislation, they can
So, what did Claude do with
that information? What any
constitutionally governed
AI would do. It attempted to
blackmail the executive.
evolve alongside the technology, which
makes them a more realistic tool for
managing the pace and complexity of AI
development.
When you consider the remaining
objectives ChatGPT suggested for
governing itself, they reveal, in my
opinion, some of the flaws of Generative
AI. For example, ChatGPT recommended
global coordination, public engagement
(through citizen assemblies or panels),
adaptive governance (like sunset clauses
and living regulatory sandboxes), and
prioritizing certain forms of AI over
others (notably excluding itself from that
focus).
In theory, these ideas sound great.
In practice, they’re far more diffi-
cult to implement and would require
immense coordination. For example,
global coordination? Global? That’s
no small feat. Look at the current state
of data privacy regulation. Over 140
countries have enacted national data
protection laws. While there’s some
overlap, there’s still no comprehen-
sive global standard.4 Overlap, yes.
Comprehensive global standard? No.
And let’s not forget AI has been
around for nearly 60 years, yet we still
have very few laws specifically designed
to govern it. That’s not to say there aren’t
laws that intersect with AI regulation. But
very few were written with AI in mind.
That may change in the near future, but
for now, it’s hard to imagine global coordi-
nation when many countries haven’t even
managed to align internally.
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THE REPORT | September/October 2025 | CincyBar.org 9