Lauren's Blog: Artificial Intelligence at the Crossroads
https://lauren.vortex.com/2023/07/13/artificial-intelligence-at-the-crossroads
Suddenly there seems to be an enormous amount of political,
regulatory, and legal activity regarding AI, especially generative AI.
Much of this is uncharacteristically bipartisan in nature.
The reasons are clear. The big AI firms are largely depending on their
traditional access to public website data as the justification for
their use of such data for their AI training and generative AI
systems.
This is a strong possibility that this argument will ultimately fail
miserably, if not under current laws then under new laws and
regulations likely to be pushed through around the world, quite likely
in a rushed manner that will have an array of negative collateral
effects that could actually end up hurting many ordinary people.
Google for example notes that they have long had access to public
website data for Search.
Absolutely true. The problem is that generative AI is wholly different
in terms of its data usage than anything that has ever come before.
For example, ordinary Search provides a direct value back to sites
through search results pages links -- something that the current
Google CEO has said Google wants to de-emphasize (colloquially, "the
ten blue links") in favor of providing "answers".
Since the dawn of Internet search sites many years ago, search results
links have long represented a usually reasonable fair exchange for
public websites, with robots.txt (Robots Exclusion Protocol) available
for relatively fine-grained access control that can be specified by
the websites themselves, and which at least the major search firms
generally have honored.
But generative AI answers eliminate the need for links or other "easy
to see" references. Even if "Google it!" or other forms of "more
information" links are available related to generative AI answers at
any AI firm's site, few users will bother to view them.
The result is that by and large, today's generative AI systems by
their very nature return essentially nothing of value to the sites
that provide the raw knowledge, data, and other information that
powers AI language/learning models.
And typically, generative AI answers (leaving aside rampant inaccuracy
problems for now) are like high school term papers that haven't even
included sufficient (if any) inline footnotes and comprehensive
bibliographies with links.
A very quick "F" grade at many schools.
I have proposed extending robots.txt to help deal with some of these
AI issues -- and Google also very recently proposed discussions around
this area.
Giving Creators and Websites Control Over Generative AI:
https://lauren.vortex.com/2023/02/14/giving-creators-and-websites-control-over-generative-ai
But ultimately, the "take -- and give back virtually nothing in
return" modality of many AI systems inevitably leads toward enormous
pushback. And I do not sense that the firms involved fully understand
the cliff that they're running towards in a competitive rush to push
out AI systems long before they or the world at large are ready for
them.
These firms can either grasp the nettle themselves and rethink the
problematic aspects of their current AI methodologies, or continue
their current course and face the high probability that governmental
and public concerns will result in major restrictions to their AI
projects -- restrictions that may seriously negatively impact their
operations and hobble positive AI applications for users around the
world long into the future.
- - -
--Lauren--
Lauren Weinstein
[email protected] (https://www.vortex.com/lauren)
Lauren's Blog: https://lauren.vortex.com
Twitter: https://twitter.com/laurenweinstein
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Founder: Network Neutrality Squad: https://www.nnsquad.org
PRIVACY Forum: https://www.vortex.com/privacy-info
Co-Founder: People For Internet Responsibility
Tel: +1 (818) 225-2800
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