The best way to approach issues that seem
limited and exclusively technical is often to reframe them as "public
problems," a notion popularized by philosopher and educator John Dewey
over a century ago. Unclean air, contaminated water, global warming, and early
childhood education are a few examples of public issues. Although the damages
caused by public issues are not often felt personally, they still influence
what it means to be a healthy individual in a thriving society. It is necessary
to acknowledge, talk about, and work together to address these issues.
According to Dewey, public issues arise when individuals encounter
"indirect consequences" that must be collectively and
"systematically cared for," independent of a person's circumstances,
income, privilege, or interests. This is in contrast to problems that are
personal, private, or technical. Our common realities are defined by public
challenges.
Although generative AI has always been seen as a technical issue, redefining it
as a public issue opens up new options for intervention. Generative AI is
rapidly evolving into a language for educating us about one another and the
tales that our civilization has to tell. Essentially, you are asking a
probabilistic machine learning model to provide a statistically sound
explanation of a public concern when you ask generative AI to produce an
explanation of climate change narrative or movie. Tools like Chat GPT and Mid
Journey are quickly becoming into languages for comprehending societal issues,
but there hasn't been much examination of how they might influence the
narratives people employ to comprehend the shared consequences that Dewey said
define public life.
The claims made by tech giants and AI
"godfathers," who contend that generative AI poses an existential
danger and is a matter best left to engineers, should be rejected by every
member of society. Public issues are discussed, taken into consideration, and
handled together.
In order to properly deal with generative AI, both developers and users must
see it as a rapidly developing language that humans use to communicate, learn,
and make sense of their surroundings—rather of just seeing it as biased
datasets and machine learning gone wild. Stated differently, it must be seen as
a public issue.
Initially, scientists must see generative AI
as a powerful language—as "infrastructures," "boundaries,"
and "hinges" that scientists and technologists claim help build
innovations. This entails tracking the relationships between the humans and the
machines that create synthetic language: engineers who create machine learning
systems, for instance; company owners who present business concepts;
journalists who create fake news; and viewers who find it difficult to decide
which sources to trust. Generative AI is a language for knowledge
representation, invention, storytelling, and shared worlds because of these
intricate and mostly unseen presumptions.
Second, we must examine the negative effects of generative AI as a society.
When chat bots misidentify authors, statistical hallucinations fabricate facts,
or computational summaries misunderstand analysis, the result is dangerously
incorrect language with the assurance of an apparently unbiased, computational
certainty. Not only are these inaccuracies peculiar and infrequent in
misrepresentation, but their actual and perceived presence casts the media in a
negative light and erodes public confidence. The sources of information used by
society and its capacity to assess reality are unstable.
Lastly, the claims made by tech giants and AI
"godfathers" that generative AI poses an existential danger and is an
issue best solved by technologists should be rejected by all members of
society. Public issues are not the domain of private enterprises or
self-described guardians who operate on their own timeframes with proprietary
information; rather, they are collaboratively discussed, accounted for, and
handled. Problems that are really public are never delegated to private
organizations or charismatic leaders.
A public issue is not only an unavoidable
future, a moral crisis, or a curious technical question. It is a system of
interactions between humans and machines that produces language, is prone to
error, and requires regular maintenance. We will be in a better position to
address the issue as a public one if we recognize generative AI as a crucial
language for building shared realities and addressing group problems.
Mr. Atul
Tiwari
Assistant
Professor I
Mechanical
Engineering Department
