The Future of Higher Education - 13

Part 3: Technology and Education
effort, especially if assignments make this easy
to do. For some observers and practitioners,
generative AI represents a call to overhaul the
entire college writing assessment system.
Students and faculty can use generative AI for
research as well. This was not so apparent when
ChatGPT-3 appeared, as it had access to a limited
swath of the web and often generated citations
poorly or not at all. Competition has improved
the picture, with Google's Bard capable of selfcritique
for Google search, Bing's default of
citing web resources to queries, and new tools
emerging. Some scholarly journals and societies
have taken official positions against researchers
relying on generative AI to produce content, but
it seems likely that faculty, staff, and students will
increasingly use these applications in their work.
There is also the possibility of replacing some
academic work functions, or jobs, with AI. At an
operational level, people are experimenting with
using the technology to perform a wide range of
tasks, from writing (and summarizing) memos
to creating strategies and writing code. Similarly
there are many examples of using AI to teach
without a teacher's intervention. Two centuries
of industrial progress offer ample precedent
for replacing humans with machines, and
that possibility is now before us. The financial
pressures noted above may encourage campus
leaders to take such steps.
Yet engaging with generative AI brings a different
swarm of challenges to colleges and universities.
To begin with, the technologies are in their early
days and are developing very, very rapidly. It
is difficult for any organization to keep up with
the contours of this emerging ecosystem, much
less to follow evolving feature sets. This makes
things more challenging for campus IT and
academic computing units as they must decide
Part 3: Technology and Education
10
which applications to support and how to assist
faculty and staff in using them. Pedagogies are
developing at a similar clip. At a deeper level,
key elements in that generative AI ecosystem are
potentially in flux. For example, legal threats exist
to these projects, based on complaints that they
infringe on copyrights at a massive scale, can
facilitate private violations, and may pose serious
security risks. Courts, nations, and companies
may rule or issue policies against generative AI.
In other words, the sudden rise of this technology
could plausibly be followed by a fall. All of this
makes it difficult for academics to decide what to
do with AI.
There is also a macroeconomic picture to
consider. It is possible that AI, along with
robotics, will change the labor market for
which higher education prepares students. One
scenario is of automation replacing humans
across the economy, leading to widespread
under- and unemployment. A second sees
human creativity generating new jobs to deal
with automation, much as we created new jobs
in the industrial era as innovations supplanted
older ways of work. A third possibility is that
automation won't replace humans, but will
instead partner with us. Workers in this world
will increasingly labor alongside AI and/or
robotics. In each of these cases colleges and
universities should consider their curriculum and
pedagogical practices for the emerging economy.
The Future of Higher Education

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