THE AI CON by Emily M.
Bender and Alex Hanna offers a unique perspective on “How to Fight Big Tech's
Hype and Create the Future We Want.” In fact, Kirkus describes this book
as “a refreshingly contrarian take on AI” and includes it in a list of “5 Essential
New Books That Challenge Big Tech” (Careless People, on my TBR pile, is
also included). Bender is a Linguistics professor at the University of
Washington and Hanna, a former member of the ethical AI team at Google, is now Director
of Research at the Distributed AI
Research Institute (DAIR); both have been critical about promises made
and potential societal impact of AI. They have crafted this book with the following
goal: “preventing harm from AI hype. [They believe] When people can spot AI
hype, they make better decisions about how and when to use automation, and they
are in a better position to advocate for policies to constrain the use of
automation by others.” Bender and Hanna raise issues such as surveillance (including
facial recognition often coupled with biased algorithms) or devaluing
creativity, and they point to the importance of more discussion and evaluation.
They focus on the application of automation in the areas of decision-making, classification,
recommendation, transcription/translation, and text/image generation. Bender
and Hanna provide an entire chapter containing questions which “we can each
ask, whenever we are in a position to make decisions about automation or
influence others who are doing so.” Prompting more thoughtful consideration,
they certainly ignited my desire to investigate further with sources such as The
Conversation, Journalist’s Resource, CNET’s ai atlas, and think
tanks like Brookings
Institution or reports from CQ Researcher (citing AI Now Institute, Center for
Democracy & Technology, MIT, Pew
Research Center, and The
Stanford Institute for Human Centered AI, as just a few examples). As an aide to critical thinking and
accountability, roughly a third of their text is devoted to notes and an index.
Interested readers may also want to explore their podcast: Mystery AI Hype Theater 3000.
In
contrast,
AI FOR LIFE by Celia Quillian offers “100+ Ways to Use
Artificial Intelligence to Make Your Life Easier, More Productive…and More Fun!”
PC Magazine recently
interviewed the author and begins by quoting her: “Approach AI with curiosity,
not fear.” Quillan, who has been featured as a commentator on AI by several
business publications, begins by discussing “getting started with generative AI”
and then offers numerous helpful suggestions (e.g., “explain it to me like I’m
12” or “ask me 10 questions to better guide your response”) in a chapter titled
“Prompting 101.” From there, she delves into using AI and devotes a chapter to
each of the following areas: Home Life; Food, Health, and Wellness; Career
Development; Personal Finance; Personal Growth and Learning; Relationships;
Travel; and Fun and Entertainment. Using travel as an example, readers will
find a series of helpful suggestions for personalizing destination ideas (e.g.,
What is the best time of year to travel? What are some must-do activities? What
is the estimated cost per person?), planning road trips, and exploring local
cuisine. This should help users new to AI because her prompts are often quite
instructive and specific, like this one: “Could you identify 10 upcoming events
or performances in and around Philadelphia's music, arts, or nightlights scenes
in May 2025? Make note of the date they are happening and provide a brief
description of the event.” Packing tips, local etiquette, and translation are
other topics she explores in that travel chapter. My teaching experience has
reinforced the view that people learn best when they are pursuing a task
relevant to them – Quillian highlights numerous ways to experiment with AI in a
personally meaningful way. Although her text is not up-to-the minute (e.g., no
reference to Deepseek), she does provide information on several models and AI FOR LIFE should propel readers to a better understanding
of the benefits and limitations of AI. This important topic was just addressed in an Atlantic article, “What Happens When People Don’t Understand How AI Works?” by Tyler Austin
Harper. Coming full circle, he references Bender and Hanna, expresses concern
about the industry’s “tradition of anthropomorphizing,” and argues that large
language models “do not think and feel but instead mimic and mirror.” And
laments further about “minimizing attention spans, literacy, and social
cohesion.” Much to reflect upon and consider.
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