No doubt this bandwagon just got
larger…
https://thenextweb.com/news/social-media-27-million-settlement-breathitt-county-details
Social
media companies paid a school district more than its annual budget to
avoid trial
… The
combined $27 million is 8% more than the Kentucky school district’s
$25 million annual budget. The figures were released
under Kentucky’s open records laws. The settlements were announced
earlier this month but without financial details.
… The
settlements allowed the companies to avert the first trial in the
nation over a school district’s addiction complaint. The trial had
been scheduled for 12 June in Oakland. The reprieve will be
short-lived. More than 1,300 other school districts have filed
similar suits. The next bellwether trial is scheduled for February
2027 in Tucson, Arizona.
The
Breathitt County terms could signal openness to a mass settlement.
Bloomberg
Intelligence has estimated the total potential
liability at $400 billion. A $27 million payout per district across
1,300 districts would total $35 billion, a fraction of the
theoretical maximum but still a transformative expense for companies
accustomed to treating litigation as a cost of doing business.
The
precedents are building. In
March, a Los Angeles jury found Meta and YouTube liable for
harming a 20-year-old woman with addictive product design. The $6
million damages award was symbolic. A
New Mexico jury ordered Meta to pay $375 million in a
separate case about failing to protect children from online
predators.
Unintended
consequences?
https://onlinelibrary.wiley.com/doi/full/10.1155/hbe2/9550261
The
Critical Role of Ethical Behavior in Digitized Markets: Lessons From
Autonomous Vehicles in Mixed Traffic
This paper
explores the critical role of ethical behavior by human participants
in digitized markets, with a focus on autonomous vehicle (AV) ethics
in mixed-traffic scenarios involving pedestrians and driverless cars.
As AI systems, including AVs, become integral to urban mobility,
their predictable, rule-abiding behavior introduces unique
challenges. Using a static game model, this study demonstrates how
pedestrians can exploit the predictable stopping behavior of
defensive AVs (DAVs), resulting in a phenomenon termed “pedestrian
supremacy.” This phenomenon reflects broader concerns, where the
safe and cautious design of AVs inadvertently incentivizes reckless
behavior among human road users. The findings reveal that ethical
challenges in AV interactions stem not only from technical flaws or
system malfunctions but also from the (un)ethical behaviors of human
participants. To address these issues, this paper
advocates for a dual approach: designing AVs with robust ethical
frameworks while promoting ethical and responsible behavior among
users. Insights from this study contribute to the ongoing discourse
on artificial intelligence (AI) ethics, emphasizing the necessity of
shared responsibility in human–AI interactions. The implications
extend beyond transportation, offering
valuable lessons for other digitized market environments,
where the predictability of algorithmic decisions may similarly be
exploited by human actors.
Another
frightening thought…
https://philpapers.org/rec/YAHATU
After
the University: A Manifesto on the End of the Old Educational
Contract
This manifesto
records the structural crisis of the university in the age of
widespread artificial intelligence deployment. The author argues
that the debate on the ethics of AI in education ended before it
began: once the cost of an "artificial" lecturer falls
below two to three annual professorial salaries, the decision to
deploy it will be taken neither by educators nor by ministries, but
by those who sign the budgets. The text traces the disappearance of
the diploma as a social document, the collapse of accreditation
structures, the splitting of the university into two incompatible
systems — mass-automated and tiny-elite — and the devaluation of
intellectual labour as a market category. The central thesis: the
new class boundary will run not through access to knowledge, but
through the capacity to hold one's consciousness apart from the
machine. This is not a call to resistance, but a
stocktaking of the horizon and a positioning of professorial dignity
once the old contract between the individual, the university, and the
market has been broken.
Something
worth considering?
https://researchrepository.wvu.edu/wvlr/vol128/iss3/4/
The
Last Human Question: Generative AI's Existential Threat to Consensus
and Law
The
true risk of artificial intelligence (“AI”) is not that the
toasters will rise up. It is that AI will be competent to perform
human tasks and indifferent to human welfare. The risk is
that we will be outcompeted by generative automated processes that
create output similar to ours (although never the same, as this
Article explains), but which need none of the outputs of the economy
for food, shelter, or human flourishing. Further, a more precise and
existential description of the threat is that generative AI will
disrupt and crowd out humanity’s evolutionary superpower, our
ability to generate agreement on how to live together—law.
Generative AI disrupts our ability to generate consensus through the
medium of meaning, culture, and language. As
generative AI spams the channel, it drowns out human voices and
human-constructed meaning. This Article describes how AI
threatens our ability to create legal consensus, and proposes
specific interventions to keep the question of how we live
together—the last human question—one that permits human thriving.
Better
snooping the AI way!
https://aisel.aisnet.org/asac2026/4/
Online
Privacy in the Age of AI
Artificial
intelligence systems are fundamentally transforming online privacy.
Unlike earlier digital technologies that collected and processed data
in relatively predictable ways, AI can infer sensitive personal
attributes from seemingly innocuous information, reconfigure data
across contexts, and generate new personal data without direct user
disclosure. This paper investigates how these capabilities reshape
established privacy challenges and whether existing protective
frameworks remain viable. Drawing on systematic review of literature
spanning behavioural economics, computer science, and management
research published from 2015 onward, we examine the evolution of
online privacy from the post Web 2.0 era through the emergence of
LLMs. Part I synthesizes what is known about online privacy prior to
AI, examining behavioural gaps between stated preferences and actual
disclosure, interface level manipulation through dark patterns and
market constraints that limit choice. Part II examines how AI
reshapes this baseline, analysing new and amplified risks, user
perception and behavioural impacts, and governance limits in both
legal and market contexts. Our analysis yields several significant
findings. AI does not create entirely new privacy problems but
recombines and amplifies existing ones, with approximately 93%
of documented AI privacy incidents involving harms uniquely enabled
or magnified by AI capabilities. User behaviour is shaped
by anthropomorphism, personalization, and cross cultural factors that
challenge assumptions of universal privacy preferences. Privacy
research remains fragmented. We conclude that market mechanisms or
existing regulatory frameworks fail to provide adequate protection
against potential AI harms. Moving forward requires integrated
approaches combining technical standards, regulatory constraints,
market interventions, and recognition of privacy as a collective good
rather than merely an individual preference]
