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]
