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AI backlash reaches major university with bold ban on laptops and phones for law students

FOX News

The University of Chicago is banning laptops, tablets and phones for first-year law students in a sweeping AI ban aimed at preserving critical thinking in legal education.


Nobel Prize winner leaving UC Berkeley for new role in China

Los Angeles Times

Things to Do in L.A. Tap to enable a layout that focuses on the article. Omar Yaghi, professor at the University of California, Berkeley, speaks during a media conference in Brussels, Oct. 8, 2025, after being one of three scientists awarded the Nobel Prize in chemistry. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.


18-year-old man arrested over 2025 cyberattack on internet cafe operator

The Japan Times

An 18-year-old man has been arrested for his suspected involvement in a cyberattack on an internet cafe operator. An 18-year-old man has been arrested for his suspected involvement in a cyberattack on the operator of the Kaikatsu Club internet cafe chain, according to investigative sources. On Wednesday, the Metropolitan Police Department's cybercrime countermeasure division arrested the company employee from Tokyo's Katsushika Ward, who was in the second year of high school at the time of the incident, on suspicion of fraudulent obstruction of business and violation of the law against unauthorized computer access. He has denied parts of the allegations, the sources said. In the cyberattack on the internet cafe chain operator Kaikatsu Frontier, a computer program that a high school boy from the city of Osaka developed using ChatGPT was used.


Starship delivery robots leave campuses for cities

FOX News

Starship Technologies is pulling 1,200 delivery robots from U.S. college campuses to focus on grocery delivery in cities across the United States and Europe.


The Business Model of Colleges Is Broken. It's About to Get Worse

TIME - Tech

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Supreme Court Upholds State Bans on Transgender Athletes

TIME - Tech

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Nancy Pelosi's next challenge: Building a nonpartisan democracy institute at UC Berkeley

Los Angeles Times

Things to Do in L.A. Tap to enable a layout that focuses on the article. Rep. Nancy Pelosi (D-San Francisco) tours the UC Berkeley campus alongside Chancellor Rich Lyons ahead of announcing the Nancy Pelosi Institute for Representative Democracy. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.


Carvalho was threatened with possible dismissal before he resigned as LAUSD superintendent

Los Angeles Times

Things to Do in L.A. Tap to enable a layout that focuses on the article. Alberto Carvalho addresses a press conference at Elysian Heights Elementary Arts Magnet in 2022. This is read by an automated voice. Please report any issues or inconsistencies here . See more from the L.A. Times in Google Search.


Statistical and Structural Approaches to Algorithmic Fairness

arXiv.org Machine Learning

Modern machine learning systems have outgrown their origins as isolated predictive constructs, evolving into complex socio-technical architectures that actively mediate human opportunity. As algorithms increasingly determine access to economic and social opportunities, it has become widely recognized that these systems are deeply embedded with the structural inequalities and prejudices of their environments. The field of algorithmic fairness emerged in response to the growing recognition that models optimized for predictive accuracy can systematically disadvantage marginalized groups. Early mitigation strategies, however, rested on fragile simplifications that limited their effectiveness in complex sociotechnical environments. This thesis identifies and addresses two fundamental limitations of contemporary fairness paradigms: the reliance on deterministic point estimates for auditing and the treatment of individuals as isolated entities devoid of structural context. First, the diagnosis of algorithmic unfairness has traditionally depended on scalar metrics that fail to capture the nuances of real-world deployment. This deterministic approach ignores the high statistical variance inherent in small, intersectional groups, often leading to false alarms or missed detections of bias. Furthermore, standard auditing struggles with the opacity of black-box models, frequently conflating unjustifiable bias with the influence of legitimate features.