The Australian Securities and Investments Commission and Australian Prudential Regulation Authority have urged financial market entities to move beyond awareness of frontier AI risks and begin preparing for their consequences. The regulators said increasingly capable AI models are accelerating cyber threats while adding pressure to the technology and operational risks financial institutions already face.
Ofcom has set out how it plans to enforce the UK’s Online Safety Act across more than 100,000 companies, detailing an approach that can begin with guidance and direct regulatory pressure but escalate to investigations, fines and, in certain cases, measures that disrupt a company’s business.
DermTech, the skin cancer testing company which filed for bankruptcy in 2024 and is now liquidating as DTech Liquidating, has agreed to resolve allegations that it violated the False Claims Act by knowingly submitting claims to Medicare for unreliable tests. Under the settlement announced Wednesday, the federal government received an allowed Class Three General Unsecured Claim of $5,038,011 in DermTech’s bankruptcy proceeding.
Google has agreed to pay £260 million to settle a lawsuit brought on behalf of UK app developers who accused the company of using its control over the Play Store to impose unfair commissions and restrictions on how their apps could reach customers, according to Reuters.
Manchester Airports Group said criminal hackers accessed data belonging to about 8.7 million customers in a cyberattack affecting systems used across Manchester, London Stansted and East Midlands airports, one of the largest breaches of customer information disclosed by a UK airport operator.
KKR & Co. has agreed to pay $250 million to settle Justice Department allegations that it repeatedly violated federal premerger review requirements, a penalty without precedent under a law whose effectiveness depends, in no small part, on companies telling regulators what they are required to know.
For South Korean AI developers, some useful data has come with an awkward choice. Get fresh consent from the people behind it, strip away enough identifying information to satisfy privacy requirements, or find another legal basis for using information that may have been collected for an entirely different reason. None is especially convenient when the object is to train an AI model on large and varied datasets.