President Joe Biden on Wednesday signed an executive order that will narrowly prohibit certain United States investments in sensitive technology in China and require government notification of funding in other tech sectors. Biden said in a letter to Congress he was declaring a national emergency to deal with the threat of advancement by countries like China "in sensitive technologies and products critical to the military, intelligence, surveillance, or cyber-enabled capabilities". The long-awaited order authorises the US treasury secretary to prohibit or restrict certain US investments in Chinese entities in three sectors: semiconductors and microelectronics, quantum information technologies, and certain artificial intelligence systems. Senior administration officials said that the effort stemmed from national security goals, rather than economic interests and that the categories it covered were narrow in scope. The order seeks to blunt China's ability to use US investments in its technology companies to upgrade its military while also preserving broader levels of trade that are vital for both nations' economies.

Should artificial intelligence or machine learning (AI/ML) be allowed to alter FDA approved software in medical devices? If so, where should the guardrails be set? The discussions and debates surrounding AI/ML are heated; some believe the technology may destroy humanity, while others look forward to the speed of advancement it will allow. The FDA is getting out ahead on this debate. This week the agency drafted a list of “guiding principles” intended to begin developing best practices for machine learning within medical devices. A new framework envisioned by the FDA includes a “predetermined change control plan” in premarket submissions. This plan would include the types of anticipated modifications, referred to as “Software as a Medical Device Pre-Specifications”. The associated methodology used to implement those changes in a measured and controlled approach that manages risk the FDA calls the “Algorithm Change Protocol.”

The California Fair Employment and Housing Council (FEHC) recently took a major step towards regulating the use of artificial intelligence (AI) and machine learning (ML) in connection with employment decision-making. On March 15, 2022, the FEHC published Draft Modifications to Employment Regulations Regarding Automated-Decision Systems, which specifically incorporate the use of "automated-decision systems" in existing rules regulating employment and hiring practices in California. The draft regulations seek to make unlawful the use of automated-decision systems that "screen out or tend to screen out" applicants or employees (or classes of applicants or employees) on the basis of a protected characteristic, unless shown to be job-related and consistent with business necessity. The draft regulations also contain significant and burdensome recordkeeping requirements. Before the proposed regulations take effect, they will be subject to a 45-day public comment period (which has not yet commenced) before FEHC can move toward a final rulemaking.

The National Science Foundation and the White House's Office of Science and Technology Policy are developing a plan to make high-performance computing, machine-learning datasets and other resources more widely available to artificial intelligence researchers at every level. Developing artificial intelligence tools and technologies requires lots of data and even more computing resources. Gaining a national advantage in this area will require a significant concentration of work that is currently limited to agencies and organizations that have those resources. But the best, groundbreaking ideas aren't always centered in places with the most resources. To address this issue, the 2021 National Defense Authorization Act charged NSF and OSTP with developing a plan to build up those resources and make sure they are available to people throughout the U.S. who can make good use of them.

Five federal financial regulatory agencies, including NCUA and the Consumer Financial Protection Bureau, announced Monday they will extend the comment period on the request for information on financial institutions' use of artificial intelligence (AI) until July 1, 2021. The agencies are seeking information from the public on how financial institutions use AI in their activities, including fraud prevention, personalization of customer services, credit underwriting, and other operations. More specifically, the RFI seeks comments to better understand the use of AI, including machine learning, by financial institutions; appropriate governance, risk management, and controls over AI; and challenges in developing, adopting, and managing AI. The agencies extended the comment period to allow stakeholders more time to coordinate and prepare their comments, which were originally due by June 1, 2021.

Back in 2019, Ben Lorica and I wrote about deepfakes. Ben and I argued (in agreement with The Grugq and others in the infosec community) that the real danger wasn't "Deep Fakes." The real danger is cheap fakes, fakes that can be produced quickly, easily, in bulk, and at virtually no cost. Tactically, it makes little sense to spend money and time on expensive AI when people can be fooled in bulk much more cheaply. I don't know if The Grugq has changed his thinking, but there was an obvious problem with that argument.