Data Dive

The development of artificial intelligence (AI) and particularly Generative Artificial Intelligence (GenAI) has exploded in recent years, prompting government officials including the Biden administration to call for studies and recommendations that will likely lead to regulation on both the federal and state levels. With 35 out of 50 of the world’s leading AI tech companies based in California, the state’s Governor Gavin Newsom has stepped into the GenAI arena by issuing a September 6, 2023 executive order (EO) outlining steps to “foster[] a safe and responsible innovation ecosystem.”

In response to the exponential growth of artificial intelligence (AI) technologies over the past few years, the United States (U.S.) Department of Commerce’s National Institute of Standards and Technology (NIST) has been actively engaged in shaping the nation’s approach to AI, seeking to balance the societal benefits of trustworthy, inclusive and responsible AI against the inherent risks. Building on the White House’s “Blueprint for an AI Bill of Rights” and the January 2023 NIST AI Risk Management Framework (AI RMF 1.0), NIST’s recent activities signal continued focus on cultivating trust in AI technologies through the development of sufficient controls and exploration of regulatory intervention.

On September 8, 2023, federal court approved a consent decree from the Equal Employment Opportunity Commission (EEOC) with iTutorGroup Inc. and its affiliates (“iTutor”) over alleged age discrimination in hiring, stemming from automated systems in recruiting software. Arriving on the heels of the EEOC announcing its artificial intelligence (AI) guidance initiative, many are calling this case the agency’s first ever AI-based antidiscrimination settlement.¹ While it is not clear what, if any, AI tools iTutor used for recruiting, one thing is certain: We will soon see many more lawsuits involving employers’ use of algorithms and automated systems, including AI, in recruitment and hiring.²

New technical guidance on how to measure adverse impact when employment selection tools use artificial intelligence (AI) was released by the EEOC. Companies currently using or considering using AI or other algorithmic decision-making in the employment context should look to this nonbinding technical assistance when validating employment tests and other selection devices.

The European Parliament has reached agreement on the text of the Digital Services Act (DSA). The DSA is new legislation that will require certain providers of online services to comply with new obligations in order to ensure online safety and to prevent the spread of illegal content. The practical effects of the legislation will likely include increased compliance costs for businesses, possible organisational/personnel changes at a compliance level and increased accountability to relevant authorities.

As part of the Consolidated Appropriations Act, Congress had tasked the Federal Trade Commission (FTC) to examine whether artificial intelligence (AI) is a useful tool to combat the proliferation of harmful content online. In a June 2022 report titled, “Combatting Online Harms Through Innovation,” the FTC concluded that governments, platforms and other stakeholders must exercise great caution in mandating AI use, or over-relying on AI as a solution.

On March 10, 2022, the U.S. Department of Transportation’s (DOT) National Highway Traffic and Safety Administration (NHTSA) issued a first-of-its-kind final rule updating occupant safety requirements to account for vehicles that lack the traditional manual controls associated with a human driver.¹

On Deember 3, 2021, we published a client alert on the National Institute of Standards and Technology (NIST) issuing a request for public comment to help guide the development of the current and future state of technology in eight emerging technology areas. Those areas include artificial intelligence, the Internet of Things (IoT) (including in manufacturing), quantum computing, blockchain, unmanned delivery services, new and advanced materials and three-dimensional (3D) printing.