Photo of Olivia Dworkin

Olivia Dworkin

Olivia Dworkin minimizes regulatory and litigation risks for clients in the pharmaceutical, food, consumer brands, digital health, and medical device industries through strategic advice on FDA compliance issues.
Olivia defends her clients against such litigation as well, representing them through various stages of complex class actions and product liability matters. She maintains an active pro bono practice that focuses on gender-based violence, sexual harassment, and reproductive rights.

Prior to joining Covington, Olivia was a fellow at the University of Michigan Veterans Legal Clinic, where she gained valuable experience as the lead attorney successfully representing clients at case evaluations, mediations, and motion hearings. At Michigan Law, Olivia served as Online Editor of the Michigan Journal of Gender and Law, president of the Trial Advocacy Society, and president of the Michigan Law Mock Trial Team. She excelled in national mock trial competitions, earning two Medals for Excellence in Advocacy from the American College of Trial Lawyers and being selected as one of the top sixteen advocates in the country for an elite, invitation-only mock trial tournament.

Contact:Read more about Olivia DworkinEmail

On September 6, Senator Bill Cassidy (R-LA), the Ranking Member of the U.S. Senate Health, Education, Labor and Pensions (HELP) Committee, issued a white paper about the oversight and legislative role of Congress related to the deployment of artificial intelligence (AI) in areas under the HELP Committee’s jurisdiction, including health and life sciences.  In the white paper, Senator Cassidy disfavors a one-size-fits-all approach to the regulation of AI and instead calls for a flexible approach that leverages existing frameworks depending on the particular context of use of AI.  “[O]nly if our current frameworks are unable to accommodate . . . AI, should Congress look to create new ones or modernize existing ones.”  The Senator seeks public feedback on the white paper by September 22, 2023.  Health care and life sciences stakeholders should consider providing comments. 

This blog outlines five key takeaways from the white paper from a health care and life sciences perspective. Note that beyond health and life sciences issues, the white paper also addresses considerations for other areas, such as use of AI in educational settings and labor/employment implications created by use of AI.

5 Key Takeaways for AI in Health Care and Life Sciences

The white paper – entitled “Exploring Congress’ Framework for the Future of AI: The Oversight and Legislative Role of Congress Over the Integration of Artificial Intelligence in Health, Education, and Labor” – describes the “enormous good” that AI in health care presents, such as “the potential to help create new cures, improve care, and reduce administrative burdens and overall health care spending.”  At the same time, Senator Cassidy notes that AI presents risks that legal frameworks should seek to minimize.  Five key takeaways from the white paper include:…

Continue Reading Framework for the Future of AI: Senator Cassidy Issues White Paper, Seeks Public Feedback

This quarterly update summarizes key legislative and regulatory developments in the second quarter of 2023 related to key technologies and related topics, including Artificial Intelligence (“AI”), the Internet of Things (“IoT”), connected and automated vehicles (“CAVs”), data privacy and cybersecurity, and online teen safety.

Artificial Intelligence

AI continued to be an area of significant interest of both lawmakers and regulators throughout the second quarter of 2023.  Members of Congress continue to grapple with ways to address risks posed by AI and have held hearings, made public statements, and introduced legislation to regulate AI.  Notably, Senator Chuck Schumer (D-NY) revealed his “SAFE Innovation framework” for AI legislation.  The framework reflects five principles for AI – security, accountability, foundations, explainability, and innovation – and is summarized here.  There were also a number of AI legislative proposals introduced this quarter.  Some proposals, like the National AI Commission Act (H.R. 4223) and Digital Platform Commission Act (S. 1671), propose the creation of an agency or commission to review and regulate AI tools and systems.  Other proposals focus on mandating disclosures of AI systems.  For example, the AI Disclosure Act of 2023 (H.R. 3831) would require generative AI systems to include a specific disclaimer on any outputs generated, and the REAL Political Advertisements Act (S. 1596) would require political advertisements to include a statement within the contents of the advertisement if generative AI was used to generate any image or video footage.  Additionally, Congress convened hearings to explore AI regulation this quarter, including a Senate Judiciary Committee Hearing in May titled “Oversight of A.I.: Rules for Artificial Intelligence.”

There also were several federal Executive Branch and regulatory developments focused on AI in the second quarter of 2023, including, for example:

  • White House:  The White House issued a number of updates on AI this quarter, including the Office of Science and Technology Policy’s strategic plan focused on federal AI research and development, discussed in greater detail here.  The White House also requested comments on the use of automated tools in the workplace, including a request for feedback on tools to surveil, monitor, evaluate, and manage workers, described here.
  • CFPB:  The Consumer Financial Protection Bureau (“CFPB”) issued a spotlight on the adoption and use of chatbots by financial institutions.
  • FTC:  The Federal Trade Commission (“FTC”) continued to issue guidance on AI, such as guidance expressing the FTC’s view that dark patterns extend to AI, that generative AI poses competition concerns, and that tools claiming to spot AI-generated content must make accurate disclosures of their abilities and limitations.
  • HHS Office of National Coordinator for Health IT:  This quarter, the Department of Health and Human Services (“HHS”) released a proposed rule related to certified health IT that enables or interfaces with “predictive decision support interventions” (“DSIs”) that incorporate AI and machine learning technologies.  The proposed rule would require the disclosure of certain information about predictive DSIs to enable users to evaluate DSI quality and whether and how to rely on the DSI recommendations, including a description of the development and validation of the DSI.  Developers of certified health IT would also be required to implement risk management practices for predictive DSIs and make summary information about these practices publicly available.

…
Continue Reading U.S. Tech Legislative & Regulatory Update – Second Quarter 2023

This quarterly update summarizes key legislative and regulatory developments in the fourth quarter of 2022 related to Artificial Intelligence (“AI”), the Internet of Things (“IoT”), connected and autonomous vehicles (“CAVs”), and data privacy and cybersecurity.

Artificial Intelligence

In the last quarter of 2022, the annual National Defense Authorization Act (“NDAA”), which contained AI-related provisions, was enacted into law.  The NDAA creates a pilot program to demonstrate use cases for AI in government. Specifically, the Director of the Office of Management and Budget (“Director of OMB”) must identify four new use cases for the application of AI-enabled systems to support modernization initiatives that require “linking multiple siloed internal and external data sources.” The pilot program is also meant to enable agencies to demonstrate the circumstances under which AI can be used to modernize agency operations and “leverage commercially available artificial intelligence technologies that (i) operate in secure cloud environments that can deploy rapidly without the need to replace operating systems; and (ii) do not require extensive staff or training to build.” Finally, the pilot program prioritizes use cases where AI can drive “agency productivity in predictive supply chain and logistics,” such as predictive food demand and optimized supply, predictive medical supplies and equipment demand, predictive logistics for disaster recovery, preparedness and response.

At the state level, in late 2022, there were also efforts to advance requirements for AI used to make certain types of decisions under comprehensive privacy frameworks.  The Colorado Privacy Act draft rules were updated to clarify the circumstances that require controllers to provide an opt-out right for the use of automated decision-making and requirements for assessments of profiling decisions.  In California, although the California Consumer Privacy Act draft regulations do not yet cover automated decision-making, the California Privacy Protection Agency rules subcommittee provided a sample list of related questions concerning this during its December 16, 2022 board meeting.…

Continue Reading U.S. AI, IoT, CAV, and Privacy Legislative Update – Fourth Quarter 2022

This quarterly update summarizes key federal legislative and regulatory developments in the second quarter of 2022 related to artificial intelligence (“AI”), the Internet of Things, connected and automated vehicles (“CAVs”), and data privacy, and highlights a few particularly notable developments in U.S. state legislatures.  To summarize, in the second quarter of 2022, Congress and the Administration focused on addressing algorithmic bias and other AI-related risks and introduced a bipartisan federal privacy bill.

Artificial Intelligence

Federal lawmakers introduced legislation in the second quarter of 2022 aimed at addressing risks in the development and use of AI systems, in particular risks related to algorithmic bias and discrimination.  Senator Michael Bennet (D-CO) introduced the Digital Platform Commission Act of 2022 (S. 4201), which would empower a new federal agency, the Federal Digital Platform Commission, to develop regulations for online platforms that facilitate interactions between consumers, as well as between consumers and entities offering goods and services.  Regulations contemplated by the bill include requirements that algorithms used by online platforms “are fair, transparent, and without harmful, abusive, anticompetitive, or deceptive bias.”  Although this bill does not appear to have the support to be passed in this Congress, it is emblematic of the concerns in Congress that might later lead to legislation.

Additionally, the bipartisan American Data Privacy and Protection Act (H.R. 8152), introduced by a group of lawmakers led by Representative Frank Pallone (D-NJ-6), would require “large data holders” (defined as covered entities and service providers with over $250 million in gross annual revenue that collect, process, or transfer the covered data of over five million individuals or the sensitive covered data of over 200,000 individuals) to conduct “algorithm impact assessments” on algorithms that “may cause potential harm to an individual.”  These assessments would be required to provide, among other information, details about the design of the algorithm and the steps the entity is taking to mitigate harms to individuals.  Separately, developers of algorithms would be required to conduct “algorithm design evaluations” that evaluate the design, structure, and inputs of the algorithm.  The American Data Privacy and Protection Act is discussed in further detail in the Data Privacy section below.…

Continue Reading U.S. AI, IoT, CAV, and Data Privacy Legislative and Regulatory Update – Second Quarter 2022

A recent AAA study revealed that, although the pandemic has resulted in fewer cars on the road, traffic deaths have surged.  Speeding, alcohol-impairment, and reckless driving has caused the highest levels of crashes seen in decades, and the National Safety Council estimates a 9% increase in roadway fatalities from 2020.  Autonomous vehicles (AVs) have the…

On 27 October 2021, the U.S. Food and Drug Administration (“FDA”), Health Canada, and the United Kingdom’s Medicines and Healthcare products Regulatory Agency (“MHRA”) (together the “Regulators”) jointly published 10 guiding principles to inform the development of Good Machine Learning Practice (“GMLP”) for medical devices that use artificial intelligence and machine learning (“AI/ML”).

Purpose

AI…