New Federal and State Regulation of Corporate AI Systems: Mitigating Bias in Automated Decision-Making
National Artificial Intelligence Initiative Act, Proposed Algorithmic Accountability Act, and the Algorithmic Fairness Act
Course Details
- smart_display Format
On-Demand
- signal_cellular_alt Difficulty Level
- work Practice Area
Corporate Law
- event Date
Thursday, August 11, 2022
- schedule Time
1:00 p.m. ET./10:00 a.m. PT
- timer Program Length
90 minutes
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This 90-minute webinar is eligible in most states for 1.5 CLE credits.
This CLE course will address the increasing use of artificial intelligence (AI) and algorithms in decision-making processes by businesses. The panel will discuss the recently enacted National Artificial Intelligence Act and how it creates new initiatives, committees, and workflows on AI. The panel will advise companies on best practices to respond to and comply with the emerging regulatory environment and how to operate in the absence of clear guidance and standards.
Ms. Mithal is an internationally recognized expert on privacy and data security, having led the Federal Trade Commission’s Division of Privacy and Identity Protection prior to joining the firm. In this capacity, she oversaw a team of 40 lawyers responsible for the enforcement of privacy and security laws and the development of policy positions in emerging areas such as artificial intelligence, facial recognition, biometrics, and connected cars, as well as health privacy, children’s privacy, ransomware, and the intersection of privacy and competition. Ms. Mithal was also responsible for enforcing the Fair Credit Reporting and Gramm-Leach-Bliley Act Safeguards Rule. She led the negotiation of numerous privacy and data security settlements and managed the first litigated FTC decisions on cybersecurity issues. She also worked with congressional staff on federal privacy legislation, with state attorney general offices on joint investigations, and with other federal and international agencies on a variety of initiatives.
Ms. Friedman focuses her practice on structuring and negotiating large scale strategic sourcing and technology transactions, concentrating on global and domestic outsourcings in the areas of information technology, software development and maintenance, and business process outsourcing. Her practice also includes drafting and negotiating transition services agreements in connection with M&A transactions, software licensing, integration and implementation transactions, hosting agreements, distribution agreements, related corporate transactions, and handling issues relating to data privacy, data security and IP matters. Ms. Friedman is often called upon by multinational companies for the negotiation of complex Internet of Things (IoT) contracts, big data, Artificial Intelligence (AI) and other disruptive technology transactions as they evolve or develop novel solutions to emerging issues. Her experience spans all phases of a transaction, including the RFP stage, and contract development, execution, implementation and maintenance.
Mr. Hedges is a member of the firm’s Litigation and Dispute Resolution Practice Group. He has extensive experience in e-discovery and in the management of complex litigation and has served as a special master, arbitrator and mediator. He also consults on management and discovery of electronically stored information (ESI). Mr. Hedges is a frequent author and lecturer on many legal topics.
More businesses are using AI and algorithms to drive decision-making processes. Congress passed the National Artificial Intelligence Initiative Act, which creates numerous new initiatives, committees, and workflows on AI, with the goal of preparing the federal workforce, conducting and funding research, and identifying and mitigating risks, particularly the potential for unintended bias.
In the absence of regulatory guidance and standards, industry and legal stakeholders are struggling with how to address concerns about algorithmic fairness, leading to increased regulatory and reputational risk. Attorneys must understand the risks related to automated decision-making and stay ahead of the regulatory landscape. However, legal is not the only stakeholder--engineers, economists, data scientists, ethicists, and others might spot different issues. Creating diverse teams with different viewpoints and life experiences is essential to any effort to mitigate bias.
One cause of bias might be a lack of diverse representation in the data set used to train the algorithm. But even if the data set is diverse, it might replicate historical patterns of bias. Counsel needs to develop and document programs, policies, and procedures based on questioning what the AI is determining and what data errors may be created.
Counsel should consider effective ways to test the algorithm before deploying it and consider having periodic audits to ensure biased outcomes are not an unintended result.
Listen as our expert panel discusses the National Artificial Intelligence Initiative Act and other proposed legislation, how counsel with other stakeholders can develop and alter an algorithm as necessary to address unintended bias, and what the future of AI in business decision-making may entail.
- Artificial intelligence in business decisions
- National Artificial Intelligence Initiative Act
- Proposed legislation
- Algorithmic Accountability Act
- Algorithmic Fairness Act
- State regulation and privacy laws
- Creating algorithms without bias
- Cross-discipline teams
- Team education
- Evaluating algorithms for appropriate solutions
- Question algorithm results and develop procedures
- Preapplication testing
- State and local regulations on AI
- Best practices
- Periodic audits
The panel will address these and other key topics:
- How the National Artificial Intelligence Initiative Act and other proposed legislation may affect corporate use of AI?
- How can counsel work with others to develop an algorithm?
- What should counsel and other stakeholders do to address unintended bias?
- What are the best practices when advising a company using AI in decision-making processes?
