A New Approach to Measuring AI Bias in Human Resources Functions: Model Risk Management

This scholarship is the first to offer a commonsense, durable, implementable, and traceable solution to the problem of artificial intelligence bias in the human resources industry by proposing the application of the Model Risk Management structure that has proven successful in the financial services industry since the Great Recession of 2008. Such industry regulation will likely reduce the incidents of EEOC charges of violations of Title VII of the Civil Rights Act of 1964 and produce a more stable and safe regulatory environment for firms. Most importantly, the promise of an American workplace with less disparate treatment and disparate impact among employees on protected grounds will be achieved

The Sword and the Shield: The Benefits of Opinion Letters by Employment and Labor Agencies

Opinion letters are a highly beneficial vehicle for federal and state agencies to provide meaningful guidance for courts, businesses, workers, unions, trade groups, practitioners, advocacy groups, and the public at large. This Article examines the benefits and criticisms of opinion letters issued by employment and labor agencies. For more than seventy years the Department of Labor (“DOL”) provided employers, workers, and others with guidance regarding the interpretation and application of the Fair Labor Standards Act and related regulations through opinion letters. Indeed, opinion letters have been issued during both Democratic and Republican administrations. Unfortunately, in more recent years, opinion letters have become increasingly – and unnecessarily – politicized. Significantly, DOL under the Obama Administration stopped the practice of issuing opinion letters and thereby denied the public the opportunity for significant and timely guidance. Fortunately, in 2017, DOL announced that it would resume its practice of issuing opinion letters. At the time of this publication, it is unclear what the current administration will do

The Promise and The Peril: Artificial Intelligence and Employment Discrimination

Artificial intelligence (“AI”) is undeniably transforming the workplace, though many implications remain unknown. Employers increasingly rely on algorithms to determine who gets interviewed, hired, promoted, developed, disciplined, or fired. If appropriately designed and applied, AI promises to help workers find their most rewarding jobs, match companies with their most valuable and productive employees, and advance diversity, inclusion, and accessibility in the work- place. Notwithstanding its positive impacts, however, AI poses new perils for employment discrimination, especially when designed or used improperly. This Article examines the interaction between AI and federal employment antidiscrimination law. This Article explores the legal landscape including responses taken at the federal level, as well as state, local, and global legislation. Next, this Article examines a few legislative proposals designed to further regulate AI as well as several non-legislative proposals. In the absence of a comprehensive federal framework, this Article outlines and advances a deregulatory approach to using AI in the context of employment antidiscrimination that will maintain and spur further innovation. Against the backdrop of the deregulatory approach, this Article concludes by discussing best practices to guide employers in using AI for employment decisions

The Sword and the Shield: The Benefits of Opinion Letters by Employment and Labor Agencies

Opinion letters are a highly beneficial vehicle for federal and state agencies to provide meaningful guidance for courts, businesses, workers, unions, trade groups, practitioners, advocacy groups, and the public at large. This Article examines the benefits and criticisms of opinion letters issued by employment and labor agencies. For more than seventy years the Department of Labor (“DOL”) provided employers, workers, and others with guidance regarding the interpretation and application of the Fair Labor Standards Act and related regulations through opinion letters. Indeed, opinion letters have been issued during both Democratic and Republican administrations. Unfortunately, in more recent years, opinion letters have become increasingly – and unnecessarily – politicized. Significantly, DOL under the Obama Administration stopped the practice of issuing opinion letters and thereby denied the public the opportunity for significant and timely guidance. Fortunately, in 2017, DOL announced that it would resume its practice of issuing opinion letters. At the time of this publication, it is unclear what the current administration will do

The Promise and The Peril: Artificial Intelligence and Employment Discrimination

Artificial intelligence (“AI”) is undeniably transforming the workplace, though many implications remain unknown. Employers increasingly rely on algorithms to determine who gets interviewed, hired, promoted, developed, disciplined, or fired. If appropriately designed and applied, AI promises to help workers find their most rewarding jobs, match companies with their most valuable and productive employees, and advance diversity, inclusion, and accessibility in the work- place. Notwithstanding its positive impacts, however, AI poses new perils for employment discrimination, especially when designed or used improperly. This Article examines the interaction between AI and federal employment antidiscrimination law. This Article explores the legal landscape including responses taken at the federal level, as well as state, local, and global legislation. Next, this Article examines a few legislative proposals designed to further regulate AI as well as several non-legislative proposals. In the absence of a comprehensive federal framework, this Article outlines and advances a deregulatory approach to using AI in the context of employment antidiscrimination that will maintain and spur further innovation. Against the backdrop of the deregulatory approach, this Article concludes by discussing best practices to guide employers in using AI for employment decisions