Does Private Equity Create Wealth? The Effects of Private Equity and Derivatives on Corporate Governance
The authors would like to thank Harry DeAngelo, Todd Henderson, James Spindler, Robert Thompson, Charles Whitehead, the Harvard Law School Faculty Workshop, the University of Pennsylvania Law School Business Law Scholarship Workshop, and the participants of The University of Chicago Symposium, The Going-private Phenomenon: Causes and Implications, for their helpful comments.
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Private equity has reaped large rewards in recent years. We claim that one major reason for this success is due to the corporate governance advantages of private equity over those of the public corporation. We argue that the development and trade of substantial derivative contracts have significantly weakened the governance of public corporations and have created a need for financially sophisticated directors and much closer supervision of management. The private-equity model delivers these benefits and allows corporations to be better governed, creating large wealth gains for investors.
We would like to thank the participants of the How AI Will Change the Law Symposium, cohosted by the Coase-Sandor Institute, the University of Chicago Law Review Online, and Oxford Business Law Blog, for their helpful comments.
We would like to thank the participants of the How AI Will Change the Law Symposium, cohosted by the Coase-Sandor Institute, the University of Chicago Law Review Online, and Oxford Business Law Blog, for their helpful comments.
Artificial intelligence (AI) has the potential to alter the interpretation of the duties of care, skill, and diligence. As these duties form the foundation for the BJR and equivalent provisions, the development of AI is also expected to impact the BJR. There is a broadening importance, in an increasingly data-driven business environment, of the requirement to gather sufficient information before making a decision and to use information in a valid manner. Changes are both quantitative (how much information to collect) and qualitative (which types of information to collect). The changes also relate to the methods of decision-making, including the role of measures and statistics over intuition.
We would like to thank the participants of the How AI Will Change the Law Symposium, cohosted by the Coase-Sandor Institute, the University of Chicago Law Review Online, and Oxford Business Law Blog, for their helpful comments.
We would like to thank the participants of the How AI Will Change the Law Symposium, cohosted by the Coase-Sandor Institute, the University of Chicago Law Review Online, and Oxford Business Law Blog, for their helpful comments.
Artificial intelligence (AI) has the potential to alter the interpretation of the duties of care, skill, and diligence. As these duties form the foundation for the BJR and equivalent provisions, the development of AI is also expected to impact the BJR. There is a broadening importance, in an increasingly data-driven business environment, of the requirement to gather sufficient information before making a decision and to use information in a valid manner. Changes are both quantitative (how much information to collect) and qualitative (which types of information to collect). The changes also relate to the methods of decision-making, including the role of measures and statistics over intuition.
She graduated from Tel-Aviv University and Harvard Law School. Named as one of the most cited legal scholars in the United States, and specifically the most cited scholar in employment law and one of the most cited in law and technology, she is influential in her field. Professor Lobel has served on President Obama’s policy team on innovation and labor market competition, has advised the Federal Trade Commission (FTC), and has published multiple books to critical acclaim. Her latest book, The Equality Machine, is an Economist Best Book of the Year.
This Essay argues for the development of more robust—and balanced—law that focuses not only on the risks, but also the potential, that AI brings. In turn, it argues that there is a need to develop a framework for laws and policies that incentivize and, at times, mandate transitions to AI-based automation. Automation rights—the right to demand and the duty to deploy AI-based technology when it outperforms human-based action—should become part of the legal landscape. A rational analysis of the costs and benefits of AI deployment would suggest that certain high-stakes circumstances compel automation because of the high costs and risks of not adopting the best available technologies. Inevitably, the rapid advancements in machine learning will mean that law soon must embrace AI; accelerate deployment; and, under certain circumstances, prohibit human intervention as a matter of fairness, welfare, and justice.