Law Commons^™

The Role Of Ethical Principles In Ai Startups, James Bessen, Stephen Michael Impink, Robert Seamans

Faculty Scholarship

Do high-tech startups benefit from developing more ethical AI? AI startups implement policies and take actions to manage ethical issues associated with data collection, storage, and usage and adapt to the norms of their industry. This paper describes these startups' ethics-related actions, including ethical AI policy adoption, and examines how these actions relate to startup performance. We find that merely adopting an ethical AI policy (i.e., a less costly signal) does not relate to increased performance. However, there is evidence that investors reward startups that take more costly preventative pro-ethics actions, like seeking expert guidance, training employees about unconscious bias, …

Using Artificial Intelligence In The Law Review Submissions Process, Brenda M. Simon

Faculty Scholarship

The use of artificial intelligence to help editors examine law review submissions may provide a way to improve an overburdened system. This Article is the first to explore the promise and pitfalls of using artificial intelligence in the law review submissions process. Technology-assisted review of submissions offers many possible benefits. It can simplify preemption checks, prevent plagiarism, detect failure to comply with formatting requirements, and identify missing citations. These efficiencies may allow editors to address serious flaws in the current selection process, including the use of heuristics that may result in discriminatory outcomes and dependence on lower-ranked journals to conduct …

Legislating Data Loyalty, Woodrow Hartzog, Neil Richards

Faculty Scholarship

Lawmakers looking to embolden privacy law have begun to consider imposing duties of loyalty on organizations trusted with people’s data and online experiences. The idea behind loyalty is simple: organizations should not process data or design technologies that conflict with the best interests of trusting parties. But the logistics and implementation of data loyalty need to be developed if the concept is going to be capable of moving privacy law beyond its “notice and consent” roots to confront people’s vulnerabilities in their relationship with powerful data collectors.

In this short Essay, we propose a model for legislating data loyalty. Our …

Data-Informed Duties In Ai Development, Frank A. Pasquale

Faculty Scholarship

Law should help direct—and not merely constrain—the development of artificial intelligence (AI). One path to influence is the development of standards of care both supplemented and informed by rigorous regulatory guidance. Such standards are particularly important given the potential for inaccurate and inappropriate data to contaminate machine learning. Firms relying on faulty data can be required to compensate those harmed by that data use—and should be subject to punitive damages when such use is repeated or willful. Regulatory standards for data collection, analysis, use, and stewardship can inform and complement generalist judges. Such regulation will not only provide guidance to …

The Inadequate, Invaluable Fair Information Practices, Woodrow Hartzog

Faculty Scholarship

For the past thirty years, the general advice for those seeking to collect, use, and share people’s personal data in a responsible way was relatively straightforward: follow the fair information practices, often called the “FIPs.” These general guidelines were designed to ensure that data processors are accountable for their actions and that data subjects are safe, secure, and endowed with control over their personal information. The FIPs have proven remarkably sturdy against the backdrop of near-constant technological change. Yet in the age of social media, big data, and artificial intelligence, the FIPs have been pushed to their breaking point. We …