Science and Technology Law Commons^™

Regulating New Tech: Problems, Pathways, And People, Cary Coglianese

All Faculty Scholarship

New technologies bring with them many promises, but also a series of new problems. Even though these problems are new, they are not unlike the types of problems that regulators have long addressed in other contexts. The lessons from regulation in the past can thus guide regulatory efforts today. Regulators must focus on understanding the problems they seek to address and the causal pathways that lead to these problems. Then they must undertake efforts to shape the behavior of those in industry so that private sector managers focus on their technologies’ problems and take actions to interrupt the causal pathways. …

Enabling Science Fiction, Camilla A. Hrdy, Daniel H. Brean

Michigan Technology Law Review

Patent law promotes innovation by giving inventors 20-year-long exclusive rights to their inventions. To be patented, however, an invention must be “enabled,” meaning the inventor must describe it in enough detail to teach others how to make and use the invention at the time the patent is filed. When inventions are not enabled, like a perpetual motion machine or a time travel device, they are derided as “mere science fiction”—products of the human mind, or the daydreams of armchair scientists, that are not suitable for the patent system.

This Article argues that, in fact, the literary genre of science fiction …

From Automation To Autonomy: Legal And Ethical Responsibility Gaps In Artificial Intelligence Innovation, David Nersessian, Ruben Mancha

Michigan Technology Law Review

The increasing prominence of artificial intelligence (AI) systems in daily life and the evolving capacity of these systems to process data and act without human input raise important legal and ethical concerns. This article identifies three primary AI actors in the value chain (innovators, providers, and users) and three primary types of AI (automation, augmentation, and autonomy). It then considers responsibility in AI innovation from two perspectives: (i) strict liability claims arising out of the development, commercialization, and use of products with built-in AI capabilities (designated herein as “AI artifacts”); and (ii) an original research study on the ethical practices …

Race Cartels: How Constructor Collaboration Is Curbing Innovation In Formula 1, Chandler C. Gerard-Reimer

Vanderbilt Journal of Entertainment & Technology Law

Formula 1 is in the midst of a copycat scandal: technology has made it possible for teams to reverse engineer clones of competitors’ race cars. This is a less than ideal state of affairs for the championship series, which prides itself on being the pinnacle of motorsport and automotive innovation, thanks in large part to the cars’ rapid rate of technological advancement. In order to address this problem, the Fédération Internationale de l’Automobile (FIA), Formula 1’s governing body, must increase independent innovation efforts by amending the technical regulations to restrict the extent of presently allowed inter-team collaboration. Worried that the …

Technology And The (Re)Construction Of Law, Christian Sundquist

Articles

Innovative advancements in technology and artificial intelligence have created a unique opportunity to re-envision both legal education and the practice of law. The COVID-19 pandemic has accelerated the technological disruption of both legal education and practice, as remote work, “Zoom” client meetings, virtual teaching, and online dispute resolution have become increasingly normalized. This essay explores how technological innovations in the coronavirus era are facilitating radical changes to our traditional adversarial system, the practice of law, and the very meaning of “legal knowledge.” It concludes with suggestions on how to reform legal education to better prepare our students for the emerging …

Clearing Opacity Through Machine Learning, W. Nicholson Price Ii, Arti K. Rai

Articles

Artificial intelligence and machine learning represent powerful tools in many fields, ranging from criminal justice to human biology to climate change. Part of the power of these tools arises from their ability to make predictions and glean useful information about complex real-world systems without the need to understand the workings of those systems.