Recent Articles in Volume 27, Number 1 (2024)
By April G. Dawson – Algorithmic governance is when algorithms, often in the form of AI, make decisions, predict outcomes, and manage resources in various aspects of governance. This approach can be applied in areas like public administration, legal systems, policy-making, and urban planning. Algorithmic adjudication involves using AI to assist in or decide legal disputes. This often includes the analysis of legal documents, case precedents, and relevant laws to provide recommendations or even final decisions. The AI models typically used in these emerging decision-making systems use traditionally trained AI systems on large data sets so the system can render a decision or prediction based on past practices. However, the decisions often perpetuate existing biases and can be difficult to explain. Algorithmic decision-making models using a constitutional AI framework (like Anthropic's LLM Claude) may produce results that are more explainable and aligned with societal values. The constitutional AI framework integrates core legal and ethical standards directly into the algorithm’s design and operation, ensuring decisions are made with considerations for fairness, equality, and justice. []
By Nicole Morris – Over the past several years, startups that once seemed destined for greatness have failed or collapsed because of fraud committed by the founders. Most notable are the Theranos and FTX business collapses, which culminated in the convictions of two infamous entrepreneurs, Elizabeth Holmes and Sam Bankman-Fired, respectively. Startup innovators are not alone when it comes to morally dubious behavior. According to Retraction Watch, nearly 5000 papers published in science & engineering journals were retracted in 2022. Research misconduct allegations eventually led to the resignation of Stanford University President Marc Tessier-Lavigne in July 2023. The research scandal at Stanford received lots of public attention. Absent such public scrutiny, however, organizations are slow to act on allegations of research falsification. This raises several important questions: are these occurrences becoming more frequent? What governance frameworks are available to effectively detect and prevent such misconduct and fraudulent behavior? []
By William H. Widen and Philip Koopman – Abstract
This paper explains how the law ought to assign liability for automated vehicle accidents by providing an example of a proposed statute. We advocate for the creation of the legal fiction of a “Computer Driver,” which can have negligence liability, anytime a court or jury determines that the Computer Driver’s behavior failed to imitate or exceed the level of care we would expect of an attentive and unimpaired Human Driver in similar circumstances. We then use this concept to explain how to determine contributory negligence and comparative fault when control of a vehicle is transferred from a Computer Driver to a Human Driver by specifying a portion of time during the take-over transition period in which the Human Driver cannot have contributory negligence or comparative fault as a matter of law. We have proposed and defended these views in contemporaneous traditional law review articles, but to achieve the needed regulatory reform, our suggestions must be presented in a form containing proposed statutory language for adoption by a legislature. []