AI, on the Law of the Elephant: Toward Understanding Artificial Intelligence

Abstract

Machine learning and other artificial intelligence (“AI”) systems are changing our world in profound, exponentially rapid, and likely irreversible ways. Although AI may be harnessed for great good, it is capable of and is doing great harm at scale to people, communities, societies, and democratic institutions. The dearth of AI governance leaves unchecked AI’s potentially existential risks. Whether sounding urgent alarm or merely jumping on the bandwagon, law scholars, law students, and lawyers at bar are contributing volumes of AI policy and legislative proposals, commentaries, doctrinal theories, and calls to corporate and international organizations for ethical AI leadership.

Profound concerns exist about AI and the actual and potential crises of societal, democratic, and individual harm that it causes or may cause in future. Compounding those deep concerns is lawyers’ lack of sufficient AI knowledge and technological competence, despite ethical mandates for diligence and competence. As a result, legal discussions and law and policy recommendations may be fundamentally flawed because they are constructed upon erroneous, uninformed, or misconceived understandings of AI technologies, inputs, and processes.

Keywords: artificial intelligence, law, machine learning, Algorithm, Statistical model, Governance, Ethics, Automated Decision, AI risk, Predictive system, Big data, Supervised learning, Neural network, Competency, Ethics, Taxonomy, Definition, Patent, Synthetic data, Imputed data, Derived data