Law Commons^™

Constructing Ai Speech, Margot E. Kaminski, Meg Leta Jones

Publications

Artificial Intelligence (AI) systems such as ChatGPT can now produce convincingly human speech, at scale. It is tempting to ask whether such AI-generated content “disrupts” the law. That, we claim, is the wrong question. It characterizes the law as inherently reactive, rather than proactive, and fails to reveal how what may look like “disruption” in one area of the law is business as usual in another. We challenge the prevailing notion that technology inherently disrupts law, proposing instead that law and technology co-construct each other in a dynamic interplay reflective of societal priorities and political power. This Essay instead deploys …

Do Ais Dream Of Electric Boards?, Robert J. Rhee

UF Law Faculty Publications

When artificial intelligence (“AI”) acquires self-awareness, agency, and unique intelligence, it will attain ontological personhood. Management of firms by AI would be technologically and economically feasible. The law could confer AI with the status of legal personhood, as it did with the personhood of traditional business firms in the past, thus dispensing with the need for inserting AI as property within the legal boundary of a firm. As a separate and distinct entity, AI could function independently as a manager in the way that legal or natural persons do today: i.e., AI as director, officer, partner, member, or manager. Such …

Two Ai Truths And A Lie, Woodrow Hartzog

Faculty Scholarship

Industry will take everything it can in developing Artificial Intelligence (AI) systems. We will get used to it. This will be done for our benefit. Two of these things are true and one of them is a lie. It is critical that lawmakers identify them correctly. In this Essay, I argue that no matter how AI systems develop, if lawmakers do not address the dynamics of dangerous extraction, harmful normalization, and adversarial self-dealing, then AI systems will likely be used to do more harm than good.

Given these inevitabilities, lawmakers will need to change their usual approach to regulating technology. …

The Great Scrape: The Clash Between Scraping And Privacy, Daniel J. Solove, Woodrow Hartzog

Faculty Scholarship

Artificial intelligence (AI) systems depend on massive quantities of data, often gathered by “scraping” – the automated extraction of large amounts of data from the internet. A great deal of scraped data is about people. This personal data provides the grist for AI tools such as facial recognition, deep fakes, and generative AI. Although scraping enables web searching, archival, and meaningful scientific research, scraping for AI can also be objectionable or even harmful to individuals and society.

Organizations are scraping at an escalating pace and scale, even though many privacy laws are seemingly incongruous with the practice. In this Article, …