Geslevich Packin on Paywalling Humans

Nizan Geslevich Packin (U Haifa Law; CUNY School of Business; CUNY Law) has posted “Paywalling Humans” (Theoretical Inquiries in Law, Forthcoming) on SSRN. Here is the abstract:

This Article addresses the trend of relegating human customer service to a premium-service in the wake of advancing automation and AI technologies, underscoring the ethical, social, and legal challenges. It emphasizes the need for keeping human interaction accessible and affordable for all, particularly for vulnerable populations, amidst this digital shift. The convenience and efficiency of automated systems such as IVR, chatbots, and virtual-agents have transformed customer support, introducing significant cultural and moral challenges, notably the erosion of personal touch and empathy vital for customer satisfaction and loyalty.

The Article explores customer service automation’s evolution and its impact on workforce dynamics, consumers, and the quality of service. It highlights the hidden costs of diminished human interaction, particularly its adverse effects on disadvantaged, elderly, and disabled groups. Through case studies and examples, it showcases this trend’s negative consequences. Further, it discusses the Human-In-The-Loop concept, advocating for an approach that enhances customer experience with automation without sacrificing human interaction. It explores the considerations surrounding automated customer service, emphasizing the enforcement roles of agencies like the Federal Trade Commission (FTC) and Consumer Financial Protection Bureau (CFPB) in upholding consumer protection laws, and the need for regulations to ensure fairness, transparency, accessibility, and consent.

Concluding, the Article calls for technology to augment rather than replace human service, stressing the importance of clear regulations on the affordability of human interaction in customer support. It urges policymakers and businesses to ensure that automation does not marginalize those that need human assistance, advocating for equitable access to services.

Arango on A Legislative Foundation for Foundation Models

Steven Arango (George Washington U Law) has posted “A Legislative Foundation for Foundation Models” on SSRN. Here is the abstract:

Artificial Intelligence (AI) is not some futuristic technology—it exists in everyday products like your Uber app or the Siri on your nightstand. Its development is meteoric; foundation models are the latest AI advancement: these models are a type of AI that is able to not only produce a range of products but also be integrated into other AI models. This AI Swiss-army knife is proving to be an incredible asset for economic development and national security. But, like other world-altering technology, there is a pernicious side of foundation models. Their flexibility offers adversaries, such as state and non-state actors, the ability to level the global playing field and shift the global order in terms of defensive capabilities. As the conflict in Ukraine has shown, AI is not the future of war—it is the present. Four-hundred-dollar AI fueled drones have been used to disable and, at times, destroy million-dollar war-machines.

To address this Jekyll and Hyde potential of foundation models, President Joe Biden issued Executive Order (EO) 14110. But this EO is the starting-gun, not the end of the race. In fact, EO 14110 even admits that that more understanding and information is required for this nascent technology. To properly legislate foundation models, Congress will need to act. Legislation, however, must be measured and thoughtful with a burgeoning technology like foundation models. Otherwise, innovation will be stamped out, giving way to inflexible, misguided laws.

This paper offers a path forward to balance the scale between innovation and legislation. This paper first provides an outline of President Biden’s EO, with a focus on Section 4.6. It then turns the underlying technology of foundation models, explaining how labeling foundation models as “open” versus “closed” creates a false dichotomy. Next, the paper compares proposed U.S. legislation to the EU’s recent approach for legislating foundation models. National security implications of AI are then outlined, providing real-world examples of AI usage from the current conflict in Ukraine and across the globe. This paper concludes with recommendations on how to legislate foundation models. By balancing legislation with innovation, this paper develops a novel approach to regulating foundation models—the “fastest-growing consumer technology in U.S. history”.

Soh on NLP in the Legal World

Jerrold Soh (Singapore Management University Law) has posted “NLP in the Legal World” on SSRN. Here is the abstract:

This talk situates the rising field of NLLP in the context of legal scholarship and emerging trends in legal AI practice and regulation. It centrally suggests that, as NLP’s domain of competence expands, it would have to undergo, and is in several ways already undergoing, a fundamental transformation we might refer to as “growing up”. In particular, to succeed in the legal world, NLP technology has to contend with three key aspects of adulthood: new attitudes, new consequences, and new responsibilities. Lawyers have gone from complete AI skepticism to actively exploring use cases. Encroaching into fields like medicine, law, and finance means technologists cannot avoid dealing with difficult questions around protecting life, liberty, and money. An entire new AI rulebook is currently being written by regulators and courts around the world. Against this backdrop, the talk examines how NLLP relates to existing inquiries in computational law, AI and Law, and computational/empirical legal studies and identifies opportunities for inter-field discourse. It concludes by identifying the unique role that NLLP researchers can play in the increasingly controversial (and seemingly, decreasingly scientific) global debate on the use and regulation of large language models.