This Article explores the current framework for recording property ownership and looks ahead to opportunities and challenges presented by emerging technologies. It further explores the potential applications of blockchain technology to real estate transfers, including tokenization and Non-Fungible Tokens (NFTs). First, this Article describes blockchain technology and some of its key characteristics, such as immutability and transparency, by analogizing to familiar legal processes in order to provide legal scholars with an accessible description of the often used, rarely defined term. It then provides an overview of the predominant land recording systems used worldwide, highlighting countries that have made great progress in implementing technology-based systems, as well as others that continue to face complex challenges unsolvable even with the most advanced technology. Finally, the Article explores opportunities to change the architecture of real estate transactions through tokenization and NFTs. Real estate, initially considered an ideal use case for tokenization, has proven to be a stubbornly illiquid asset, as the industry has been slow to adopt blockchain-based solutions. As the market evolves, tokenization will advance towards its promise of decreasing paperwork and bureaucracy, while increasing transparency. Perhaps of greater impact, tokenization provides a mechanism to divide real estate ownership into numerous fractional shares, making ownership more affordable for potential investors who would otherwise be priced out of the market. Thus, tokenization has potential to create accessible pathways to wealth creation and democratize access to an asset class formerly available only to the wealthiest investors. 

Consumer welfare has been a north star of the Federal Trade Commission (FTC), providing an organizing principle for diverse issues under the Commission’s dual competition and consumer protection missions and, specifically, a uniform ground for the law and economics of privacy matters and the tradeoffs that privacy policies entail. That organizing principle is relevant to broader policy debates about privacy, as legislative initiatives at the state and federal level continue apace, as do regulatory initiatives in foreign jurisdictions. Many such initiatives appear lacking in their economic foundations and over-simple in their attention to institutional design. This paper provides the first contemporary literature synthesis by former FTC staff that brings together the legal and economics literatures on privacy. Application of economic learning through the lens of the FTC’s jurisdiction sharpens the sense of the tradeoffs inherent in privacy policy ranging from policy goals to institutional design. We observe the following: (a) privacy is a complex subject, not a simple attribute of goods and services or a simple state of affairs; (b) privacy policies entail complex tradeoffs for and across individuals; (c) the economic literature finds diverse effects, both intended and unintended, of privacy policies, including on competition and innovation; (d) while there is diverse and growing evidence of the costs of privacy policies, countervailing benefits have been understudied and, as of yet, empirical evidence of such benefits remains slight; and (e) observed costs associated with omnibus policies suggest caution regarding one-size-fitsall regulation. 

This comprehensive Article explores the evolving role of artificial intelligence (AI) in the drug validation process within the U.S. Food and Drug Administration (FDA). By examining historical practices alongside emerging trends, the study assesses the legal implications and challenges associated with the integration of AI technology in pharmaceutical regulation. The exploration commences with an overview of traditional FDA validation techniques which provides a strong foundation for understanding the pre-AI regulatory framework. Through extensive analysis of case studies and empirical evidence, the Article establishes how AI enhances efficiency, accuracy, and decision-making processes in drug validation. Furthermore, the legal aspects section scrutinizes key issues encompassing transparency, cybersecurity, data protection, intellectual property rights, and regulatory decision-making, with particular emphasis on the principle of nondelegation. In addition to examining FDA advisories on AI implementation, the study suggests enhancements to optimize the application of AI within the existing regulatory framework. The conclusion emphasizes the significance of proactive measures in refining current legal structures and establishing comprehensive industry guidelines that effectively address the transformative potential of AI in drug validation. By elucidating the benefits and challenges of AI adoption, this research contributes to the ongoing discourse surrounding the appropriate utilization and regulation of AI in the field of drug validation. 



Online search engines are key providers of legal information. Their responses to people’s search queries can influence whether and how people make use of the legal system to deal with problems like evictions, domestic violence, debt collection, and natural disasters. This article presents a new research protocol to understand and evaluate what search engines are showing to people who are seeking out legal help. Using this novel search audit protocol, the article identifies concerning trends in search engines’ responses to people’s legal queries, including low-quality information, incorrect jurisdiction, and an absence of governmental or legal aid links. The article then proposes technical and policy strategies that may improve search engines’ role in people’s attempts to access the justice system online. In this research paper, we evaluate the search results that Google shows for common legal help queries to determine if the search engine shows jurisdiction-correct, issue-correct results to people seeking help. The paper raises concerns about how the current algorithm’s design connects people to key information when their rights, houses, jobs, security, and family are at risk. 

Why was the long-awaited federal privacy bill of 2022 so controversial among privacy advocates? The answer lies in one paragraph of the 143-page bill draft: the bill’s preemption provision. And that preemption provision is not limited to this now-dead bill: It is likely to reincarnate in future federal privacy legislation. This Article assesses the risks that such a preemption provision would create for consumer data privacy. First, the Article narrows the scope of concern to only the prevention of future state laws. Other concerns, like preempting current state laws or forcing privacy cases into federal court, are likely to be of little consequence. Next, the Article divides the danger of preventing future state privacy laws into two buckets: (1) preventing laws that patch one of the privacy theories in the bill; and (2) preventing laws that introduce new privacy theories. The Article then examines the risks in both buckets. For the first bucket, the Article first sketches a novel framework for evaluating how an implementation of a privacy theory can ossify, and then applies that framework to the two implementations of privacy theories in the 2022 bill. For the second bucket, the Article evaluates whether the bill’s preemption provision preempts different privacy theories. Ultimately, this Article does not reach a conclusion about whether a strong consumer data privacy law could be worth preemption. Rather, it merely clarifies the risks so that privacy advocates can unite for—or against—future federal privacy bills.