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How Often Do You Think About the Roman Empire? Clarifying and Codifying the FTC\u27s Endorsement Guides\u27 Influencer Disclosure Guidelines
Full text linkTeaching Around Generative AI Plagiarism Risks
No full textMuch has been written and said about generative AI\u27s potential uses and misuses by lawyers and law students in the past year. This essay does not rehash the many ongoing discourses about whether, how, and to what extent generative AI (GenAI) can be used for and taught in legal writing courses. Rather, this essay is written under the assumption that, at least to some extent early on in the law school experience, some professors don\u27t want 1L legal writing students using GenAI to draft legal memoranda and briefs for them. As the American Bar Association\u27s Formal Ethics Opinion 512 warns, it is important to develop human lawyerly intelligence first before engaging in and being able to assess artificial intelligence. Despite the need for law students to develop that requisite lawyer intelligence required to meaningfully assess the value of any given AI-generated legal analysis, however, Lexis AI+ is now widely available to law students from their first month in school. That widespread access to GenAI may have its benefits, but not without also posing significant dangers of new AI-aided opportunities for plagiarism
Climate Proof Electricity
No full textThe devastating impacts of climate change make themselves known in the form of fires, floods, droughts, storms, extreme heat and cold, and worsening socioeconomic conditions around the globe. At the same time, the U.S. electricity system has never been more vulnerable to severe weather. Even as we embark on a national project to decarbonize the electricity system by 2035, the U.S. leads the developed world in power outages. These outages are in large part due to aging infrastructure, improperly weatherized systems, vegetation crashing down on transmission and distribution lines and—perhaps most devastating of all—wildfires caused by fallen power lines in places where drought and poor land management have made the surrounding area a veritable tinderbox. But even though the country is experiencing more frequent and intense bouts of extreme weather due to climate change, not enough is being done to make the electricity system more reliable or resilient.
This Article argues that climate change adaptation should be considered a separate category from both grid reliability and resilience. This is true for three reasons: first, regulatory approaches to reliability and resilience reflect old ideas and maintain utility economic interests; second, those same utility interests are partly responsible for the brittle state of the grid; and third, most existing proposals for climate adaptation will result in skyrocketing consumer energy bills, without any guarantee of effectiveness. By reframing climate adaptation as a separate category of risk and regulation, lawmakers can approach regional planning for disasters in creative ways and remove the cost of adaptation measures from regulated rates, recognizing that electricity systems are critical infrastructure. In making this argument, this Article engages with the current state of utility regulation to illustrate that there is no clear path to safe, reliable electricity in the climate change era without fundamentally changing how utilities and regulators engage with these issues
Layered Alignment
No full textMost artificial intelligence (AI) researchers now believe that AI represents an existential threat to humanity. The most dangerous threat posed by AI is an issue known as the alignment problem: the risk that a sufficiently intelligent and capable AI system could become misaligned with the goals and values of its human creators and instead pursue its own objectives to the detriment of humanity, including the possibility of extinction. The tension at the heart of the alignment problem is familiar to scholars of agency, contracts, and corporate law, though it goes by a different name: the principal-agent problem. In the traditional principal-agent problem, an agent has an incentive to act in a way that advances their own personal interests rather than the interests of the principal. This divergence of interests gives rise to agency costs that decrease the value of the agency relationship. To reduce agency costs, the principal and the agent use a variety of alignment mechanisms to realign their interests, such as contracts, control rights, and fiduciary duties. Many of these alignment mechanisms have analogs in the AI context. For example, AI agents respond to incentives built into their reward functions similarly to how human agents respond to performance-based compensation. One of the most important lessons from the literature on the principal-agent problem is that no one alignment mechanism can completely align the interests of the principal and the agent. Instead, parties in an agency relationship use a variety of alignment mechanisms to respond to different types of agency costs. For example, corporations use a mix of contracts, shareholder voting, board oversight, and fiduciary duties to align the interests of managers and shareholders. The same is true of the alignment problem-no single alignment mechanism can prevent AI misalignment. Yet despite the growing literature on AI safety, little attention has been given to the complex, interconnected nature of the alignment problem and the need for a multifaceted solution. This Article aims to fill this gap in the literature. Drawing on complexity theory, the Article argues for a layered approach to AI alignment in which a variety of alignment mechanisms are layered together to respond to different aspects of the alignment problem. Layered alignment has significant implications for the governance and regulation of AI. Implementing a layered approach to AI alignment will require a high level of coordination and cooperation between public and private AI stakeholders. This need for coordination and cooperation comes at a time when there is an escalating AI arms race between leading AI companies as well as between nations. To facilitate coordination between AI stakeholders, the Article calls for the creation of an international AI regulatory agency. It is time for us all to start working together-before it is too late
Please See the HR Robot on Your Way In: Navigating the Impact of AI in the Modern Workplace
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Human-Centered Regulation: The Approach of the European Union to the Digitalization of Employment Relations
No full textArtificial Intelligence and the Self-Represented Inventor
No full textLack of access to competent legal representation is pervasive throughout the justice system. Unfortunately, the patent system is no exception. Self-represented inventors are far less likely to obtain patents than those with legal representation. Increasing access to artificial intelligence (AI) can mitigate some of the disadvantages of self-representation, but the use of AI will also raise new challenges. To the extent that AI systems can help self-represented inventors, they can begin to address one of the underlying causes of the patent gap—lack of access to high quality legal services. Women and people of color hold fewer patents, in part, because of differential access to counsel. While AI is no substitute for legal representation, it can be incorporated into the patenting process in limited circumstances to help self-represented inventors.This Article describes the challenges self-represented inventors face in applying for patents and the implications of these difficulties for innovation as well as equitable access to the patent system. It sets forth the circumstances in which the use of AI would be most useful for self-represented inventors, when the risks outweigh the benefits, and when it may raise barriers to entry for self-represented inventors. This Article is also the first to identify how the use of AI by the Patent Office to classify and assign applications for examination may unintentionally discriminate against inventors. It concludes with recommendations for the Patent Office to improve upon its efforts to support self-represented inventors and cautions against relying on AI and other technology to satisfy the need for legal representation