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Just Look at the Map: Bounding Environmental Review of Housing Development in California
No full textCalifornia faces a dire housing crisis. California’s land-use regulatory system remains a key driver of this crisis. State law grants local governments broad power to craft their own regulations on how to review and approve housing development. Though state law may limit a locality’s ability to outright deny some types of housing development, local governments can and do use creative ways to stall approvals or functionally deny housing by making it infeasible to develop. One such strategy is to demand more intensive environmental review of new housing projects under the California Environmental Quality Act (CEQA) than what state law requires. More intensive environmental review can create substantial delay and uncertainty, increasing the costs for the construction of new housing. Although the state has made many efforts to streamline the process of both local land-use regulation and CEQA review, delays and uncertainty remain.
We propose that the state address this ongoing problem by (1) issuing an authoritative map of urban “infill priority areas” (IPAs) where new housing is expected to provide net social and environmental benefits, and (2) limiting the scope of environmental review, within the IPAs, to environmental impacts identified by the city or members of the public within a brief temporal window and demonstrated by the proponent of environmental review to be significant. In effect, the law would presume no impact from new housing within an IPA unless significant impacts are quickly and unambiguously identified. We also propose enforcement mechanisms. New infill housing reduces carbon emissions, exposure to wildfire risk, and threats to habitat. Environmental review should be calibrated accordingly
AI & Antitrust: The Algorithm Made Me Do It
No full textAs the dawn of artificial intelligence (“AI”) rises rapidly, competition authorities should contemplate the potential for hazy days ahead. Undoubtedly, AI’s already ubiquitous presence offers exciting possibilities, from enhancing efficiency, to leveling the playing field for non-native speakers,to enabling scientific discovery.Despite these breathtaking advancements, however, recent data from the Pew Research Center reveal that only 15% of adults surveyed were “more excited than concerned about the increasing use of AI in daily life,” with 46% expressing “an equal mix of concern and excitement.”
Policymakers also manifest concerns about AI, exemplified by the extent to which government actors are racing to pass laws, benchmarks, and guidelines to regulate the development and use of AI technology.And in the intellectual property realm, courts have seen a wave of copyright cases brought by individual and business content creators over the use of copyrighted work in the training of generative AI tools.
Generative AI and AI more broadly are not only making waves in the courtroom; these waves have reached legal academia as well. Although there is an abundance of literature focused on AI and its effects on intellectual property (“IP”) law,IP’s antagonistic cousin, competition law, is gently coming to the fore.Emerging competition law literature has begun to explore effects of using algorithms on competition. Moreover, recent cases increasingly assert antitrust claims against algorithmic collusion.
This paper seeks to add to this emerging antitrust and AI scholarship. As AI becomes a more accurate and skillful tool, it could conceivably lead to more anticompetitive hub-and-spoke arrangements that current competition laws may not be fully equipped to evaluate. Building on Feldman’s previous work concerning the pharmaceutical supply chain and competition-related issues raised by algorithms,this paper examines the pharmaceutical supply chain as an example of an industry with concentrated intermediaries. We argue that the widespread adoption of increasingly powerful algorithms will exacerbate the susceptibility of such industries to anticompetitive effects. Specifically, as intermediaries become equipped with more accurate and skillful AI-driven algorithms, the intermediaries will become better facilitators of tacit collusion. Moreover, a concentrated intermediary level enhances that power.
Finally, we outline some thoughts on mechanisms that have the potential to curtail such collusion. Inspired by anti-money laundering compliance schemes adopted around the world, we propose designing a model for anti-collusion compliance, and we outline the crucial characteristics that such a model should possess
Mass Surveillance as Racialized Control
No full textThis Article examines how the expanded use of pretrial GPS surveillance is radically changing the presumption of innocence by implicating punitive measures absent constitutional protections and amplifying the racial disparities in our criminal justice system. Largely viewed as a substitution for physical detention and therefore a less onerous intrusion on a defendant’s liberty, pretrial GPS surveillance erodes fundamental liberties under the guise of criminal justice regulation. These highly racialized but invisible repercussions include harms to physical and psychological health, freedom of movement, privacy, and future economic self-determination. I argue that, in light of these substantial harms, courts must examine how they evaluate technological surveillance, affording defendants substantive and procedural due process protections where there currently are none
The Uncertain Future of Restorative Justice: Anti-Woke Legislation, Retrenchment and Politics of the Right
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