Menesh S. Patel (University of California, Davis – School of Law) has posted “Fraud on the Crypto Market” (Harvard Journal of Law & Technology, Forthcoming (2023)) on SSRN. Here is the abstract:
Crypto asset trading markets are booming. Traders in the United States presently can buy and sell hundreds of crypto assets on dozens of crypto exchanges, and this trading is expected to further intensify in the coming years. While investors now increasingly turn to crypto asset trading for portfolio appreciation and diversification, the popularization of secondary crypto asset trading risks significant investor harm through increased incidents of fraud. False or misleading statements by crypto asset sponsors or third parties have the prospect of financially impairing traders in crypto asset trading markets, including everyday traders who are ill-equipped to sustain significant investment losses.
As traders seek judicial redress for their fraud-related injuries, courts will be asked to make doctrinal determinations that will be pivotal to injured traders’ ability to recover. A primary issue that courts will need to confront is whether crypto asset traders can avail themselves of fraud on the market in connection with fraud claims asserted under SEC Rule 10b-5 or CFTC Rule 180.1. This Article addresses that question and has as its intended audience not just academics, but also courts, practitioners, and market participants.
The Article shows that as a doctrinal matter fraud on the market is available in securities or commodities fraud cases involving crypto assets that trade on crypto exchanges, especially in light of the Supreme Court’s decision in Halliburton II, which resolved that fraud on the market is predicated on just a generalized notion of market efficiency, rather than a strict financial economic notion of efficiency. Drawing on how courts apply the doctrine to fraud cases involving stock transactions, the Article articulates a framework for how fraud on the market should be applied to the crypto asset context and explores methodological issues relevant to the framework’s application in a given crypto asset case.
Shelly Kreiczer-Levy has posted “Reclaiming Feudalism for the Technological Era” (Cardozo Arts & Entertainment Law Journal, (Forthcoming 2023)) on SSRN. Here is the abstract:
Personal property law has a blind spot when it comes to technological items, as they do not account for the long-term, unequal property collaboration that is required in operating these assets. I argue that we can learn from the intellectual legal history of feudalism about the vulnerabilities produced by property collaborations between unequal parties.
Owners of robots as AI objects (e.g., autonomous vehicles, drones, and robot-chefs) have limited control over their property. Users own the physical product, but they only have a license to use the software. As per the terms of the license, the manufacturer retains control over many aspects of the object’s ongoing use. Although this structure is criticized in the literature, none of the critics points out the need to rethink the current structure of these rights. AI products have autonomous decision-making capabilities that make their actions hard to foresee and require periodical updates to secure their safety and quality. This Article is the first to offer a property model for technological property collaborations.
The inspiration for this property model lies in the historical form of feudal property. Feudalism is often evoked in the law and technology literature to warn us against the power that large corporations hold over users. While these concerns are valuable, I maintain that feudal property has important potential to identify and address the unique vulnerabilities in these property collaborations. First, the duties of users and manufacturers in robots as well as feudal property are not connected to the use and function of the asset. Second, the property can only be used with the collaboration of the manufacturer or lord.
Following this analysis, this Article offers two models for property collaborations in AI products: a moderate, connection model and a more radical, competition model. The connection model adopts the basic feudal concept of split ownership accompanied by a specifically tailored relational role and applies it to robots with the necessary changes. The competition model seeks to create a market where different manufacturers compete for the development value of the robot. The proposed models have several normative implications, including invalidating limitations on use, justifying a right to repair and data portability, and clarifying the copyright protection of AI-produced creative work.