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Like a Good Neighbor, State Courts Are There: The Case for Remanding COVID-19 Business Interruption Actions to State Court

Gabriel L. Johnson

Volume 31

Issue 2

PUBLISHED

Spring 2025

Abstract

Following the emergence of COVID-19 and resulting civil orders seeking to stop its spread, many businesses filed claims with their insurance providers for “business interruption” coverage, a type of insurance intended to compensate businesses for income lost during a temporary forced closure. When insurance companies roundly denied these claims, many small-business owners filed lawsuits in state courts. Insurance company defendants largely removed these cases to federal courts, and businessowner plaintiffs filed to remand back to state court. In one consolidated appeal heard by the Third Circuit, DiAnoia’s Eatery, LLC v. Motorist Mutual Insurance Co., businessowner plaintiffs seeking remand to state court argued these claims involved novel state law issues. Although the district courts agreed, the Third Circuit reversed, and held federal courts in Pennsylvania and New Jersey could not use their statutorily granted discretion to remand the actions to state court. This Note asserts the Third Circuit’s holding in DiAnoia’s Eatery, LLC misinterpreted circuit precedent which, properly applied, permitted the district courts to remand the claims to state court under the Declaratory Judgment Act. But the Note also argues that DiAnoia’s Eatery, LLC is merely one example of a trend seen nationwide in which circuit courts issued decisions on this issue prior to the ultimate authority—state courts—ruling. It explains how federal courts instead turned inwards, relying not on binding state court precedent but rather on other federal court decisions; an approach which displaced state courts’ proper role, and risked mass federal reversal by the U.S. Supreme Court. This Note provides an important building block in a field of scholarship which has generally, thus far, criticized federal courts’ initial near-monopoly on business interruption claims, the influence they exerted on the development of this caselaw, and finally, the merits of their dismissal of COVID19 business interruption claims. This Note goes further, arguing that in addition to those concerns, federal courts were the improper forum for these suits, and that remanding them to state courts under the Declaratory Judgment Act was, and is, the best approach.

E/Insuring the AI Age: Empirical Insights into Artificial Intelligence Liability Policies

ANAT LIOR

Volume 31

Issue 2

PUBLISHED

Spring 2025

Abstract

Insurance represents an important but underappreciated part of our lives. Both individuals and corporations gain from purchasing coverage from insurers to manage and hedge their risks. It is a necessary mechanism in modern society to support innovation while ensuring that its unavoidable victims will be compensated. The innovation of emerging technologies alters the existing risk landscape, challenging insurance companies, innovators, and individuals’ ability to manage their risks. The current emerging technology of Artificial Intelligence (AI) significantly emphasizes this trend. Insurance companies are grappling with the notion of AI. They are exploring different traditional and novel insurance products that they can offer both corporations and users to manage the risks associated with AI. In return, the market for AI coverage presents unprecedented growth and revenue opportunities. Insurance is set to play a pivotal role in AI’s development and distribution, actively shaping risk mitigation strategies and regulatory frameworks for AI users and companies. This is not just an academic gap — it is a pressing regulatory issue with tangible, real-world implications. This paper examines the intersection of AI and insurance from an empirical perspective. It presents empirical findings from the insurance sector, delving into the operational dynamics of liability policies covering risks associated with AI. Through in-depth interviews with key industry stakeholders, including underwriters, brokers, and AI users navigating the uncharted risks AI presents, this paper offers a deeper understanding of three crucial questions. First, is there a need for a specialized AI insurance policy, and how should underwriting adapt to AI’s unpredictable risks? Second, do existing liability policies, such as cyber insurance and product liability, adequately cover AI-related risks, or do they leave dangerous gaps that could expose both insurers and policyholders (known as “silent AI”)? Third, what role should legislators play in crafting policies that equitably manage AI risks for all stakeholders? The findings reveal a rapidly evolving insurance market where underwriters, brokers, and AI users recognize the deep connection between anticipated AI regulation, substantial financial penalties, and the emergence of an AI-specific insurance sector. Bridging theory with practical applications is pivotal in academic and theoretical writing. This holds particular significance in the insurance realm, impacting AI users and innovators. Collaboration is necessary between those who discuss insurance for AI from a legal perspective and those who underwrite AI policies from an actuarial perspective, as new AI regulations and litigation are likely to create a new insurance
market for AI.