Western societies are marked by diverse and extensive biases and inequality that are unavoidably embedded in the data used to train machine learning. Algorithms trained on biased data will, without intervention, produce biased outcomes and increase the inequality experienced by historically disadvantaged groups. Recognising this problem, much work has emerged in recent years to test for bias in machine learning and AI systems using various fairness and bias metrics. Often these metrics address technical bias but ignore the underlying causes of inequality. In this paper we make three contributions. First, we assess the compatibility of fairness metrics used in machine learning against the aims and purpose of EU non-discrimination law. We show that the fundamental aim of the law is not only to prevent ongoing discrimination, but also to change society, policies, and practices to ‘level the playing field’ and achieve substantive rather than merely formal equality. Based on this, we then propose a novel classification scheme for fairness metrics in machine learning based on how they handle pre-existing bias and thus align with the aims of non-discrimination law. Specifically, we distinguish between ‘bias preserving’ and ‘bias transforming’ fairness metrics. Our classification system is intended to bridge the gap between non-discrimination law and decisions around how to measure fairness in machine learning and AI in practice. Finally, we show that the legal need for justification in cases of indirect discrimination can impose additional obligations on developers, deployers, and users that choose to use bias preserving fairness metrics when making decisions about individuals because they can give rise to prima facie discrimination. To achieve substantive equality in practice, and thus meet the aims of the law, we instead recommend using bias transforming metrics. To conclude, we provide concrete recommendations including a user-friendly checklist for choosing the most appropriate fairness metric for uses of machine learning and AI under EU non-discrimination law.
The shift towards the use of algorithms in business has transformed merchant–consumer interactions. Products and services are increasingly tailored for consumers through algorithms that collect and analyze vast amounts of data from interconnected devices, digital platforms, and social networks. While traditionally merchants and marketeers have utilized market segmentation, customer demographic profiles, and statistical approaches, the exponential increase in consumer data and computing power enables them to develop and implement algorithmic techniques that change consumer markets and society as a whole. Algorithms enable targeting of consumers more effectively, in real-time, and with high predictive accuracy in pricing and profiling strategies. In so doing, algorithms raise new theoretical considerations on information asymmetry and power imbalances in merchant–consumer interactions and multiply existing biases and discrimination or create new ones in society. Against this backdrop of the concentration of algorithmic decision-making in merchants, the traditional understanding of consumer protection is overdue for change, and normative debate about fairness, accountability, and transparency and interpretive considerations for non-discrimination is necessary. The theory that notice and choice in data protection laws and consumer protection laws are sufficient in an algorithmic era is inadequate, and countervailing consumer empowerment is necessary to balance the power between merchants and consumers. While legislative activity and regulation have conceivably increased consumer-empowerment, such measures may provide a limited or unclear response in the face of the transformative nature of algorithms. Instead, policy makers should consider responsible algorithmic code and other proposals as potentially effective responses in the analysis of socio-economic dimensions of algorithms in business.
This article explores the use of artificial intelligence to help define the current test for copyright infringement. Currently, the test for copyright infringement requires the jury or a judge to determine whether the parties’ works are “substantially similar” to each other from the vantage point of the “ordinary observer.” This “substantial similarity” test has been criticized at almost every level due to its inconsistent nature. Artificial intelligence has evolved to the point where it can be used as a tool to resolve many of the current issues associated with the “substantial similarity” test. Specifically, courts would no longer have to rely on a battle of the experts or the use of lay observers to determine if a work is substantially similar to another work. Using a new test based on the “ordinary AI observer” copyright infringement can be established using a means that is both less biased and more fact driven while giving alleged infringers a means by which to check ex ante if their work could be infringing.
National cybersecurity plays a crucial role in protecting our critical infrastructure, such as telecommunication networks, the electricity grid, and even financial transactions. Most discussions about promoting national cybersecurity focus on governance structures, international relations, and political science. In contrast, this Article proposes a different agenda and one that promotes the use of innovation mechanisms for technological advancement. By promoting inducements for technological developments, such innovation mechanisms encourage the advancement of national cybersecurity solutions. In exploring possible solutions, this Article asks whether the government or markets can provide national cybersecurity innovation. This inquiry is a fragment of a much larger literature on various innovation policy options (including patents, prizes, grants, and research and development tax credits). It requires determining whether national cybersecurity is a public good and an examination of market failure and government failure. Along the way, it draws on a property-liability rules theoretical framework to argue that the patent system’s invention secrecy restrictions and government patent use are ineffective for national cybersecurity innovation. On a normative level, the interface between government intervention and markets presents innovation mechanisms for national cybersecurity. Turning to prescriptions, expansion of prizes should rapidly promote national cybersecurity innovation, and reciprocal public–private research and development interactions should gradually multiply knowledge spillovers.
As new, disruptive technologies emerge, the federal government tends to proceed cautiously and often should. State and local units of government, particularly in home rule jurisdictions, may have more potential to respond quickly to innovative technology and its potential threat to civil rights. Unmanned Aerial Vehicles, commonly known as drones, or Unmanned Aerial Systems (“UAS”), which include the drone’s operator equipment and software, demonstrate this legal challenge regarding intrusions on persons and property. This article reveals the breadth and flexibility of local ordinances in the United States that permit and restrict drone usage in a way that protects the civil rights of its local residents, and at a point in time before preemption challenges close off such innovation.
Article 57 of the Uniform Code of Military Justice states the President "may commute, remit, or suspend the sentence, or any part thereof, as the President sees fit. That part of the sentence providing for death may not be suspended." This seemingly contradicts Article 2 of the United States Constitution, which states that the President "shall have the power to grant Reprieves and Pardons for Offenses against the United States, except in Cases of Impeachment." This Article looks at whether the power to "reprieve" offenses includes the power to suspend sentences, including military sentences, and concludes that it does. The historical definition of "reprieve," historical practice of presidents, state court interpretations of similar language, and legislative history of Article 57 all indicate that the President may suspend sentences and Congress may not stop him. For practical reasons, challenging Article 57 would be difficult, but a court would likely declare it unconstitutional if a challenge was ever brought.
Weighing the purposes of insolvency proceedings against applicable state regulations protecting public interests is normatively challenging. The federal goals of maximizing distributions to creditors and rehabilitating debtors are anathema to following state laws that increase a debtor’s expenses in the name of public health and safety. In cases ranging from coal producers to retailers, conflict preemption issues out of the tension between federal insolvency laws and state laws. Consider the faulty ignition switch claims in the General Motors bankruptcy case. Does the asset sale in GM’s bankruptcy case eliminate state-law successor liability? The creditors of GM benefit from a higher sale price if the sale extinguishes the claims but it would violate applicable state law. The general lack of express and field preemption in federal insolvency proceedings funnels questions like this one into conflict preemption. Unfortunately, neither courts nor commentators have created a framework for evaluating conflict preemption in federal insolvency proceedings. They have only identified a potpourri of factors. Parties pay the price through uncertainty manifesting as increased litigation. As state regulations proliferate, the need for a comprehensive framework will only become more acute. This article fills the void by conforming the relevant Supreme Court precedent and the federal insolvency saving clause (28 U.S.C. § 959(b)) to establish a framework for evaluating conflict preemption when both the saving clause is triggered and when it is not. In the process, it resolves the circuit split over whether the saving clause applies in liquidating cases. It also contributes to preemption scholarship by identifying the saving clause as a specific saving clause and clarifying implications of this status – the elimination of the obstacle prong of conflict preemption when the saving clause is triggered.
The General Data Protection Regulation (GDPR), a comprehensive EU Data Privacy Regulation in force since May 2018, has led U.S. companies interested in transatlantic business to a unique awareness and compliance with data protection regulation made in the heart of Europe. According to the predictive model known as the “Brussels effect,” such companies have been spontaneously complying with European rules which are significantly more stringent than those required by U.S. regulators. At the same time, U.S. State legislatures have taken important new measures to regulate consumer privacy, particularly via the California Consumer Privacy Act (CCPA), which provided a narrower consumer protection model than the GDPR. However, because the U.S. federal government is far from taking a comprehensive regulatory path like the GDPR, some States have committed to raising the data privacy protections by following the “California effect” spreading rapidly across U.S. jurisdictions. To better understand the emerging “Balkanization”3 of data privacy regulation, this article relies on three different lenses of analysis: the different cultural and administrative law attitudes of regulators; the diverse political economy regimes in which regulations are implemented; and finally, the path dependencies existing in technological innovation that are reflected by each regulatory regime. This threefold analysis highlights two interrelated phenomena. First, the Balkanization of data privacy regulation does not only lead to costly compliance, but it also leads to essential regulatory experimentation. Second, in the course of such experimentation, public enforcement is increasingly being replaced by privatized oversight, as businesses, rather than courts, are put in charge of monitoring privacy law compliance. In light of this evidence, we claim that the Balkanization of data privacy regulation and the ensuing possibility for experimentation need to be sustained by a heightened degree of public enforcement. Governments should prioritize the role of courts in enforcing privacy rules so as to secure a more egalitarian digital economy and a democratic digital public sphere.
In December 2018, a parrot residing in Blewbury, England cleverly mimicked his owner's voice and ordered a variety of goods on Amazon through her in-home Amazon Alexa virtual assistant device. 2 Although the owner was fortunate enough to have noticed the purchases on her linked account and cancel them in time, 3 the incident provoked a pertinent question with significant legal ramifications: who is responsible if a party other than the owner of the virtual assistant makes an unauthorized purchase on the device?
