Heads up:

The Fall Privacy Foundation Seminar is scheduled for Friday, October 27^th.

Recent Developments in State Privacy Laws

*The Colorado Privacy Act

*State Privacy Laws in Colorado compared to states like California and Virginia

Our Panel include:

Corinne O'Doherty, Senior Legislative Aide for Rep. Meg Froelich

Jefferey Riester from Attorney General Phil Weiser's Office

Shelby Dolen from Husch Blackwell

Send comments to the Privacy Foundation at privacyfoundation@law.du.edu and copy John Soma at jsoma@law.du.edu.

Can the law evolve as fast as AI?

https://eprints.ugd.edu.mk/32279/

Civil liability for AI in EU: General remarks

Artificial Intelligence (AI) has become an increasingly prominent and influential technology in modern society, permeating various sectors and significantly impacting the way we live, work, and interact. AI systems possess the ability to analyze vast amounts of data, recognize patterns, and make complex decisions with remarkable speed and accuracy. As a result, AI has facilitated significant improvements in efficiency, productivity, and problem-solving capabilities across various industries. From autonomous vehicles enhancing transportation safety to intelligent virtual assistants streamlining everyday tasks, AI has showcased immense potential in transforming societal functions. Nevertheless, alongside its transformative power, AI presents inherent risks and potential for damage. As AI systems become increasingly autonomous and capable of independent decision-making, questions regarding liability arise. Tort law, with its focus on civil wrongs and compensation for damage, plays a crucial role in determining legal accountability when AI-related damages occur. The complexities surrounding liability in AI are magnified due to the intricate interplay between human agency and machine autonomy, raising challenging legal questions that demand careful consideration.

This contribution aims to present a general overview of the liability regimes currently in place in EU Member States and to determine if they provide for an adequate distribution of all such risks. The starting idea of this research is that such cases in the EU will often have different outcomes due to peculiar features of these legal systems that may play a decisive role, especially in cases involving AI. Mainly, these legal regimes largely attribute liability to human actors, emphasizing concepts such as negligence or intentional misconduct. On the other hand, although there are strict liabilities in place in all European jurisdictions, for the legal theory at present many AI systems do not fall under these regimes, and the victims are left with the sole option of pursuing their claims via fault liability.

How does that work? An obvious question?

https://www.pnas.org/doi/abs/10.1073/pnas.2301842120

Interpretable algorithmic forensics

One of the most troubling trends in criminal investigations is the growing use of “black box” technology, in which law enforcement rely on artificial intelligence (AI) models or algorithms that are either too complex for people to understand or they simply conceal how it functions. In criminal cases, black box systems have proliferated in forensic areas such as DNA mixture interpretation, facial recognition, and recidivism risk assessments. The champions and critics of AI argue, mistakenly, that we face a catch 22: While black box AI is not understandable by people, they assume that it produces more accurate forensic evidence. In this Article, we question this assertion, which has so powerfully affected judges, policymakers, and academics. We describe a mature body of computer science research showing how “glass box” AI—designed to be interpretable—can be more accurate than black box alternatives. Indeed, black box AI performs predictably worse in settings like the criminal system. Debunking the black box performance myth has implications for forensic evidence, constitutional criminal procedure rights, and legislative policy. Absent some compelling—or even credible—government interest in keeping AI as a black box, and given the constitutional rights and public safety interests at stake, we argue that a substantial burden rests on the government to justify black box AI in criminal cases. We conclude by calling for judicial rulings and legislation to safeguard a right to interpretable forensic AI.

It is sounding less and less likely that AI will replace lawyers. Darn.

https://techreg.org/article/view/17979

All Rise for the Honourable Robot Judge?

There is a rich literature on the challenges that AI poses to the legal order. But to what extent might such systems also offer part of the solution? China, which has among the least developed rules to regulate conduct by AI systems, is at the forefront of using that same technology in the courtroom. This is a double-edged sword, however, as its use implies a view of law that is instrumental, with parties to proceedings treated as means rather than ends. That, in turn, raises fundamental questions about the nature of law and authority: at base, whether law is reducible to code that can optimize the human condition, or if it must remain a site of contestation, of politics, and inextricably linked to institutions that are themselves accountable to a public. For many of the questions raised, the rational answer will be sufficient; but for others, what the answer is may be less important than how and why it was reached, and whom an affected population can hold to account for its consequences.

New approach?

https://www.research.unipd.it/handle/11577/3496800

Artificial Intelligence, the Public Space, and the Right to Be Ignored

AI is capable of is occupying, patrolling, and even controlling the physical space. The issue of Artificial Face Recognition is only the most visible aspect of a much broader phenomenon, as computer vision empowers private and public entities to capture a great deal of information that is available in the public sphere in an unprecedented way, challenging how public law conceives public spaces. Despite significant differences, various legal orders are similarly concerned with this phenomenon, which is shifting the boundaries between what is private and what is public. This Chapter i) explains how, because of AI, public spaces are morphing into something new; ii) argues for the protection of anonymity; iii) demonstrates the failures of several contemporary theorizations of public places and that the standard privacy paradigm fails to provide sufficient protection; iv) proposes a new approach to the topic. Drawing from different legal orders, it ultimately argues for a reconceptualization of the public sphere in a way that mitigates the impact of AI on social life.