Zhang et al. on Balancing Data-Driven Competition and Privacy Protection: A Duopoly Analysis of AI-Powered Digital Assistants

Xiong Zhang (Beijing Jiaotong U) et al. have posted “Balancing Data-Driven Competition and Privacy Protection: A Duopoly Analysis of AI-Powered Digital Assistants” on SSRN. Here is the abstract:

Artificial Intelligence (AI) is rapidly empowering smart products, enhancing both work efficiency and quality of life. However, these improvements rely heavily on the continuous collection and processing of user data, raising significant concerns about privacy. In response, many countries have enacted regulations to protect personal data and consumer privacy. This study examines how privacy protection influences market competition in AI-powered digital assistant markets. We develop a stylized analytical model of a duopoly where firms differ in their ability to collect and monetize consumer data. The results reveal that stronger AI capabilities amplify the profitability of data-intensive firms, while data-light firms can strategically strengthen privacy protection to remain competitive, thereby generating mutual profit gains and enhancing consumer surplus as well as overall social welfare. These findings contribute to the theoretical understanding of data-driven competition and digital privacy management, while offering actionable insights for firms seeking to balance innovation, consumer trust, and regulatory compliance in smart product markets.

Salman on The Digital Panopticon: How AI has Reshaped Workplace Surveillance and Labor Control

Urooba Salman (Lahore U Management Sciences (LUMS)) has posted “The Digital Panopticon: How AI has Reshaped Workplace Surveillance and Labor Control” on SSRN. Here is the abstract:

This paper seeks to interrogate how artificial intelligence has transformed the exercise of managerial power, labor autonomy, and the traditional and foundational principles of labor law. Drawing on Michel Foucault’s theory of thepanopticon and extending it to the modern workplace, it argues that algorithmic systems have created a “digital panopticon”; an architecture of invisible surveillance which disciplines workers through datafication and the fear of surveillance rather than outright coercion. Using insights from labor law scholarship, critical theory, and existing empirical research, the paper demonstrates that AI-based monitoring tools, ranging from productivity trackers and biometric attendance systems to predictive analytics, actually embed control into the very scaffolds of the modern workplace, eroding collective bargaining practices, privacy, and procedural fairness.

This study situates these changes and transformations within the Pakistani context and legal framework, where though the infiltration of surveillance is not so perverse, fragile labor protections, weak privacy and data governance laws, and imported surveillance technologies create an especially fertile ground for exploitation. It conceptualises this phenomenon as “surveillance colonialism,” wherein technologies from authoritarian or unregulated jurisdictions infiltrate developing economies under the guise of modernization. The paper contends that Pakistan’s outdated legal architecture regarding AI and data cannot adequately address such algorithmic decision making, leading to an accountability vacuum and a structural silencing of labor resistance which needs to be addressed before it is too late.

Remolina on Open Finance

Nydia Remolina (Singapore Management U Yong Pung How Law) has posted “Open Finance” on SSRN. Here is the abstract:

This chapter provides an account of open finance as a regulatory and technological architecture for customer-authorised financial data sharing. It begins by defining open finance and open banking, and identifying its core components: data holders, data users, APIs, consent mechanisms, technical standards and governance arrangements. It then traces the evolution of open finance from open banking initiatives, with particular attention to the UK and EU experiences and their influence on later frameworks. The chapter next examines the main claimed benefits of open finance, including competition, innovation, improved user experience, safer data access, AI-enabled services and financial inclusion. It also analyses the risks and implementation challenges, including fragmented standards, cybersecurity, liability, privacy, profiling, discrimination and platform concentration. Finally, the chapter compares market-development and compulsory regulatory models across jurisdictions.

Golway on The Problems of Philosophy in the Age of AI

Tom Golway (Generative Dynamics Research) has posted “The Problems of Philosophy in the Age of AI” on SSRN. Here is the abstract:

When Bertrand Russell wrote The Problems of Philosophy in 1912, he grappled with the gap between appearance and reality, asking how we can know anything with certainty when our senses may deceive us. Russell’s skepticism presumed that underlying truth existed and could be approached through rigorous inquiry. Over a century later, his questions have not merely persisted—they have proliferated into new domains of epistemic risk. Artificial intelligence does not simply introduce fresh uncertainties; it actively manufactures realities, fragments shared understanding, and operates at speeds that preclude human deliberation. In this landscape, the peril is not ignorance but epistemic surrender: the quiet abdication of judgment to systems that neither know nor care what is true. This paper revisits Russell’s inquiry in light of AI’s epistemic power, arguing for a renewed ethics of validation, provenance, and human oversight.

Stefano on Labour Law, Technology, and the Attack on the Rules-Based-Order

Valerio De Stefano (York U Osgoode Hall Law) has posted “Labour Law, Technology, and the Attack on the Rules-Based-Order” on SSRN. Here is the abstract:

This paper argues that current debates on artificial intelligence and algorithmic management at work are also debates about private power, managerial prerogative, and democracy. It situates recent attacks by major technology companies and their political allies on the European Union and other rule-based international institutions within a broader struggle over who should regulate technology and govern society. It contends that the anti-democratic turn of parts of the tech world is closely connected to authoritarian ideas about work, hierarchy, and obedience. The workplace is one of the principal sites where authority is exercised, surveillance normalised, and habits of subordination formed, with consequences that extend beyond employment relations into democratic life more broadly. Against this background, the paper examines how AI and algorithmic management intensify employer power through pervasive monitoring, automated evaluation, predictive analytics, and data-driven discipline. It argues that existing legal frameworks, especially data protection law, remain insufficient unless infused with labour law concepts that address the structural imbalance of power at work. It therefore advocates a substantial upgrading of labour law, stronger limits on digital surveillance, and a more robust role for collective bargaining, codetermination, and worker voice in the governance of workplace technologies. It contends that labour law is one of the main ways in which the rule of law enters the workplace and workers remain citizens rather than subjects while at work. The regulation of AI at work is thus a constitutional and democratic question as much as an economic or technological one.

Shucha on Closing the AI Readiness Gap: A Framework for Law Schools

Bonnie J. Shucha (U Wisconsin Law) has posted “Closing the AI Readiness Gap: A Framework for Law Schools” (32 (2) Perspectives: Teaching Legal Research and Writing (forthcoming 2026)) on SSRN. Here is the abstract:

Gen AI literacy for new associates is expected, not optional, yet most law schools have not caught up, and students are arriving in practice without the foundational gen AI literacy skills to use these tools safely and effectively. Closing that gap need not mean a new curriculum or a major investment; it can be done by coordinating what a school already has, so that every student graduates prepared. This article offers a framework built on three co-equal questions: what students learn, when and where they learn it, and who coordinates the learning.

Khalid on The Use of Autonomous Weapons in the Ukraine Conflict:Assessing Compliance with IHL Principles

Mahmood Khalid (Ziauddin U) has posted “The Use of Autonomous Weapons in the Ukraine Conflict:Assessing Compliance with IHL Principles” on SSRN. Here is the abstract:

This research paper examines how Autonomous Weapon Systems (AWS) are being used in the war between Russia and Ukraine and evaluates how well they adhere to the fundamental rules of International Humanitarian Law (IHL), such as proportionality, distinction, and caution. Based on actual case studies using Ukrainian AI-enabled drones and surveillance platforms and Russian loitering bombs, the study examines the level of human control, the consequences for accountability, and the operation of autonomous systems on the battlefield. It assesses the moral and legal ramifications of giving machines the ability to make deadly decisions, emphasizing potential dangers such attribution errors, automation bias, and a lack of contextual judgment. The paper also looks at existing international legal frameworks, including the Geneva Conventions, CCW, and customary IHL, and finds weaknesses in their capacity to control new technology. The article claims that current rules are unable to handle the growing threat posed by AWS, citing expert viewpoints, particularly Paul Scharre’s work on autonomy in warfare. In order to guarantee accountability, protect human dignity, and stop abuse, it ends by assessing current regulatory initiatives and suggesting legislative changes. In the end, the situation in Ukraine is a real-world experiment that highlights how urgent it is to have complete international oversight of AWS.

Joseph on Balancing Innovation and Biomedical Ethics within National Institutes of Health: Integrative and Regulatory Reforms for Artificial Intelligence-Driven Biotechnology

Joshua S. Joseph (Hofstra U Maurice A. Deane Law) has posted “Balancing Innovation and Biomedical Ethics within National Institutes of Health: Integrative and Regulatory Reforms for Artificial Intelligence-Driven Biotechnology” (44 Biotech. L. Rep. 2 (2025) [10.1089/blr.2025.360002.jj ]) on SSRN. Here is the abstract:

The article examines the foundational principles of biomedical ethics and their relevance to the intersection of artificial intelligence (AI) and biotechnological progress. It then analyzes the potential impact of the National Institutes of Health’s (NIH or the Agency) proposed 2024 reorganization reforms, as presented by the House Committee on Energy and Commerce (E&C), and advocates for the inclusion of provisions that would enable the Agency to develop and deploy “safe, secure, and trustworthy” AI within the biotechnology sector. Thus, the article proposes two key integrative reforms to address these concerns: (1) enhancing research collaborations among healthcare systems, academic institutions, and the private sector through AI-driven platforms, and (2) establishing an NIH office to oversee AI-based health initiatives. These reforms would require legislative amendments, including updates to the Patent and Trademark Law Amendments Act of 1980 (Bayh-Dole Act or Bayh Dole) and the 21st Century Cures Act of 2016 (Cures Act), while adhering to biomedical ethics. Such amendments would ensure (1) ethical standards in collaborative research and development (R&D) among institutions and (2) effective health initiative design and implementation. In the same light, this article advocates for an updated legislative framework to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) that regulates the role of such integrative efforts and balances the transformative potential of AI in biotechnology. In all, these regulatory steps ensure that innovation benefits society while safeguarding individual rights such as personal data and privacy and mitigating algorithmic bias.

Abraha on Navigating Workers’ Data Rights in the Digital Age: A Historical, Current, and Future Perspective on Workers’ Data Protection

Halefom H. Abraha (Utrecht U Law) has posted “Navigating Workers’ Data Rights in the Digital Age: A Historical, Current, and Future Perspective on Workers’ Data Protection” on SSRN. Here is the abstract:

Over recent decades, comprehensive data protection legislation has proliferated worldwide, with a majority of jurisdictions enacting robust statutory regimes. Despite this abundance of legal standards, persistent challenges remain regarding the efficacy of these laws in protecting individuals‒ particularly workers‒within the increasingly digitalised workplace. Workers are especially susceptible to harm due to entrenched power asymmetries and heightened risks of data exploitation, yet many existing legal frameworks provide insufficient or inconsistent protection, and some jurisdictions explicitly exclude workers from coverage.

This research critically examines the multidimensional risks associated with workplace digitalisation and systematically analyses regulatory challenges and protection gaps across diverse jurisdictions. By integrating historical analysis, current policy initiatives, and comparative cross-jurisdictional perspectives, the study identifies structural deficiencies in prevailing approaches. It concludes by proposing policy solutions to advance worker-centric data governance frameworks, tailored to address the distinctive challenges of contemporary labour relations and to ensure more equitable and effective protection for workers in the digital age.

Whalen on Human-Required Originality: Copyright Eligibility in a Post-AI World

Ryan Whalen (The U Hong Kong Law) has posted “Human-Required Originality: Copyright Eligibility in a Post-AI World” (Forthcoming AIPLA Q.J. (Summer 2026)) on SSRN. Here is the abstract:

Generative artificial intelligence upends the assumptions that have anchored U.S. copyright law for more than a century. By enabling the production of high‑quality expressive works at effectively zero marginal cost, GenAI destabilizes copyright’s utilitarian foundation and exposes a deep incoherence in the originality requirement: the law grants exclusive rights to human‑authored works that could have been produced just as easily—and at no cost—by modern generative systems, while denying protection to the machine‑generated equivalents that render human effort unnecessary. At the same time, GenAI introduces a dynamic risk that existing doctrine is unequipped to address: as AI increasingly substitutes for human creators in markets characterized by commoditized content, human participation may collapse, starving future models of the novel, high‑signal training data needed for continued aesthetic and cultural evolution. Left unaddressed, these twin pressures threaten both the theoretical coherence and the long‑term creative vitality of the copyright system.

This Article argues that the core of the problem lies not in questions of infringement or AI authorship, but in copyright’s threshold requirement: the “modicum of creativity” standard no longer filters works that require human incentives from those that do not. I propose a new, technologically grounded interpretation of originality—the human‑required creativity standard—under which copyright protection attaches only to works that could not have been generated by state‑of‑the‑art models with de minimis human input at the time of authorship or registration. This content‑focused approach restores alignment between copyright’s incentives and its constitutional purpose by denying protection to trivially generable works regardless of whether a human or a machine produced them, while continuing to protect works that demand meaningful human creative contribution.

A rebuttable presumption of eligibility and an affirmative defense of trivial generability make the human required standard administratively workable while preserving automatic copyright protection. The framework remains compatible with international treaty obligations, avoids prohibited formalities, and maps onto familiar doctrine. By grounding copyright eligibility in the realities of modern creative production, the human‑required standard offers a path toward preserving human creativity, supporting sustainable innovation in AI, and re‑anchoring copyright law in its fundamental task: promoting progress in the arts and sciences.