Summer 2025
The Network Law Review publishes four issues a year. Articles go online one by one and are gathered by season. This issue closed with 15 publications.
Contents
Newest first19 September 2025
Japanese AI Regulation and Competition Law
Kyohei Yamamoto and Yasunori Tabei
This article explores Japan’s emerging approach to regulating generative AI, balancing innovation and risk. The government emphasizes soft, sector-specific regulation guided by international norms, while the 2025 AI Bill outlines policies promoting AI development and safety.
Read Japanese AI Regulation and Competition LawCite Japanese AI Regulation and Competition Law
17 September 2025
Crafting the Regulatory Ecosystem for AI: Competition 2.0
The challenges of the global landscape and new market realities, significantly led by the digital sector and AI development, are poised to shape competition policy and call for an unprecedented level of inter-policy coordination.
Read Crafting the Regulatory Ecosystem for AI: Competition 2.0Cite Crafting the Regulatory Ecosystem for AI: Competition 2.0
15 September 2025
Statutory Obsolescence in the Age of Innovation: A Few Thoughts about GDPR
This article examines the problem of statutory obsolescence in the regulation of rapidly evolving technologies, with a focus on GDPR and generative AI. It shows how core GDPR provisions on lawful processing, accuracy, and erasure prove difficult—if not impossible—to apply to AI systems, generating…
Read Statutory Obsolescence in the Age of Innovation: A Few Thoughts about GDPRCite Statutory Obsolescence in the Age of Innovation: A Few Thoughts about GDPR
12 September 2025
AI Governance as Regulation of Collective Memory
The emerging regulatory landscape in the field of AI will substantially influence the construction of collective memory and play a critical role in shaping our “future’s past”. This contribution takes a close look at the traits of collective memory, maps its potential frictions with the emerging AI…
Read AI Governance as Regulation of Collective MemoryCite AI Governance as Regulation of Collective Memory
10 September 2025
Dams For The Infinite River: Limits To Copyright’s Power Over The Next-Generation of Generative AI Media
As the levels of speed and control of Generative AI tech increase to a degree that any media can be changed in real-time to the whim of the consumer, content is becoming interactive – each image its own canvas, each song its own instrument.
Read Dams For The Infinite River: Limits To Copyright’s Power Over The Next-Generation of Generative AI MediaCite Dams For The Infinite River: Limits To Copyright’s Power Over The Next-Generation of Generative AI Media
8 September 2025
Governing Hyperobjects: The New Economics of AI Regulation
Artificial intelligence is not simply a hard regulatory problem, but a fundamentally different kind of object – a hyperobject. Like global warming or the internet, AI operates at scales of space, time, and complexity that exceed the conceptual and institutional boundaries of conventional regulatory…
Read Governing Hyperobjects: The New Economics of AI RegulationCite Governing Hyperobjects: The New Economics of AI Regulation
5 September 2025
The Regulation that Cried Wolf: Generative AI Training Data and the Challenge of Lawful Scale
This essay examines how the EU’s Digital Markets Act unintentionally reshapes the foundations of generative AI. By barring gatekeepers from relying on “legitimate interest” as a legal basis for processing personal data, the DMA creates a fragmented two-tier regime: smaller firms retain flexibility…
Read The Regulation that Cried Wolf: Generative AI Training Data and the Challenge of Lawful ScaleCite The Regulation that Cried Wolf: Generative AI Training Data and the Challenge of Lawful Scale
3 September 2025
Artificial Intelligence and Data Policies: Regulatory Overlaps and Economic Tradeoffs
Ginger Zhe Jin, Liad Wagman and Mengyi Zhong
Advances in artificial intelligence (AI) have sparked intense policy debates worldwide on whether and how to govern the technology. Because data is an input into the training of modern AI systems, existing data regulations may intersect with AI policy proposals.
Read Artificial Intelligence and Data Policies: Regulatory Overlaps and Economic TradeoffsCite Artificial Intelligence and Data Policies: Regulatory Overlaps and Economic Tradeoffs
2 September 2025
Toward Compliance Zero: AI and the Vanishing Costs of Regulatory Compliance
Thanks to recent advances in artificial intelligence, we can now automate tasks that we have never before been able to automate. Work that was expensive has become cheap; tasks that once required a lot of time can now be accomplished nearly instantaneously.
Read Toward Compliance Zero: AI and the Vanishing Costs of Regulatory ComplianceCite Toward Compliance Zero: AI and the Vanishing Costs of Regulatory Compliance
29 August 2025
Special issue on “The Law & Technology & Economics of AI”
Adrian Kuenzler, Thibault Schrepel and Volker Stocker
Regulators across the globe are rushing to ramp up their regulatory frameworks to rein in and deal with Big Tech and AI. Brussels has seized first-mover status and already rolled out a dense corpus of digital acts. The move has stirred controversy.
Read Special issue on “The Law & Technology & Economics of AI”Cite Special issue on “The Law & Technology & Economics of AI”
22 July 2025
How Employee Networks Drive Innovation, and How Remote Work Alters Both
Michael Gibbs, Friederike Mengel and Christoph Siemroth
Our research examines how employee collaboration networks within companies affect the quality of innovation, using data from over 28,000 employees at a large IT services firm. We find that employees who collaborate with more colleagues produce higher-quality innovation, and those who act as…
Read How Employee Networks Drive Innovation, and How Remote Work Alters BothCite How Employee Networks Drive Innovation, and How Remote Work Alters Both
14 July 2025
The U.S. Supreme Court and the Merger Efficiency “Defense”
Firms’ principal motives for merging are not to increase market power, but rather to improve firm outcomes through changes in internal operations or structure. Of the 17000+ mergers that occur annually in the U.S., 90% or more have no expectation of an anticompetitive price increase or output…
Read The U.S. Supreme Court and the Merger Efficiency “Defense”Cite The U.S. Supreme Court and the Merger Efficiency “Defense”
8 July 2025
The Counterintuitive Economics of Default Positions
Yongmin Chen and Marius Schwartz
Which supplier should control the default slot on digital devices? We analyze alternative ways to assign the default position for digital goods like search engines. First, we show that competitive bidding for the default usually rewards the higher-quality incumbent, yet it can reduce consumer…
Read The Counterintuitive Economics of Default PositionsCite The Counterintuitive Economics of Default Positions
30 June 2025
Computational Antitrust: Evidence From 25 Antitrust Agencies
This paper explores patterns from the Stanford Computational Antitrust project’s fourth annual report, which includes contributions from 25 agencies worldwide. The findings reveal that most agencies are converging around similar technological solutions, particularly large language models and…
Read Computational Antitrust: Evidence From 25 Antitrust AgenciesCite Computational Antitrust: Evidence From 25 Antitrust Agencies
25 June 2025
Antitrust Antidote: March-June 2025
Nathan Wilson and Koren W. Wong-Ervin
There were a number of decisions from March through June 2025 including: (1) a Ninth Circuit win by Microsoft and Activision in the FTC’s suit challenging the vertical integration between the two companies; (2) two district court decisions (U.S. et al. v. Google Ad Tech and U.S. et al. v. Live…
Read Antitrust Antidote: March-June 2025Cite Antitrust Antidote: March-June 2025