Chapter 8 revisits the classical market failure rationale for public intervention in support of innovative entrepreneurship, arguing that the emergence of artificial intelligence does not invalidate its core logic. The chapter contends that, rather than overturning established policy rationales, AI calls for their careful adaptation. In this respect, it advocates the integration of AI tools into entrepreneurship policy-making, in line with practices already used in the private sector, while cautioning against simplistic policy approaches centred on entry subsidies alone. The analysis highlights the unintended consequences that broad and undifferentiated regulatory interventions may generate, particularly when compliance costs disproportionately affect start-ups and small innovative firms. It also warns against the weaponization of industrial policy in the field of AI, stressing that such strategies risk distorting competitive conditions to the detriment of innovative entrepreneurship. Building on the risks identified in Chapter 7 – including incumbent advantage, systemic lock-in, labour market turmoil, and postmodern forms of entrepreneurship – the chapter outlines four policy propositions aimed at ensuring that AI functions as an enabler rather than a constraint for innovative entrepreneurial activity. Overall, the chapter offers a policy-oriented framework for preserving entrepreneurial dynamism, competition, and social welfare in advanced capitalist economies in the AI era.

This commentary reads the three chapters in the section through Catherine Malabou’s discussion of the politics of anarchism. It argues that the each contribution describes a specific form of anarchic normativity, a related vision of the hierarchical, implications of these specific and specifically anarchic forms, and that each remains relatively fuzzy about the possible forms of regulatory agency. The conclusion focuses on the complicit engagements of scholars with anarchic normativities, their implications and the regulatory forms associated with them.

Chapter 5 examines ‘restrictive practices’ and their legal and ethical implications for nurses. Restrictive practices are actions that restrict a person’s freedom of movement, such as locking the person in a room, secluding them by confining them to a physical space, putting them in manacles or straps, medicating them or directly holding them to restrict their movement. These practices can only be carried out as a last resort to protect the patient or another person, and must be authorised by a medical practitioner. A patient subject to restrictive practices must be observed closely at all times. In years past, the use of physical restraints in a clinical setting was not uncommon and included tying a person to a chair with a sheet, or tying the hands of a bed-bound person to the side of the bed. Besides any obvious cruelty, these practices were known to result in death by strangulation, falls, head injuries, lacerations and tissue necrosis. Nurses who use unauthorised restrictive practices may be liable for charges of kidnapping, assault and battery and, in the worst case, manslaughter.

This chapter explores the landscape of global AI regulation, and how these emerging technologies are being defined and conceptualised. It offers a comparative analysis across four major legislative orders, namely the European Union, the UK, China, and the USA. Each of these is adopting distinct frameworks for regulating AI, shaped by diverse ideological and normative attitudes towards human rights, innovation, and the preservation of state power. The chapter explores the legal and socio-ethical implications of governing AI, especially how differing stances on transparency and risk are set to influence its international development. Building upon current governance approaches to AI, this chapter draws on insights from interviews and focus groups with Law Enforcement Agency (LEA) experts to address the use of AI-powered solutions in law enforcement and the operational and societal challenges that they present; focusing on the impact and use value of advanced data processing and data analysis technologies for daily investigative work. Overall, the chapter contributes to a nuanced understanding of the multifaceted dimensions surrounding AI governance and its impact on law enforcement practices internationally.

Chapter four addresses the objection that social governance should be left to public regulators rather than corporations. It explains why regulation often arrives too late to guide corporate decisions about new technologies, platforms, and global supply chains. Firms must act long before legislatures or agencies develop workable rules.

The chapter also shows how regulators frequently rely on corporate practices when building legal frameworks. Corporate standards, metrics, and monitoring systems often become templates for public regulation. This pattern does not reflect capture alone. It reflects the information and capacity advantages that firms possess in fast moving domains.

The chapter proposes a diagnostic approach. Strong corporate ordering can justify regulatory restraint when governance systems demonstrate real deliberative capacity. Weak or symbolic ordering signals the need for intervention.

Rather than presenting corporate governance and regulation as alternatives, the chapter explains how they interact over time. Corporate ordering shapes the terrain on which regulation emerges. Public law then stabilizes, corrects, or constrains private governance. Understanding this interaction is essential for evaluating both corporate claims and regulatory design.

The primary threat of AI is not a dystopian uprising, but the quiet, rational surrender of human autonomy for convenience. While existing risks like discrimination and disinformation are concerning, another profound danger is one we willingly embrace: a life optimized by AI. As we delegate increasingly consequential decisions – from career paths to personal relationships – to demonstrably superior AI systems, we become meat puppets, happier and healthier, yet stripped of meaningful agency. The chapter argues that this philosophical loss, driven by the competitive pressure to optimize our lives, likely cannot be curbed by regulation and will be the defining, irreversible tragedy of the AI age.

This chapter challenges the notion that generative AI (GenAI) outputs qualify for First Amendment protection as “speech.” It argues that under both speech certainty and human-centric legal frameworks, GenAI outputs – being probabilistic, statistically driven, and devoid of human understanding, sentience, or intent – should be legally categorized as nonexpressive conduct or utilitarian data processing, not intentional communication.

The chapter dismantles the common counterargument that a user has a constitutional “right to receive” an AI’s output, asserting that if no speech is created by the speaker (the AI model), there is no speech to receive. This classification determines the government’s regulatory authority. If AI outputs are deemed speech, regulations face the nearly insurmountable barrier of “strict scrutiny.” If they are nonexpressive conduct, however, the government retains the power to regulate GenAI for safety. The chapter warns that extending constitutional free speech protections to nonhuman, nonintentional algorithms would jeopardize product liability, consumer protections, and democratic self-governance.

The widely accepted “AI Race” narrative, which pits the US against rivals like China, is a flawed metaphor that actively harms thoughtful AI development and policy. This chapter deconstructs the “race” by showing it lacks a clear finish line or coherent definition of “winning,” unlike historical contests such as the space race or the Manhattan Project. The narrative is based on three shaky assumptions: that innovation inherently equals progress, that generative AI is already capable of near-term, large-scale usefulness, and that the “winner” will control global AI values. Critically, these flawed premises trigger predictable, problematic policy reactions, including unlimited corporate and governmental spending, indefinite delays on necessary regulation, and hasty, thoughtless deployment. By prioritizing speed and raw capability over genuine utility, the “AI race” risks squandering resources on unreliable systems and undermining public trust. The chapter concludes that the real challenge lies in human coordination, not computation, and calls for abandoning the race framework in favor of a wise, goal-oriented approach that serves human needs over corporate interests.

This chapter traces the intellectual and technological lineage of Bitcoin and digital money. While Nakamoto’s white paper launched Bitcoin, its roots extend through decades of economic theory, cryptographic innovation, and activist movements. We examine how the Austrian and Chicago Schools of Economics provided a framework for stateless and non-inflationary money, and how Cypherpunk ideals shaped the push for privacy and decentralization. The chapter reviews early experiments with digital currencies such as DigiCash, b-money, and e-gold, highlighting the technical shortcomings, regulatory battles, and user adoption barriers that prevented their success but furnished essential building blocks for Bitcoin. We then contrast the classical financial attributes of money—medium of exchange, unit of account, and store of value—with additional digital requirements such as offline spendability, identity-less spendability, and fungibility. Finally, we show how Bitcoin resolved the long-standing double-spending problem without a central authority through Proof of Work, situating it as both a culmination of earlier efforts and the starting point for a new era of cryptocurrencies.

This chapter locates business in the economic thinking of the Single Market Program, which transformed regional economic, commercial, competition, industrial, and social policies and remade the relationship between firms and European governance. It examines the wide-ranging approaches of European officials to enterprise as they made collective Community agreements and designed policies for the internal market. Cabinet documents and speeches from regional policymakers in the European Commission shed light on the tensions between promoting the regional economic activity of firms on the one hand and increasingly regulating the market and its actors to protect consumers, workers, and the environment on the other. Ultimately, it argues, the Commission saw Community-wide business activity as the key to achieving the market and its wider economic and social objectives. By supporting cross-border mergers, acquisitions, investment, partnerships, and the development of regional supply and value chains, regional policymakers aimed to reassert the power and influence of a united Europe in the global economy.

This chapter examines how commercial firms like the Belgian grocer Delhaize did not initially respond to the Single Market Program in the mid-1980s, but they did mobilize swiftly in the late 1980s to prepare for the "threat" of the new business and regulatory environment of an integrated regional market governed by social and environmental protections. Together with other food retailers, Delhaize formed sectoral clubs and associations to defend its interests: Buying clubs collectivized price negotiating power against producer consolidation and protected profit margins, while interest associations brought distributors and retailers together to influence European policymaking. At the same time, Delhaize and other commercial firms saw in the opening of Eastern Europe a profitable business opportunity, and they expanded quickly into the markets of Poland, Hungary, and the new Czech Republic in the early 1990s. As a result, the case of Delhaize gives us purchase on the complexity of business responses to market integration and demonstrates the diverse paths to regionalization for and against the Single Market.

Drawing on archival sources from Paribas as well as published statements from bank chairmen Jean-Yves Haberer, Michel François-Poncet and André Lévy-Lang, this chapter examines Paribas in the European economy of the 1980s and 1990s, the evolution of the bank’s business strategy amid the macroeconomic changes of market integration and market openings, and the bank’s perspectives on the Single Market and banking regulation in European economic governance. If carmakers like Volkswagen and BMW expressed enthusiasm about the business opportunities of the Single Market Program for their supply chains, production, and distribution and even supported the EEC’s efforts to develop environmental regulations, merchant banks like Paribas seemed rather ambivalent and even directly opposed to the regulatory and social dimensions of market integration through their lobbying efforts and business interest associations. In the early 1990s, the opening of Central and Eastern Europe presented new investment and growth opportunities making Paribas much more interested in business opportunities in Central and Eastern Europe, the “CEE,” than in the business environment of the EEC and its Single Market.