Mark Coeckelbergh’s The Political Philosophy of AI: An Introduction boldly situates artificial intelligence (AI) within the framework of political philosophy. The book goes beyond the dominant ethical focus to explore AI’s entanglement with core political ideals like freedom, equality, democracy, and power. In this ambitious work, Coeckelbergh bridges the gap between political philosophy and the pressing societal implications of AI, offering what he calls an “Introduction” to the political philosophy of AI, a much-needed perspective in an era where AI technologies increasingly shape human lives and institutions.

At the heart of this book is a central claim: AI is inherently political, not merely a neutral tool. It also highlights the extraordinary power that corporations, who lead the way in AI innovation, now hold in influencing the political and social landscape. This change in power dynamics raises urgent questions about accountability, governance, and the ethical responsibilities in determining the future of society.

The claim that AI is inherently political may be an obvious remark for ethics scholars. However, the author takes on the challenge of identifying and articulating the unique characteristics of AI as a political phenomenon, aiming to initiate a “dialogue between thinking about politics and thinking about technology,” concretely AI. The author uses the history of political philosophy and recent work to achieve this objective. Hence, the book is an excellent overview of what recognized voices in political philosophy would have said about the impact of AI on society. These thinkers include Hegel, Marx, Foucault, Rawls, Hayek, Hannah Arendt, and more. Also, the book consists of a comprehensive literature review of current scholars who are critically examining the societal implications of AI.

Coeckelbergh organizes the book into seven chapters, each addressing a distinct political-philosophical theme. Chapter 2 explores the implications of AI on freedom, examining how technologies like algorithmic decision-making challenge autonomy and liberty. From surveillance to the rise of “robot slavery,” Coeckelbergh critically connects these developments to classical debates on negative and positive freedom by examining how AI technologies restrict individual autonomy through surveillance (negative freedom) and manipulate decision-making through nudging, thereby challenging individuals’ ability to self-govern (positive freedom).

Chapter 3 interrogates the intersection of AI with equality and justice, focusing on how automation and algorithmic biases exacerbate social inequalities and discrimination. Drawing on Rawls, Marx, and feminist theory, he questions whether justice can reconcile universal fairness with the demands of group identity and historical inequalities. By engaging with critical feminism, anti-racist, and anti-colonial perspectives, the chapter situates these debates within broader discussions of intergenerational and global justice.

The following chapters expand the discussion by addressing how AI impacts democratic processes and societal power dynamics. Chapter 4 delves into AI’s impact on democratic processes, such as election manipulation and the rise of information bubbles, situating these trends within more significant concerns about totalitarianism and Arendtian notions of the “banality of evil.” In Chapter 5, Coeckelbergh applies Foucauldian and Marxist frameworks to analyze AI’s role in shaping power dynamics, arguing that data-driven technologies discipline individuals while reinforcing structural inequalities. Chapter 6 ventures beyond the human, asking how AI might reshape political status for nonhumans and ecosystems, drawing on posthumanist and transhumanist considerations.

The book’s structure is both a strength and a limitation. The thematic organization—freedom, equality, democracy, power, and posthumanism—provides clarity and focus, but the connections between themes occasionally feel tenuous. While Coeckelbergh acknowledges these overlaps, readers may wish for a more integrated framework to capture AI’s multifaceted impacts.

One of the book’s standout contributions lies in its critique of liberal notions of equality. Coeckelbergh skillfully dissects algorithmic bias, drawing on Rawls’s Theory of Justice to contrast equality of opportunity with redistributive justice. The analysis shines in the author’s engagement with alternative frameworks, such as Marxism and identity politics. The discussion of “AI capitalism” and “algorithmic oppression” provides a multifaceted critique of how algorithmic systems perpetuate systemic biases, such as racial and gender discrimination, also highlighting opportunities for corrective interventions. For instance, Coeckelbergh’s discussion aligns with Virginia Eubanks’s Automating Inequality (Reference Eubanks2018), which examines how automated decision-making entrenches existing inequities in areas like welfare distribution. Coeckelbergh also engages with Shoshana Zuboff’s (Reference Zuboff2018) concept of surveillance capitalism, describing it as a new economic system that commodifies personal data to predict and manipulate behavior. This system not only exacerbates social inequalities by reinforcing algorithmic biases that disadvantage marginalized groups, automating discrimination in areas like hiring, lending, and law enforcement, but also reshapes the ethical landscape of business and politics, challenging corporations to address their role in perpetuating power imbalances and calling for stronger protections of individual rights and democratic freedoms in the digital age.

Another strength of the book is its application of classical political philosophy to contemporary AI dilemmas. The chapter on democracy, for example, examines the erosion of deliberative processes through AI-enabled echo chambers and misinformation, drawing parallels with Arendt’s analysis of totalitarianism. By engaging with Arendt’s insights on political participation, Marx’s critique of capitalism, and Foucault’s theories of power and surveillance, Coeckelbergh provides a nuanced examination of how AI technologies shape social control, economic inequality, and the very foundations of democratic governance.

Coeckelbergh compellingly links the pervasive loneliness of modern society to the dynamics of surveillance capitalism, illustrating how AI technologies exploit this isolation while simultaneously deepening it. Drawing on Arendt’s exploration of loneliness as a precursor to totalitarianism, he argues that AI’s role in surveillance and data collection fosters a culture of self-monitoring and behavioral conformity. These technologies do not merely observe; they shape our identities by reinforcing specific patterns of thought, consumption, and social interaction, subtly influencing how we perceive ourselves and others. Coeckelbergh highlights the troubling paradox: while AI-driven platforms promise connection and self-expression—allowing individuals to share opinions, curate identities, and engage with others—they often lead to a more profound alienation by commodifying personal data and molding individuals into predictable, manipulable subjects within a capitalist framework. This dual dynamic raises urgent questions about the kind of selves and societies these technologies are engineering.

Despite its many strengths, the book is not without its shortcomings. Coeckelbergh occasionally overgeneralizes, particularly when discussing the supposed neutrality of AI practitioners. While his critiques of technocratic optimism are valid—particularly his skepticism toward claims that technology alone can solve complex societal issues—they risk alienating readers from technical fields, such as computer science and engineering, who may already be actively addressing these ethical and political challenges. Coeckelbergh’s critique could benefit from acknowledging the ongoing efforts within these fields to develop ethical frameworks and socially responsible AI practices, as seen in initiatives like the IEEE Global Initiative on Ethics of Autonomous Systems (2019) or contributions from TU Delft scholars, such as Dignum (Reference Dignum2019) on responsible AI governance and Van de Poel (Reference Van de Poel2020) on embedding ethical values into AI system design, which seek to integrate ethical principles into AI development and governance.

Another notable limitation is the book’s Western focus. Although Coeckelbergh discusses global inequality and AI’s environmental impact, the examples and theories are largely drawn from Western contexts. While Coeckelbergh does not explicitly claim to make universal rules, his engagement with political philosophy and ethics invites broader applicability. Expanding the discussion to include non-Western perspectives on technology and politics could enrich the analysis by challenging Western-centric assumptions about concepts like freedom, justice, and democracy, which underpin much of his critique. For instance, incorporating frameworks from non-Western traditions, such as Confucian relational ethics or African Ubuntu philosophy, might offer alternative approaches to questions of community, responsibility, and governance in the context of AI. This could lead to different conclusions about how technology ought to serve societal needs, particularly in diverse cultural and political contexts.

For business ethics, the book makes a significant contribution by highlighting AI’s political and ethical dimensions and raising critical questions about how these technologies influence governance and individual freedoms, corporate practices, and responsibilities. Coeckelbergh challenges businesses to address the ethical implications of surveillance capitalism, algorithmic bias, and automation, emphasizing the need for corporations to embed fairness, accountability, and inclusivity into their operations.

In conclusion, this book illustrates how AI is inherently political and fundamentally reshapes how society is organized and functions, with profound and far-reaching political implications.