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Judith Shklar

The political philosopher who fled Riga one step ahead of annihilation and spent four decades arguing that the first obligation of any political order is not to build the good society but to prevent the worst—and whose liberalism of fear has become the sharpest available instrument for interrogating what AI is already doing to people.
Judith Shklar came to political philosophy through exile, and exile is the education she never stopped drawing on. Born in Riga in 1928, she fled the Baltic as a child in advance of the Nazi and Soviet occupations, arriving in Montreal after a journey through Japan and the United States that deposited in her the specific knowledge of someone who has watched a political order fail its people before the ideology that destroyed it was even fully articulated. From that formation she built a political philosophy of unusual modesty and unusual force: the liberalism of fear, which does not begin where most theories begin—with a vision of the good society, a blueprint for flourishing—but at the bottom, with the question every refugee learns to ask: what is the worst that can happen, and what structures prevent it? Her central move was to place cruelty first among the vices a political order might exhibit, insisting in Ordinary Vices (1984) that cruelty destroys the victim’s capacity to function as a political agent, and therefore forecloses the possibility of addressing every other wrong. Her mature work, The Faces of Injustice (1990), gave the framework its sharpest instrument: the distinction between misfortune and injustice, the argument that the powerful routinely classify avoidable suffering as inevitable in order to dissolve the obligation to prevent it. Shklar died in 1992, a decade before the tools she would have most wanted to analyze were built; but her framework, applied with precision in [YOU] on AI and extended by thinkers from Matthieu Queloz to Hannes Bajohr, has proven to be among the most diagnostically accurate instruments for the present moment in artificial intelligence.
Judith Shklar
Judith Shklar

In the [YOU] on AI Field Guide

The cycle’s governing metaphor describes AI as an amplifier that carries whatever signal it receives further and faster than any previous tool. Shklar’s liberalism of fear asks the question the amplifier metaphor defers: what is already in the signal? What suffering is the system producing right now, in real workplaces and real families, before we get to the aspirational questions about what the technology might achieve? She insists on reversing the priority of utopian theory—asking first what is being destroyed, not what is being built—and that reversal is the most practically useful thing her philosophy offers the present moment.

Her concept of cruelty by default names with precision what the AI transition is producing at scale: not the dramatic cruelty of intentional harm but the structural cruelty of institutional environments that prevent the people building and deploying powerful systems from attending to the consequences of what they build. The deployment cycle that compresses development from months to days, the competitive pressure that treats hesitation as weakness, the cultural norms that celebrate velocity—these produce indifference as a structural feature, not a personal failing, and Shklar’s framework insists that structural indifference generates the same obligation to prevent as deliberate harm.

Putting Cruelty First
Putting Cruelty First

Her distinction between misfortune and injustice is the cycle’s most important analytical tool for evaluating the discourse about AI-driven displacement. When the technology industry classifies the suffering of displaced workers as the inevitable cost of progress—as misfortune rather than injustice—it performs a political act that Shklar spent her career exposing: the reclassification of avoidable suffering as inevitable in order to dissolve the obligation to address it. The displacement is not natural. It is the product of choices about deployment speed, about the distribution of gains, about the presence or absence of transitional protections—choices made by identifiable actors within identifiable institutions that could have been otherwise.

Shklar stands alongside Judy Wajcman and Juliet Schor in the cycle’s gallery of thinkers who supply the political-economic lens the builder’s perspective tends to produce blindness about. Where Wajcman documents the gendered structure of temporal experience and Schor maps the institutional machinery of overwork, Shklar provides the foundational claim that names what is at stake in both: that the suffering of the vulnerable generated by powerful systems operated without constraint is not a side effect to be managed but a political failure to be prevented.

The Fishbowl Of The Powerful
The Fishbowl Of The Powerful

Origin

Shklar studied at McGill and Harvard, where she eventually became the first woman to receive tenure in Harvard’s Government Department. Her early work—on Hegel, on utopian thought, on legalism—reflects a thinker drawn to the gap between political ideals and political reality, a gap she understood not abstractly but from the specific pedagogy of displacement. She published Legalism (1964), After Utopia (1957), and a study of Rousseau before arriving at the mature framework of Ordinary Vices and The Faces of Injustice.

Cruelty by Default
Cruelty by Default

The key intellectual move of her career was the refusal of the political philosopher’s standard starting point. Where Rawls builds from an original position, where communitarians build from shared values, Shklar builds from the refugee’s knowledge of what political orders do to people when they fail. This is not pessimism but a different kind of realism: the realism of someone who knows that political orders are not judged by their aspirations but by their failures, by the suffering they could have prevented and did not.

The Liberalism of Fear
The Liberalism of Fear

The liberalism of fear is therefore a philosophy of institutional design, not of rights theory or of the good life. Its question is always specific and procedural: what arrangements prevent the worst? What structures constrain power enough that the powerless are protected? And—the key move for the present moment—what is lost when the institutional response to new concentrations of power arrives too slowly to prevent the harm those concentrations produce?

Matthieu Queloz
Matthieu Queloz

Key Ideas

The Liberalism of Fear. Shklar’s mature political philosophy takes fear as its starting point—not as a vice to overcome but as a political signal to be taken seriously. The person who fears has perceived something real about the distribution of power and the adequacy of protections. A political order that dismisses the fear of its vulnerable members as irrationality or failure to adapt is a political order that has stopped attending to the people it most needs to protect.

Fear as Political Data
Fear as Political Data

Putting Cruelty First. Among all the vices a political order might exhibit, cruelty occupies a singular position—not because it is the most common but because it destroys the victim’s capacity to function as a political agent. A person subjected to systematic cruelty cannot resist, cannot organize, cannot articulate what is being done to them. Cruelty forecloses every other political remedy, which is why preventing it takes priority over building the good society.

Hannes Bajohr
Hannes Bajohr

The Misfortune-Injustice Distinction. The most practically powerful instrument in Shklar’s toolkit is the argument that the line between misfortune and injustice is not a neutral empirical observation but a political act performed by those with the authority to classify suffering. When the powerful classify avoidable harm as inevitable progress, they dissolve the obligation to prevent it—and the suffering continues without generating the political demand for structural change that it would generate if correctly identified as injustice. The AI transition is producing this reclassification at scale.

Cruelty by Default. Shklar’s analysis of political cruelty always attended to systemic rather than intentional forms—the cruelty of institutional arrangements that produce suffering as a byproduct rather than a purpose, where no individual intended harm but the system was structured to make harm the predictable outcome. Contemporary AI deployment—with its compressed timescales, its competitive incentives, and its classification of transition costs as externalities—is a textbook case.

The Fishbowl of the Powerful. Shklar understood that the exercise of power produces a specific form of epistemological blindness—not a moral failing but a structural condition in which the powerful lack the perspective from which the consequences of their power are visible. The remedy is not better individuals but institutional structures that force consequences into the field of vision of those who exercise power—transparency requirements, accountability mechanisms, the participation of the vulnerable in decisions that shape their lives.

Debates & Critiques

The central objection to applying Shklar to AI is that her framework was built for the dramatic politics of totalitarianism and exile, and the harms of the AI transition—however real—are too diffuse and too voluntary to belong in the same register. Shklar herself anticipated this objection and spent much of her career refuting it: the Ordinary Vices and The Faces of Injustice are both arguments that political philosophy must attend to the quiet cruelties, the institutional arrangements that produce suffering without anyone intending to be cruel. The more pointed contemporary objection, pressed by Matthieu Queloz’s work on AI advisory systems, is about asymmetry: Shklar’s liberalism of fear focuses on freedom from interference, but AI systems introduce a new kind of dependence—the user who relies on an AI advisor for information and judgment is not merely exposed to harm but actively shaped by a system whose values she did not design and cannot inspect. Hannes Bajohr extends this further, arguing that when AI systems mediate an increasing proportion of human communication, the very conditions of democratic participation—the ability to say what one means in one’s own register—are at stake in a way Shklar did not anticipate but her framework can accommodate. The liberalism of fear is not anti-technology; it is against power without constraint. Its prescription for AI is not prohibition but the construction of institutions adequate to the power being deployed—built before the harm compounds, not after.

The Liberalism of Fear Applied

Shklar’s three diagnostic moves for evaluating AI’s political consequences
First Move
Begin at the Bottom
Do not ask what the technology might achieve. Ask first what it is already destroying—what forms of human security, dignity, and rest are being eroded by a transition no one voted for. The answer to that question determines what institutions need to be built.
Second Move
Classify Correctly
Is the suffering produced by AI deployment misfortune or injustice? If it is the product of choices—about deployment speed, distribution of gains, presence or absence of transitional protection—then it is injustice, and it generates obligations that misfortune does not.
Third Move
Build Before the Harm
Shklar’s temporal claim: protection must precede the harm, or arrive quickly enough that it does not compound beyond the capacity of institutions to address. Every month without intervention is a month in which avoidable suffering becomes entrenched.

Further Reading

  1. Judith N. Shklar, Ordinary Vices (Harvard University Press, 1984)
  2. Judith N. Shklar, The Faces of Injustice (Yale University Press, 1990)
  3. Judith N. Shklar, “The Liberalism of Fear,” in Liberalism and the Moral Life, ed. Nancy Rosenblum (Harvard University Press, 1989)
  4. Matthieu Queloz, “Taking the Liberalism of Fear Seriously in the Age of AI,” Ethics and Information Technology (2025)
  5. Hannes Bajohr, “The Linguistic Conditions of Democratic Participation in the Age of Large Language Models,” Philosophy & Technology (2025)
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