Category Archives: philosophy

what is a brute fact?

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During the twenties, so a story goes, [the former Prime Minister of France, Georges] Clemenceau, shortly before his death, found himself engaged in a friendly talk with a representative of the Weimar Republic on the question of guilt for the outbreak of the First World. War. “What, in your opinion,” Clemenceau was asked, “will future historians think of this troublesome and controversial issue?” He replied, “This I don’t know. But I know for certain that they will not say Belgium invaded Germany.” (Hannah Arendt, “Truth and Politics,” 1967, p. 239 )

Arendt uses this anecdote as an example of “brutally elementary data.” On p. 237, she mentions the “unyielding, blatant, unpersuasive stubbornness” of certain “truths seen and witnessed with the eyes of the body, and not the eyes of the mind.”

I agree that Belgium did not invade Germany in August 1914. (The reverse is true.) However, this example is complicated.

First, it is not a literal fact that “Germany” invaded “Belgium.” The name of any country is a concept, a metaphor, or a simplification. Perhaps the “brutally elementary data” is that some people moved from locations in German territory to locations in Belgian territory, and these people were (among other things) soldiers in the German Army. But even that formulation introduces information that would not be evident to an observer who was unaware of European politics.

Second, you and I do not remember seeing German troops cross the border. We believe that Germany invaded because that is what we have learned in school or from media. Our knowledge is entirely contingent on trust in these institutions.

Third, the word “invaded” is normatively loaded. An invasion isn’t necessarily bad. The Allied landings in Normandy were an invasion in a just cause. But Clemenceau uses the the word to imply that Germany broke its obligations and started the war. He would disagree with someone who said, “In August 1914, Imperial German troops had to extend the front into Belgian territory to protect the Fatherland,” even though that would also describe the same event.

Finally, Clemenceau used this example because he presumed–and expected his audience to presume–that the act of invading Belgium was the crucial causal factor. What if someone replied that the invasion was only one event in a sequence that begin with the assassination in Sarajevo on June 28, 1914, Austro-Hungary’s declaration of War on Serbia one month later, and Russia’s declaration of war against Austro-Hungary?

Clemenceau could have remarked, “They will not say that the Archduke Franz Ferdinand assassinated Gavrilo Princip.” (The reverse was the case). But he did not choose that example because his motive was to cast blame on Germany. There are infinite facts, and Clemenceau selected one to make a point.

Lenin argued that the cause of the First World War was imperialism. Europeans had run out of countries to conquer and exploit and had turned on each other. Some would say that Lenin’s thesis was an interpretation, whereas “Germany invaded Belgium” is a fact. But Clemenceau implied (or “implicated“) a whole interpretation by choosing a particular fact. And Lenin could cite many facts in support of his interpretation.

Insofar as we can know facts by direct observation or reliable methods, we don’t really need a variety of opinions to attain knowledge. If you think of a school, a university, or a newspaper as a purveyor of facts, then you may be uninterested in whether the people involved hold diverse views, and you may be suspicious when they seem to be editorializing. They should stick to the truth. Disagreement is a sign that an issue hasn’t yet been resolved–as it should be.

On the other hand, if you think that every important claim is an opinion, then you will see such institutions as forums for debate. (I think that is how Bari Weiss sees both CBS News and the University of Austin.) You may want these institutions to be pluralistic, but you won’t count on them to generate reliable information. And you may be quick to assert a right to disagree with any claim, no matter the nature of the evidence.

Presumably, we should navigate between these extremes, valuing both information and opinion and recognizing the two as intrinsically linked. Arendt wants us to remain connected to the actual world, and she is worried that ideology disconnects us from facts. But she also wants us to remain connected to other people, who inevitably have different interpretations. As she writes in The Human Condition (p. 57):

… the reality of the public realm relies on the simultaneous presence of innumerable perspectives and aspects in which the common world presents itself and for which no common measurement or denominator can ever be devised. For though the common world is the common meeting ground of all, those who are present have different locations in it, and the location of one can no more coincide with the location of another than the location of two objects. Being seen and being heard by others derive their significance from the fact that everybody sees and hears from a different position. This is the meaning of public life, compared to which even the richest and most satisfying family life can offer only the prolongation or multiplication of one’s own position with its attend ing aspects and perspectives. ….Only where things can be seen by many in a variety of aspects without chang ing their identity, so that those who are gathered around them know they see sameness in utter diversity, can worldly reality truly and reliably appear.

See also: ideological pluralism as an antidote to cliche; the case for viewpoint diversity; is all truth scientific truth?; holding two ideas at once: the attack on universities is authoritarian, and viewpoint diversity is important etc.

Juergen Habermas (1929-2026)

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Jürgen Habermas died on Saturday. His death has been the occasion for several substantial and interesting obituaries. So far, I prefer Gal Beckerman’s in the New York Times.

I took a seminar on Habermas in 1988, when I was a college junior. Georgia Warnke was the professor, and I have kept her useful packet of readings to this day. Habermas crystallized my early thinking about politics and philosophy and has remained a pillar for me ever since. I discuss him in most of my books, with the most general and extensive presentation in chapter 5 of What Should We Do? A Theory of Civic Life (2022) The title of that book basically captures Habermas in a phrase. I have also recorded a 29-minute introductory lecture on him.

It is misleading to treat Habermas as a proponent of rational, civil discourse. (See “Habermas with a Whiff of Tear Gas,” 2018). I suspect that more Americans have read Iris Marion Young’s critique of Habermas (“Activist Challenges to Deliberative Democracy, Political Theory, 2011) than have read Habermas itself. The late and lamented Iris Young caricatured him in that article. If Habermas wanted everyone to talk calmly all the time, then why did he conclude his two-volume magnum opus, The Theory of Communicative Action, with a celebration of disruptive social movements?

Habermas lived so long and became famous so early that his public role is itself an interesting phenomenon. Apparently, Ronald Dworkin remarked that even Habermas’ fame is famous, and it is worth asking why someone who wrote such thorny theory occupied the position of (arguably) the most influential German thinker for half a century.

I took a whole semester course on Habermas–in English, on the other side of the Atlantic–when he still had 38 years ahead of him. That is an indication of his stature. But it does not mean that he shaped the course of history, or even of scholarship.

In Postwar, Tony Judt discusses “the demise of the continental intellectual.” On May 31, 2003, Habermas plus Jacques Derrida, Umberto Eco, Richard Rorty, and several other leading thinkers published coordinated essays against the Iraq War in distinguished European newspapers. The result “passed virtually unnoticed. It was not reported as news, nor was it quoted by sympathizers. No-one implored the authors to take up their pens and lead the way forward. … The whole project sputtered out. One hundred years after the Dreyfus Affair, fifty years after the apotheosis of Jean-Paul Sartre, Europe’s leading intellectuals had thrown a petition–and no one came” (pp. 785-7).

I am not quoting Judt today to cast aspersions on Habermas, whose work was deep and broad. I suspect that changes in media and communications have reduced the influence of serious intellectuals. Besides, Habermas may never have wanted to be the new Jean-Paul Sartre. Elsewhere, I have discussed how Michel Foucault (born just three years before Habermas) deliberately shunned the role of the “universal intellectual”; and perhaps we are better off without such people. By all accounts, Habermas welcomed criticism and learned from a wide range of responses. He modeled what he advocated: listening and learning from others. I think his work will long outlive him.

See also: introducing Habermas; saving Habermas from the deliberative democrats; Habermas with a Whiff of Tear Gas: Nonviolent Campaigns and Deliberation in an Era of Authoritarianism; Matthew G. Specter, Habermas: An Intellectual Biography, and many other posts.

How do we know whether fish are happy? How do we know whether we are? (Zen, Aristotelian, and Taoist discussions)

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When you watch fish swimming around in very cold water, they look fine. Human beings have a protein, TRPM8, that reacts to cold and affects our nervous system, causing discomfort or even pain when the temperature goes down. But fish do not have any TRPM8 (Yong p. 138). Thus we can infer that fish do not sense cold in the way we do.

This does not mean that we know what cold is really like, while fish do not. Nor does it mean that our pain is nothing real, as if we can make it go away by disbelieving it. Nor does it mean that we know what it feels like to be a fish. But we can perceive a difference between species.

Long before anyone knew about proteins, the behavioral difference between us and fish was obvious enough that it served as an example for several thinkers who asked whether experiences like pleasure and suffering are subjective. More deeply, they asked what happiness is.

Japanese Zen Buddhism uses the term kyogai. Often translated as “consciousness,” it literally means “boundary” or “bounded place,” deriving originally from the Sanskrit word visayah, in the sense of a pasture that has a boundary. The Buddhist Abbot Mumon Yamada (1900-1988) taught:

This thing called kyogai is an individual thing. …. Only another fish can understand the kyogai of a fish. In this cold weather, perhaps you are feeling sorry for the fish, poor thing, for it has to live in the freezing water. But don’t make the mistake of thinking it would be better off if you put it in warm water; that would kill it. You are a human and there is no way you can understand the kyogai of a fish.

I think the upshot here is humility: if things seem and feel very different to creatures that have different senses, we cannot really know how things are. We should be compassionate, but that is harder than it may at first appear because it requires knowing what another feels. It would not be compassionate to move carp to a warmer pond. Our humility must temper even our compassion.

Aristotle wants to distinguish wisdom, which is knowledge of objective truths, from practical wisdom or phronesis, which allows us to act well. For example, “straight” (using the term from geometry) always means the same thing. The line that takes the shortest distance between two points is straight, regardless of whether any creature sees it as such–or sees it at all. In fact, a line would be straight even if there were no sentient creatures. Hence geometry is a part of wisdom.

However, says Aristotle, different things are healthy and good for people and for fish, and human phronesis involves doing the healthy thing for us, not for them. The “lower animals” also have practical wisdom because they also know what to do. If we try to convince ourselves that our phronesis is wisdom because we are higher than fish, we are foolish because there are things far more divine than we are (NE 1143a).

The upshot, for Aristotle, is that each creature has its own nature, and the proper definition of happiness is acting according to that nature. This means that a fish is happy if it swims around in the cold, not because that behavior feels good to it, but because happiness is accordance with nature. One distinguishing feature of human beings is that we can also know wisdom, or glimpses of it, by studying things higher than ourselves. Thus, for Aristotle, observing the behavior of fish does not really encourage humility. It directs us to identify our proper nature and its place in the cosmos as a whole.

Now here is a passage from Zhuangzi:

Zhuangzi and Huìzi wandered along the bridge over the Hao river. Zhuangzi said, ‘The minnows swim about so freely and easily. This is the happiness of fish’.

Huìzi said, ‘You’re not a fish. How do you know the happiness of fish?

Zhuangzi said, ‘You’re not me. How do you know I don’t know the happiness of fish?’

Huìzi said, ‘I’m not you, so indeed I don’t know about you. You’re indeed not a fish, so that completes the case for your not knowing the happiness of fish’.

Zhuangzi said, ‘Let’s go back to where we started. When you said, “How do you know the happiness of fish”, you asked me about it already knowing that I knew it. I knew it over the Hao river’. (17/87–91)

I have virtually no knowledge of Taoism or its context, so it is risky for me to venture an interpretation. But I think the idea here is that neither of the men in the story can know the other, let alone the fish, and therefore all knowledge (including of one’s self) is illusory. However, Zhuangzi was right in the first place. “This” was the happiness of fish. He could not know its content or how happiness would feel to a fish, only that because fish were being fish, they were happy.

Ed Yong, An Immense World: How Animal Senses Reveal the Hidden Realms Around Us (Penguin Random House, 2022); Yamada as cited in Victor Sogen Hori, “Koan and Kensho in the Rinzai Zen Curriculum,” in The Koan: Texts and Contexts in Zen Buddhism (2000); Zhuangzi. The Complete Writings, translated by Chris Fraser (Oxford World’s Classics, p. 200). I translated Aristotle from the 1894 Clarendon edition on https://scaife.perseus.org/, but I have paraphrased here because the literal text is thorny. See also: some basics; Verdant mountains usually walk

living life as a story

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Thesis: It is better to live as if one’s life were a story, yet many people cannot live that way.

A conventional story has a finite number of named characters, many of whom know many of the rest. These characters have constraints and limitations, but they also face at least some consequential choices. The choices they make contribute to the plot. Their choices tend to be related to their inner lives: their beliefs, desires, and character traits. Although they may spend most of their time separately and quietly, the narrative emphasizes their interactions. In fact, dialogue occupies much of a conventional novel and all the text of a play or a screenplay. In biographies and narrative histories, quotations from speech may be shorter, but they are are often prominent. What the characters think, do, and say is noticed and preserved–at least by the narrator, and usually by some of their fellow characters.

We can feel that our lives are like this, and we can be correct about it. Or we can feel (rightly or wrongly) that this is not how we live. Here are some threats to living as if in a story:

  • Modern economies (capitalist or socialist) that organize masses of workers so that each one feels little agency, while many live so precariously that they cannot make consequential decisions.
  • State tyranny, which not only blocks consequential choices and suppresses frank discussion but also invades the private spaces in which people could develop independent beliefs and values.
  • Hypertrophied science and technology, which make human behavior appear mechanical and predictable, or which actually control human beings.
  • Bureaucracy, which minimizes individual agency by applying rules, metrics, and files.
  • Ideologies, in the pejorative sense of all-encompassing theories that explain individual choices away or that replace human characters with abstractions, such as classes or nations, as the major protagonists.
  • Loneliness or isolation, meaning the absence of the interactions that would constitute a conventional story.
  • A lack of solitude, an inner life that can be described in a narrative and connected to overt actions.
  • Catastrophes, which wipe out the memories of characters and their actions.

(On that last point, Jonathan Lear writes:

Not long ago, I listened to a lecture on climate change. The lecture went as one might expect. There was a warning of impending ecological catastrophe and talk of the “Anthropocene,” suggesting that our age—the age in which humans dominate the Earth—is coming to an end. At the end of the talk, there was a discussion period. At one point, a young academic stood up and said simply, “Let me tell you something: We will not be missed!” She then sat down. There was laughter throughout the audience. It was over in a moment.

Lear develops the idea that missing or mourning things is a distinctively human contribution; and it is ineffably sad that no one would miss homo sapiens, even if we cause our own extinction, and even if other species would be better off without us. It means that all the stories would be gone.)

I think many of us assume that our lives are like stories and that some other people notice and remember our roles in them. For us, the evaluative questions are: How is this story turning out? And what kind of a character am I? I would rather live in a comedy than in a tragedy, and I aspire to be the hero rather than the villain in my own little patch.

However, I think the main thrust of Hannah Arendt’s philosophy is that there is an antecedent question: Am I in a story at all? (See, e.g., The Human Condition, chapter v.) I believe she would say that it is better to be the villain in a tragedy than not to inhabit any kind of story, and that most modern people no longer do. The list of threats (above) comes directly from her work.

Note that this is a different ideal from the common one of authorship. For instance, Immanuel Kant defines ethical individuals as the authors of the rules that govern them:

The will is therefore not merely subjected to the law, but in such a way that it must also be regarded as self-legislating, and precisely for that reason must it be subject to the law (of which it can consider itself the author [als Urheber]).

In contrast, Arendt writes:

Although everybody started his life by inserting himself into the human world through action and speech, nobody is the author or producer of his own life story. In other words, the stories, the results of action and speech, reveal an agent, but this agent is not an author or producer. Somebody began it and is its subject in the twofold sense of the word, namely, its actor and sufferer, but nobody is its author (The Human Condition, p. 184)

For her, politics is the domain where people are characters but there is no author. This is a result of plurality: there are many of us, and no one (not even a dictator) can solely determine the outcomes.

Jürgen Habermas holds a generally similar view but presents all the citizens of a community as its authors (in the plural):

According to the republican view, the status of citizens is not determined by the model of negative liberties to which these citizens can lay claim as private persons. Rather, political rights—preeminently rights of political participation and communication—are positive liberties. They guarantee not freedom from external compulsion but the possibility of participation in a common praxis, through the exercise of which citizens can first make themselves into what they want to be—politically autonomous authors of a community of free and equal persons.

Authors and characters are metaphors, not literal descriptions. As such, they capture certain compelling ideas without fully describing reality. Here I want to suggest that the metaphor of characters draws our attention to urgent issues. We need social, political, and intellectual reforms to enable more people to live like characters in stories. These reforms require intentional action. We must be the authors of contexts in which people can be characters.

Sources: Jonathan Lear, Imagining the End: Mourning and Ethical Life (Harvard, 2022, p. 1); Kant, Grundlegung zur Metaphysik der Sitten (my trans.); Habermas, “Three Normative Models of Democracy,” in Seyla Benhabib (ed.), Democracy and Difference: Contesting the Boundaries of the Political (Princeton University Press, 1996). p. 22. See also: Hilary Mantel and Walter Benjamin; Kieran Setiya on midlife; a vivid sense of the future; the coincidences in Romola; and Freud on mourning the past.

can AI solve “wicked problems”?

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I’ve been reading predictions that artificial intelligence will wipe out swaths of jobs–see Josh Tyrangiel in The Atlantic or Jan Tegze. Meanwhile, this week, I’m teaching Rittel & Webber (1973), the classic article that coined the phrase “wicked problems.” I started to wonder whether AI can ever resolve wicked problems. If not, the best way to find an interesting job in the near future may be to specialize in wicked problems. (Take my public policy course!)

According to Rittel & Webber, wicked problems have the following features:

  1. They have no definitive formulation.
  2. There is no stopping rule, no way to declare that the issue is done.
  3. Choices are not true or false, but good or bad.
  4. There is no way to test the chosen solution (immediate or ultimate).
  5. It is impossible, or unethical, to experiment.
  6. There is no list of all possible solutions.
  7. Since each problem is unique, inductive reasoning can’t work.
  8. Each problem is a symptom of another one.
  9. You can choose the explanations, and they affect your proposals.
  10. You have no “No right to be wrong.” (You are affecting other people, not just yourself. And the results are irreversible.)

Rittel and Webber argue that those features of wicked problems deflate the 20th-century ideal of a “planning system” that could be automated:

Many now have an image of how an idealized planning system would function. It is being seen as an on-going, cybernetic process of governance, incorporating systematic procedures for continuously searching out goals; identifying problems; forecasting uncontrollable contextual changes; inventing alternative strategies, tactics, and time-sequenced actions; stimulating alternative and plausible action sets and their consequences; evaluating alternatively forecasted outcomes; statistically monitoring those conditions of the publics and of systems that are judged to be germane; feeding back information to the simulation and decision channels so that errors can be corrected–all in a simultaneously functioning governing process. That set of steps is familiar to all of us, for it comprises what is by now the modern-classical mode planning. And yet we all know that such a planning system is unattainable, even as we seek more closely to approximate it. It is even questionable whether such a planning system is desirable (p. 159)

Here they describe planning systems that would have been very labor-intensive in 1973, but many people today imagine that this is how AI works, or will work.

why are problems wicked?

Some of the 10 reasons that some problems are “wicked,” according to Rittel & Webber, relate to the difficulty of generating knowledge. Policy problems involve specific things that have many features or aspects and that relate to many other specific things. For example, a given school system has a vast and unique set of characteristics and is connected by causes and effects to other systems and parts of society. These qualities make a school system difficult to study in conventional, scientific ways. However, could a massive LLM resolve that problem by modeling a wide swath of the society?

Another reason that problems are wicked is that they involve moral choices. In a policy debate, the question is not what would happen if we did something but what should happen. When I asked ChatGPT whether AI will be able to resolve wicked problems, it told me no, because wicked problems “are value-laden.” It added, “AI can optimize for values, but it cannot choose them in a legitimate way. Deciding whose values count, how to weigh them, and when to revise them is a normative, political act, not a computational one.”

Claude was less explicit about this point but emphasized that “stakeholders can’t even agree on what the problem actually is.” Therefore, an AI agent cannot supply a definitive answer.

A third source of the difficulty of wicked problems involves responsibility and legitimacy. In their responses to my question, both ChatGPT and Claude implied that AI models should not resolve wicked problems because they don’t have the right or the standing to do so.

what’s our underlying theory of decision-making?

Here are three rival views of how people decide value questions:

First, perhaps we are creatures who happen to want some things and abhor other things. We experience policies and their outcomes with pleasure, pain, or other emotions. It is better for us to get what we want–because of our feelings. Since an AI agent doesn’t feel anything, it can’t really want anything; and if it says it does, we shouldn’t care. Since we disagree about what we want, we must decide collectively and not offload the decision onto a computer.

Some problems with this view: People may want very bad things–should their preferences count? If we just happen to want various things, is there any better way to make decisions than to maximize as many subjective preferences as possible? Couldn’t a computer do that? But would the world be better if we did maximize subjective preferences?

In any case, you are not going to find a job making value-judgments. Today, lots of people are paid to make decisions, but only because they are assumed to know things. Nobody will pay for preferences. Life works the other way around: you have to pay to get your preferences satisfied.

Second, perhaps value questions have right and wrong answers. A candidate for the right answer would be utilitarianism: maximize the total amount of welfare. Maybe this rule needs constraints, or we should use a different rule. Regardless, it would be possible for a computer to calculate what is best for us. In fact, a machine can be less biased than humans.

Some problems with this view: We haven’t resolved the debate about which algorithm-like method should be used to decide what is right. Furthermore, I and others doubt that good moral reasoning is algorithmic. For one thing, it appears to be “holistic” in the specific sense that the unit of assessment is a whole object (such as a school or a market), not separate variables.

Third, perhaps all moral opinions are strictly subjective, including the opinion that we should maximize the satisfaction of everyone’s subjective opinions. Then it doesn’t matter what we do. We could outsource decisions to a computer, or just roll a die.

The problem with this view: It certainly does matter what we do. If not, we might as well pack it in.

AI as a social institution

I am still tentatively using the following model. AI is not like a human brain; it is like a social institution. For instance, medicine aggregates vast amounts of information and huge numbers of decisions and generates findings and advice. A labor market similarly processes a vast number of preferences and decisions and yields wages and employment rates. These are familiar examples of entities that are much larger than any human being–and they can feel impersonal or even cruel–but they are composed of human inputs, rules, and some hardware.

Another interesting example: integrated assessment models (IAMs) for predicting the global impact of carbon emissions and the costs and benefits of proposed remedies. These models have developed collaboratively and cumulatively for half a century. They take in thousands of peer-reviewed findings about specific processes (deforestation in Brazil, tax credits in Germany) and integrate them mathematically. No human being can understand even a tiny proportion of the data, methods, and instruments that generate the IAMs as a whole. But an IAM is a human product.

A large language model (LLM) is similar. At a first approximation, it is a machine that takes in lots of human generated text, processes it according to rules, and generates new text. Just the same could be said of science or law. This description actually understates the involvement of humans, because we do not merely produce the text that the LLM processes to generate output. We also conceive the idea of an LLM, write the software, build the hardware, construct the data centers, manage the power plants, pour the cement, and otherwise work to make the LLM.

If this is the case, then a given AI agent is not fundamentally different from a given social institution, such as a scientific discipline, a market, a body of law, or a democracy. Like these other institutions, it can address complexity, uncertainty, and disagreements about values. We will be able to ask it for answers to wicked problems. If current LLMs like ChatGPT and Claude refuse to provide such answers, it is because their authors have chosen–so far–to tell them not to.

However, AI’s rules are different from those in law, democracy, or science. I am biased to think that its rules are worse, although that could be contested. The threat is that AI will start to generate answers to wicked problems, and we will accept its answers because our own responses are not definitively better and because it responds instantly at low cost. But then we will lose not only the vast array of jobs that involve decision-making but also the intrinsic value of being decision-makers.

Source: Rittel, Horst WJ, and Melvin M. Webber. “Dilemmas in a general theory of planning.” Policy sciences 4.2 (1973): 155-169. See also: the human coordination involved in AI; the difference between human and artificial intelligence: relationships; the age of cybernetics; choosing models that illuminate issues–on the logic of abduction in the social sciences and policy