from Andalusia to Cornwall

Four sabbatical months in Europe are coming to a close this week. We spent three of those months in Granada, Spain, until our Schengen tourist visas ran out. Since then, we have mostly stayed in Penzance, Cornwall.

It’s a study in contrasts. To name one: Andalusia is famous for fervent Catholic spirituality, although I’ve written a bit about how that reputation is exaggerated.* Meanwhile, Cornwall may be the most Methodist region on earth, with Methodists representing an outright majority of Cornish churchgoers since the 1800s. Few expressions of Christianity could be as different as a stark, sober Nonconformist chapel versus a whole city that pulsates with baroque, syncretic Catholicism during Holy Week.

But I want to mention water.

Andalusia has always been semi-arid, and its classic landscape is dry earth studded with olive trees between stony mesas. Right now, the region is suffering a catastrophic draught that is probably related to climate change. However, the Nasrid (medieval Arabized Muslim) rulers of Granada built a remarkable irrigation system for the city. Snow melts on the Sierra Nevada mountains, fills Nasrid aqueducts, flows through high-pressure pipes under the Alhambra to the Plaza Nueva, and then up to the area around today’s Church of San Nicolás, where a mosque covered a large public cistern. From that reservoir, pipes still fill more than a dozen other Nasrid cisterns, from which water irrigates backyard gardens and squares filled with flowering trees and other plants that attract an exuberant array of birds. The whole city is an artificial oasis, more than eight centuries old, which is surviving the ecological crisis so far. You can clearly see the distant snow that waters the trees around you.

When we arrived in Cornwall, it stopped raining here, as if we had brought the Andalusian draught with us. The skies have been almost as blue as they were in Spain. But this is a watery place. Everywhere, burbling streams rush down to the nearby sea. Most streams are overgrown, almost concealed in foliage, as is nearly everything. The entire county has been covered by a thick mat “Of tendrils, leaves, and rough nuts brown”–not inert, but luxuriantly growing as you watch; and flowers have been generously sprinkled over all that deep green.

*See also reflections on modern Granada (Spain); Richard Wright’s Pagan Spain.

Postdoctoral Fellowship in Civic Science

Tufts University’s Jonathan M. Tisch College of Civic Life offers a Postdoctoral Fellowship in Civic Science for the 2023-24 academic year (September 1, 2023- August 31, 2024) with the possibility of renewal for an additional year. This position is offered in partnership with the Rita Allen Foundation in Princeton, NJ and involves remote work with the Rita Allen Foundation, the Civic Science Fellowship, and their partners as well as full-time employment at Tufts. Some in-person work in the Boston area is preferred, although remote-only employment can be considered.

The position is open to applicants who hold PhDs. We will also post a version of this position open to people who are ABDs (all-but-dissertation), so watch this space for that opening.

The Tisch College Civic Science initiative, led by Dr. Peter Levine and Dr. Samantha Fried, aims to reframe the relationships among scientists and scientific institutions, institutions of higher education, the state, the media and the public. It also asks about the relationships and distinctions among those institutions, historically and today.

The Rita Allen Foundation invests in early-stage research and practice in biomedicine, Civic Science, and philanthropic practice. In its work on Civic Science, the foundation fosters networks that expedite learning, promote inclusion, and generate impactful outcomes to ensure that science and evidence help to inform solutions to society’s most pressing problems.

The Civic Science Fellowship program, an initiative of the Rita Allen Foundation and other philanthropic partners, is committed to positioning emerging leaders of diverse backgrounds within organizations that operate at the intersection of science and society. Fellows are entrusted with a range of multidisciplinary projects that link Civic Science research to evidence-based practice and facilitate the interaction between scientists and communities. Such projects may entail the creation of innovative media, the design of strategies for community engagement, and/or the exploration of optimal practices for collaboration with specific demographic groups. Additionally, Fellows contribute to strengthening the culture of Civic Science across various networks by forging connections and creating shared resources.

Applicants must demonstrate a strong interest in investigating the intersections of science and civic matters as the focus of their postdoctoral fellowship.

Civic Science is interdisciplinary, and this fellowship is open to specialists in any relevant field.

More here, including the official link to apply.

the difference between human and artificial intelligence: relationships

A large-language model (LLM) like ChatGPT works by identifying trends and patterns in huge bodies of text previously generated by human beings.

For instance, we are currently staying in Cornwall. If I ask ChatGPT what I should see around here, it suggests St Ives, Land’s End, St Michael’s Mount, and seven other highlights. It derives these ideas from frequent mentions in relevant texts. The phrases “Cornwall,” “recommended” (or synonyms thereof), “St Ives,” “charming,” “art scene,” and “cobbled streets” probably occur frequently in close proximity, because ChatGPT uses them to construct a sentence for my edification.

We human beings behave in a somewhat similar way. We also listen to or read a lot of human-generated text, look for trends and patterns in it, and repeat what we glean. But if that is what it means to think, then LLM has clear advantages over us. A computer can scan much more language than we can and uses statistics rigorously. Our generalizations suffer from notorious biases. We are more likely to recall ideas we have seen most recently, those that are most upsetting, those that confirm our prior assumptions, etc. Therefore, we have been using artificial means to improve our statistical inferences ever since we started recording possessions and tallying them by category thousands of years ago.

But we also think in other ways. Specifically, as intensely social and judgmental primates, we frequently scan our environments for fellow human beings whom we can trust in specific domains. A lot of what we believe comes from what a relatively small number of trusted sources have simply told us.

In fact, to choose what to see in Cornwall, I looked at the recommendations in The Lonely Planet and Rough Guide. I have come to trust those sources over the years–not for every kind of guidance (they are not deeply scholarly), but for suggestions about what to see and how to get to those places. Indeed, both publications offer lists of Cornwall’s highlights that resemble ChatGPT’s.

How did these publishers obtain their knowledge? First, they hired individuals whom they trusted to write about specific places. These authors had relevant bodily experience. They knew what it feels like to walk along a cliff in Cornwall. That kind of knowledge is impossible for a computer. But these authors didn’t randomly walk around the county, recording their level of enjoyment and reporting the places with the highest scores. Even if they had done that, the sites they would have enjoyed most would have been the ones that they had previously learned to understand and value. They were qualified as authors because they had learned from other people: artists, writers, and local informants on the ground. Thus, by reading their lists of recommendations, I gain the benefit of a chain of interpersonal relationships: trusted individuals who have shared specific advice with other individuals, ending with the guidebook authors whom I have chosen to consult.

In our first two decades of life, we manage to learn enough that we can go from not being able to speak at all to writing books about Cornwall or helping to build LLMs. Notably, we do not accomplish all this learning by storing billions of words in our memories so that we can analyze the corpus for patterns. Rather, we have specific teachers, living or dead.

This method for learning and thinking has drawbacks. For instance, consider the world’s five biggest religions. You probably think that either four or five of them are wrong about some of their core beliefs, which means that you see many billions of human beings as misguided about some ideas that they would call very important. Explaining why they are wrong, from an outsider’s perspective, you might cite their mistaken faith in a few deeply trusted sources. In your opinion, they would be better off not trusting their scriptures, clergy, or people like parents who told them what to believe.

(Or perhaps you think that everyone sees the same truth in their own way. That’s a benign attitude and perhaps the best one to hold, but it’s incompatible with what billions of people think about the status of their own beliefs.)

Our tendency to believe select people may be an excellent characteristic, since the meaning of life is more about caring for specific other humans than obtaining accurate information. But we do benefit from knowing truths, and our reliance on fallible human sources is a source of error. However, LLMs can’t fully avoid that problem because they use text generated by people who have interests and commitments.

If I ask ChatGPT “Who is Jesus Christ?” I get a response that draws exclusively from normative Christianity but hedges it with this opening language: “Jesus Christ is a central figure in Christianity. He is believed to be … According to Christian belief. …” I suspect that ChatGPT’s answers about religious topics have been hard-coded to include this kind of disclaimer and to exclude skeptical views. Otherwise, a statistical analysis of text about Jesus might present the Christian view as true or else incorporate frequent critiques of Christianity, either of which would offend some readers.

In contrast, my query about Cornwall yields confident and unchallenged assessments, starting with this: “Cornwall is a beautiful region located in southwestern England, known for its stunning coastline, picturesque villages, and rich cultural heritage.” This result could be prefaced with a disclaimer, e.g., “According to many English people and Anglophiles who choose to write about the region, Cornwall is …:” A ChatGPT result is always a summary of what a biased sample of people have thought, because choosing to write about something makes you unusual.

For human beings who want to learn the truth, having new tools that are especially good at scanning large bodies of text for statistical patterns should prove useful. (Those who benefit will probably include people who have selfish or even downright malicious goals.) But we have already learned a fantastic amount without LLMs. The secret of our success is that our brains have always been networked, even when we have lived in small groups of hunter-gatherers. We intentionally pass ideas to other people and are often pretty good at deciding whom to believe about what.

Moreover, we have invented incredibly complex and powerful techniques for improving how many brains are connected. Posing a question to someone you know is helpful, but attending a school, reading an assigned book, finding other books in the library, reading books translated from other languages, reading books that summarize previous books, reading those summaries on your phone–these and many other techniques dramatically extend our reach. Prices send signals about supply and demand; peer-review favors more reliable findings; judicial decisions allow precedents to accumulate; scientific instruments extend our senses. These are not natural phenomena; we have invented them.

Seen in that context, LLMs are the latest in a long line of inventions that help human beings share what they know with each other, both for better and for worse.

See also: the design choice to make ChatGPT sound like a human; artificial intelligence and problems of collective action; how intuitions relate to reasons: a social approach; the progress of science.

analytical moral philosophy as a way of life

(These thoughts are prompted by Stephen Mulhall’s review of David Edmonds’ book, Parfit: A Philosopher and His Mission to Save Morality, but I have not read that biography or ever made a serious study of Derek Parfit.)

The word “philosophy” is ancient and contested and has labeled many activities and ways of life. Socrates practiced philosophy when he went around asking critical questions about the basis of people’s beliefs. Marcus Aurelius practiced philosophy when he meditated daily on well-worn Stoic doctrines of which he had made a personal collection. The Analects of Confucius may be “a record of how a group of men gathered around a teacher with the power to elevate [and] created a culture in which goals of self-transformation were treated as collaborative projects. These people not only discussed the nature of self-cultivation but enacted it as a relational process in which they supported one another, reinforced their common goals, and served as checks on each other in case they went off the path, the dao” (David Wong).

To practice philosophy, you don’t need a degree (Parfit didn’t complete his), and you needn’t be hired and paid to be a philosopher. However, it’s a waste of the word to use it for activities that aren’t hard and serious.

Today, most actual moral philosophers are basically humanities educators. We teach undergraduates how to read, write, and discuss texts at a relatively high level. Most of us also become involved in administration, seeking and allocating resources for our programs, advocating for our discipline and institutions, and serving as mentors.

Those are not, however, the activities implied by the ideal of analytic moral philosophy. In that context, being a “philosopher” means making arguments in print or oral presentations. A philosophical argument is credited to a specific individual (or, rarely, a small team of co-authors). It must be original: no points for restating what has already been said. It should be general. Philosophy does not encompass exercises of practical reasoning (deciding what to do about a thorny problem). Instead, it requires justifying claims about abstract nouns, like “justice,” “happiness,” or “freedom.” And an argument should take into consideration all the relevant previous points published by philosophers in peer-reviewed venues. The resulting text or lecture is primarily meant for philosophers and students of philosophy, although it may reach other audiences as well.

Derek Parfit held a perfect job for this purpose. As a fellow of All Souls College, he had hardly any responsibilities other than to write philosophical arguments and was entitled to his position until his mandatory retirement. He did not have to obtain support or resources for his work. He did not have to deliberate with other people and then decide what to say collectively. Nor did he have to listen to undergraduates and laypeople express their opinions about philosophical issues. (Maybe he did listen to them–I would have to read the biography to find out–but I know that he was not obliged to do so. He could choose to interact only with highly prestigious peers.)

Very few other people hold similar roles: the permanent faculty of the Institute for Advanced Study, the professors of the Collège de France, and a few others. Such opportunities could be expanded. In fact, in a robust social welfare state, anyone can opt not to hold a job and can instead read and write philosophy, although whether others will publish or read their work is a different story. But whether this form of life is worthy of admiration and social support is a good question–and one that Parfit was not obliged to address. He certainly did not have to defend his role in a way that was effective, persuading a real audience. His fellowship was endowed.

Mulhall argues that Parfit’s way of living a philosophical life biased him toward certain views of moral problems. Parfit’s thought experiments “strongly suggest that morality is solely or essentially a matter of evaluating the outcomes of individual actions–as opposed to, say, critiquing the social structures that deeply shape the options between which individuals find themselves having to choose. … In other words, although Parfit’s favoured method for pursuing and refining ethical thinking presents itself as open to all whatever their ethical stance, it actually incorporates a subtle but pervasive bias against approaches to ethics that don’t focus exclusively or primarily on the outcomes of individual actions.”

Another way to put this point is that power, persuasion, compromise, and strategy are absent in Parfit’s thought, which is instead a record of what one free individual believed about what other free individuals should do.

I am quite pluralistic and inclined to be glad that Parfit lived the life he did, even as most other people–including most other moral philosophers–live and think in other ways. Even if Parfit was biased (due to his circumstances, his chosen methods and influences, and his personal proclivities) in favor of certain kinds of questions, we can learn from his work.

But I would mention other ways of deeply thinking about moral matters that are also worthy and that may yield different kinds of insights.

You can think on your own about concrete problems rather than highly abstract ones. Typically the main difficulty is not defining the relevant categories, such as freedom or happiness, but rather determining what is going on, what various people want, and what will happen if they do various things.

You can introduce ethical and conceptual considerations to elaborate empirical discussions of important issues.

You can deliberate with other people about real decisions, trying to persuade your peers, hearing what they say, and deciding whether to remain loyal to the group or to exit from it if you disagree with its main direction.

You can help to build communities and institutions of various kinds that enable their members to think and decide together over time.

You can identify a general and relatively vague goal and then develop arguments that might persuade people to move in that direction.

You can strive to practice the wisdom contained in clichés: ideas that are unoriginal yet often repeated because they are valid. You can try to build better habits alone or in a group of people who hold each other accountable.

You can tentatively derive generalizations from each of these activities, whether or not you choose to publish them.

Again, as a pluralist, I do not want to suppress or marginalize the style that Parfit exemplified. I would prefer to learn from his work. But my judgment is that we have much more to learn from the other approaches if our goal is to improve the world. That is because the hard question is usually not “How should things be?” but rather “What should we do?”

See also: Cuttings: A book about happiness; the sociology of the analytic/continental divide in philosophy; does doubting the existence of the self tame the will?

whom to engage: stakeholders, citizens, activists or the community?

Here are four common ways of talking about who should be engaged in decision-making or collective work. Each approach has significant drawbacks.

DefinitionWho decides who they are?Drawbacks
Stakeholders People with specific, identifiable, relevant knowledge, power, commitment or vulnerability. The organizers of a process identify the stakeholders.The organizers retain power and discretion. The process favors people with special “stakes,” who may not represent everyone.
CitizensAll adults who are recognized by the authorities as full members of the jurisdiction, e.g., a country. Normatively, all adult residents have claims to be citizens. In practice, the definition reflects power.One person/one vote does not reflect the real distribution of influence and interests. Realistically, specific stakeholders will set the agenda. Also, people who are not citizens may have valid stakes.
ActivistsMembers of social movements who have obtained visibility and influence through their struggles.Activists identify themselves. However, an individual may not be accepted by a given group and may not then be heard.Since a movement is usually defined by its stance, it cannot represent people with alternative views or those who are neutral or agnostic.
The communityMembers of an affected group who are outside of the system that organizes the process. For instance, the police consider civilians to be the community. Professors consider non-academics to be the community. For the state, the police and the university might be parts of the community.Usually, someone with authority defines the community as an “other.”The abstract idea of a community often devolves to leaders and staff of NGOs or social-movement activists. People who have formal titles may define themselves out of the community, which is a mistake.
The oppressed or marginalized, sometimes named “The People” in left-wing discourse.Members of social groups who are and have been subject to violence, discrimination, dispossession, etc.People with influence over the discourse–perhaps including those who are themselves oppressed. (But usually, powerful people do most of the talking.)A negative definition can be patronizing. Defining someone else as oppressed does not empower them.

See also: citizens, stakeholders, publics, interest groups?; problems with “stakeholders”; and Levine P. (2022), Social Movements and Stakeholder Engagement. In: Lerner D., Palm M.E., Concannon T.W. (eds) Broadly Engaged Team Science in Clinical and Translational Research. Springer