two futures for AI, work, and learning

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AI tools can be designed to accomplish tasks that have been done so far by human workers. Engineers use rubrics to assess and refine the outputs of AI. Their rubrics are often based on human performance. For example, how well does as an LLM perform at writing a contract or allocating investments, compared to a lawyer or an investment advisor? The next version will do it better.

On the other hand, AI tools can (or could) be designed to accomplish tasks that human beings cannot do or truly don’t want to do.

This is a choice. The consequences could be profound.

If AI is designed to replace human work, then we risk a scenario in which many people may get laid off, aggregate growth suffers because those people have less money to spend, the job losses are concentrated among knowledge workers, the benefits of education (broadly defined) shrink, and people lose commitment to developing their own minds.

We could see not only an economic recession but a mental one. For example, a college degree would be worth less on the market, and students would not see the point of challenging themselves to learn. Intelligence is a good, and the market value of human intelligence could slip if there is also a growing supply of artificial intelligence.

This scenario would be bad for business, not only for workers and learners. A consumer-oriented company that replaced all its salespeople, managers, accountants, and so on with machines would also contribute to reducing its own consumer base. That would be a classic Tragedy of the Commons. The only companies worse off than those that cut their own employees would be those that didn’t. Labor’s share of income would shrink, but capital’s slice would also be smaller than it is today.

We are familiar with the story that new technologies replace some workers but also boost productivity, which creates new jobs. The technologies of the Industrial Revolution tended to replace higher-skilled artisans, forcing many workers down the skill ladder. Those people suffered, yet today’s workforce is much better educated and better paid. If AI turns out like steam engines and machine looms, we’ll be OK in the longer run.

Then again, we have never had a technology so relentlessly tunable to replace any worker, even someone in a brand-new occupation. Besides, the tools of the Industrial Revolution displaced skilled artisans but not people who had formal educations, whereas AI seems to threaten the most advanced occupations, even pure mathematicians. That means that there may be no way to escape by learning higher skills.

Reading and math scores fell rapidly all across the world between 2018 and 2022, and then further in 2025:

The PISA report shows that this decline is correlated with AI use. In 2025, it says, “AI chatbots (such as ChatGPT) were used for schoolwork by a majority of students in most participating countries and economies.” But there was variation in how much it was used, and where. “PISA shows that students who do not use AI chatbots for schoolwork generally score higher than students who do, and are more likely to report higher levels of help-seeking behaviours.”(OECD 2026 p. 236)

Specifically, students who never used AI to summarize an assigned text or to draft text for writing assignments scored much higher than those who ever used it for those purposes, whether or not their scores were adjusted for socioeconomic status (fig 1.4.13).

This evidence does not prove causality, but it’s consistent with the concern that AI tools can replace rewarding tasks that human beings have done (such as reading) and even cause a global mental recession. Inventions like railroads and typewriters never lowered reading skills.

It is also worth exploring positive scenarios, in which AI tools are trained and refined by rubrics that ask whether they are accomplishing something valued by humans that humans cannot do or do not want to do. Then we could see economic growth, profits for companies that solve new problems, and positive externalities, such as better health and more learning. The PISA report adds, “among students who use AI for schoolwork for a general purpose (‘to help me learn’), those who report moderate use score slightly higher in PISA than students who use it either rarely or intensively.” I have no doubt that AI tools can help us learn instead of replacing our learning, but this is a matter of design.

I worked with Tufts engineering students to develop a rubric to assess tools like the Civic Helpdesk, asking whether these tools provided useful advice for voluntary groups. To some extent, we imagined experienced community organizers as our models. Thus our tool could replace people, although paid organizers have always been critically scarce. But the Civic Helpdesk can also draft boring documents so that voluntary groups can concentrate on meatier topics. That is an example of freeing people to do more valuable work..

Zeke Emanuel and Vinod Khosla argue that AI tools can perform the algorithmic aspects of medicine (applying “detailed guidelines from professional societies”). In such cases, AI tools would be designed to replace some work by doctors. However, presumably, the same physicians could then concentrate on aspects of medical care that are not resolved by guidelines.

Earlier, I described a race to replace workers with AI as a Tragedy of the Commons. Companies would hurt themselves as well as others by reducing employment, thus shrinking their consumer base.

Problems of collective action require collective solutions–not always governmental regulation (although that is worth considering) but sometimes voluntary collaboration or pressure from organized people.

The current resistance to new data centers may not be the ideal way to counter to Silicon Valley. When residents block a data center in their own community, it will probably be built somewhere else. But such resistance introduces friction that could lead to genuine negotiation.

At a high level of generality, the goal of workers, consumers, and their elected representative should be to press AI companies to refine their tools to perform tasks that people cannot do or truly don’t want to do.

We are very early in the history of widely available AI. It is too soon to tell which path we’re on. Dean Baker sees little evidence of jobs lost to AI yet. He notes that jobs in the insurance industry should be at risk, yet the number of insurance positions shrank by just 2.5 percent in a year, versus an 8.6% decline in manufacturing, which should be less exposed to AI.

On the other hand, the share of GDP that workers capture has fallen since 2000–and sharply since 2020. Brent Neiman writes, “While we can debate about [the causes] over the past five decades, when it comes to the last five quarters, technological change has to be a leading contender in explaining its rapid decline.” He implies that AI already “substitutes for labor”:

The Financial Times’ John Burn-Murdoch shows that the college wage premium (the extra amount of salary that comes with a college degree) has suddenly fallen since 2020 in both the USA and the UK.

This trend could be good news if it meant that people without college degrees were being paid better than in the past. In an equitable world, the college premium would be small. AI could even help make the world more equitable by, for example, helping employers to find fully qualified prospective workers who don’t have expensive college degrees. (See “How AI can advance a skills-first labor market” by Opportunity at Work.)

However, since labor–in the aggregate–has been capturing a smaller share of GDP since 2020, it seems more likely that college graduates are being squeezed by technology. Meanwhile, hundreds of millions of younger children are simply learning less.

Source: OECD (2026), PISA 2025 Results (Volume I): Future-Ready Students, PISA, OECD Publishing, Paris,See also: AI as the road to socialism?; attitudes about AI by age; why the humanities could never be automated; and other posts on AI.

Wendell Berry, September 2

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On September 2, I posted Wendell Berry’s poem with that title on social media, moved that he had just missed the anniversary of the day when, according to the poem, he accepted “decline” and recognized that he would dissolve into “sleep.” The original appeared in Poetry magazine, May 1970. Berry died on August 31 of this year.

I have since spend a bit more time with the poem, and I will offer a few notes in the hope that they may encourage you to give it additional attention. (Berry always invited us to attend.)

It is written in iambic pentameter. There are rhymes: “hawks” and “stalks” get the poem going, and later, “knew” rhymes with “grew”; “as in” with “garden”; and–more loosely–“darkening” with “fading.” I hear the last word of the poem, “flight,” as a rhyme of “light,” although that word came at a caesura in line 10.

Neither the rhythm nor the rhyme scheme is perfectly regular. Nor are rows of sunflowers. But the regularity is sufficient to connect this poem to the tradition of rhymed English iambic pentameter that Chaucer began in the 14th Century. Running to twelve lines, it can be read as variant of a sonnet.

Early September would likely be hot in a place like Kentucky. The poem is set in the evening, when nighthawks hunt for insects, and the “landscapes of the sky” are fading at dusk. These features connect “September 2” to a long tradition of rustic elegy. As one of countless examples, Virgil’s second “Eclogue”:

The shadows lengthen as the sun goes low;
Cool breezes now the raging heats remove;
Ah! cruel heaven, that made no cure for love!
I wish for balmy sleep, but wish in vain ...
           (translated by John Dryden, 1697)

The nighthawks, sunflowers, and garden pull powerfully upward, as suggested by the words “rose,” “tall,” and “straining to the light.” The nighthawks are even “summoned” up. But the final two lines work like the “turn” or concluding couplet in a Shakespearean sonnet. They suddenly describe the narrator’s downward motion.

Berry was, famously, an actual farmer. But the garden in this poem is in his mind. Acceptance grows in his garden, not planned or planted there but naturally arising. He has worked in his mental garden; now he is ready to sleep.

Like most poems, this one should be read as fiction. But it is hard to ignore the fact that Berry had 56 years ahead of him to describe restraint and acceptance after he wrote these lines.

The last phrase is hard: “my leaves all dissolved in flight.” It echoes the sentence that likens the nighthawks to rags tossed in the sky. The birds rise into sight, while the narrator’s leaves dissolve, flying, out of view. But what are they–him? Are they about to fly from their stems when autumn comes?

If his leaves are his writings, I do not think they will soon dissolve.

navigating the social sciences

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Here is a tentative effort to map the social sciences for a novice, such as a student who’s thinking of taking some social science courses. (It is a counterpart to my recent post on the humanities.) I will risk over-generalizations to offer some pointers.

I would start with three familiar cases:

Researchers want to understand and, if possible, predict a situation in which many individuals face a similar choice that is concrete and observable. For example, people can buy a specific good at a given price, apply for a job, pursue a particular kind of education, marry, or vote. Although individuals’ motives and beliefs vary, there is a typical reason that one would do each of these things (e.g., one buys a good to possess it) as well as costs, disadvantages, and competitors. Thus it should be possible to model the whole situation with an equation that shows the outcome on one side of the equal sign. To test the model, we want to collect as much data as possible, and the data tend to be concrete and unambiguous. It may not be necessary to work with samples if data can represent all the relevant behavior, as a price reflects all the recent purchases of a given good or an election tallies all the votes. Economics relies heavily (but not exclusively) or large-scale data that markets generate or that bureaucracies collect for planning purposes. The mathematics that’s most useful includes statistics (especially statistical tools for inferring causality) and calculus, which reveals maximum values subject to constraints.
Researchers want to understand a mental characteristic that is not measurable with a single datapoint. For example, they want to understand anxiety, hand-eye coordination, prejudice, or knowledge of the American Civil War. They will probably study specific human subjects, rather than use data to describe populations, and they will devote attention and ingenuity to deriving measures of unobserved, latent, and/or unconscious characteristics. This is the point of a laboratory test of perception, a multi-item survey that measures an attitude, an in-depth interview, or an exam, which might include graded essay questions along with multiple-choice items. Again, statistics is a useful tool, but now often the main statistical question is whether an individual differs from the mean of a relatively small sample that shows a lot of variation. Qualitative research becomes more prominent. And a different kind of math emerges as useful: factor analysis and related methods that turn many datapoints into scales.
Researchers want to interpret a whole human situation: a cockfight in Bali, adolescence in Samoa, a ceremonial feast in the Pacific Northwest, or indeed, a US high school or a physics lab or a Manhattan apartment building with a doorman. The key questions are what happens and what that means. Often the important happenings (cockfights, gifts, rites of passage, holiday tips) recur regularly and may not seem optional or determined by the individuals’ characteristics, such as their personal desires. Quantitative data become less relevant. Instead, the researcher’s main method is to spend a considerable amount of time in the community, observing intensively and listening to many informants.

The bastions of these approaches are, respectively, economics, psychology, and anthropology. Each discipline arose to study a restricted range of topics and then expanded by applying its favored methods to other topics.

Economists began with markets but have studied topics like voting since at least 1942 (Schumpeter) and probably earlier. Some of the pioneering anthropologists sought to understand what they then called “Man” by conducting ethnographies of people who were presumed to live as early humans had lived. Several assumptions of that approach are now rejected, and ethnography is now applied to all kinds of communities. And psychology emerged from early studies of perception and cognition by people like Wilhelm Wundt (1832-1920) and William James (1842-1910) plus efforts to define and treat mental illnesses by doctors like Sigmund Freud (1856-1939). The discipline now extends to all areas of human and animal life.

As a first approximation, I would say that sociology and political science are not defined by their favored methods; they are methodologically pluralistic. Instead, they are defined by their topics: respectively, society and politics. That said, both make more use of representative surveys of populations than other disciplines do. (Economists would rather work with revealed preferences, and psychologists often intensively study smaller samples.)

Also, economics and psychology are often (not always) methodologically individualist, meaning that they seek to analyze group phenomena as aggregates of individuals’ behavior. But sociology has contributed powerful models and methods that treat other things–such as classes or institutions–as the causes of outcomes. Similarly, political science contributes a focus on power, which can be missing in models that presume that people have psychological traits and choose accordingly.

Unfortunately, I do not read much research in geography, but its unique contribution is spatial analysis. A characteristic tool of geographers is a map. Public health employs many of the methods favored in the other social sciences (including maps), but it addresses diseases and syndromes that affect human beings. “Epidemiology” is derived from the Greek words for “upon the people.” Focusing on non-human factors that are “upon us” requires studying phenomena like contagion and mutation that apply to bacteria and viruses in relation to people.

Disciplines like public policy, communications, and education are methodologically pluralistic and defined by their topics. In fact, some professors of these disciplines hold PhDs in the liberal arts and apply methods that they learned there. However, experts in these fields might rightly emphasize their distinctive approaches to research. For instance, public policy research has a distinctive emphasis on feedback loops (how policies affect society, which then affects policy). And education thinks developmentally.

Finally, history is often classified among both the humanities and the social sciences. A cultural historian who seeks to enrich our perception of human artifacts is very much a humanist. Likewise, a narrative historian who weaves events and intentional action into a nonfiction narrative is humanistic. But it is also possible to employ methods like econometrics and epidemiology to the past, in which case history operates as a social science.

See also: navigating the disciplines (from 2020, with a video); the humanities for specialists and for everyone; against methodological individualism; three cores of contemporary social science (which is worryingly similar to the current post, but written in 2016); is social science too anthropocentric? etc.

Karpowitz and Patterson, The Politics of Individualism

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In The Politics of Individualism (Oxford University Press, 2025), Christopher F. Karpowitz and Kelly D. Patterson make an important contribution by defining a new construct, moral individualism. They show that it is prevalent in the USA and may help explain various concerning outcomes, from resistance to public health measures to low voter turnout.

This post is a short review. Anyone who is attending this year’s Annual Meeting of the American Political Science Association is welcome to an authors-meet-critics session about the book on September 6 from 8:00 to 9:30 am (early on a Sunday morning!) with comments by Michigan’s Yanna Krupnikov, Stanford’s Elizabeth Mitchell Elder, North Carolina’s Marc J. Hetherington, and me.

Karpowitz and Patterson define moral individualism as the conjunction of two beliefs: 1) any “authorities external to the self’ must curtail or abridge a person’s liberty, and 2) “only moral choices that are self-authorized are legitimate” (p. 32).

They measure this construct in nationally representative samples using an ingenious survey design. In part, they ask respondents to name who is most important when they’re deciding how to live their lives or what is best for society. The ten response options include a religious leader, a scientist or expert, and a family member, among others.

Respondents are then asked to evaluate ten statements about how to treat their chosen source, e.g., “Nobody, not even [the favored source] can decide what is right and wrong, except for me” and “The world has many truths, and whatever I learned from [the favored source] is just one of them.”

A moral individualist is someone who does not feel bound by what their own most important sources may say.

Scores on this scale do not correlate strongly with measures of economic individualism, such as “Any person who is willing to work hard has a good chance of succeeding.” Thus economic and moral individualism are not the same construct. Likewise, moral individualism does not have a partisan valence: it is found on both sides of the aisle. It does not correlate strongly with attitudes toward Donald Trump or MAGA.

Moral individualism does, however, correlate with important outcomes, even when other factors are controlled. It predicts lower odds of voting and serving other people, less commitment to family, less religious attendance, weaker sense of efficacy (confidence that one can make a difference), less support for patriotism, much less support for public health measures during COVID, and more suspicion that other people were violating COVID restrictions. Controlling for party, ideology and support for Donald Trump, moral individualism correlated with less opposition to the riot on January 6.

Traditionally, governments have tried to counteract moral individualism. For example, public schools and colleges (as well as private and parochial ones) not only instruct students to honor various external authorities–from the Constitution to science–but they also present the school itself as something that should be honored. Military recruitment campaigns often emphasize one’s duty to country. In WWI, Uncle Sam said, “I want you for U.S. Army!” Karpowitz and Patterson trace the evolution of the all-volunteer Army’s slogans from the communitarian “Join the People Who Have Joined the Army” (1973-1980) through “Be All You Can Be” (1980-2000) to the individualistic “Army of One” (2001-6).

State-supported efforts to combat moral individualism may not work today and could provoke a backlash. Indeed, there may be legitimate debates about whether and in what ways moral individualism is a public problem. Moral individualism correlates with outcomes like religious attendance and patriotism–but also voting and political confidence–which may concern some of us but not others.

In any case, institutions apart from the government have stakes. For example, the statements that measure moral individualism are explicit rejections of the various kinds of authority that religions tend to claim, and (as noted) the construct correlates with lower church attendance. So religions might want to work against moral individualism.

I couldn’t improve on the authors’ analysis of the American population (by way of large samples). But I am curious about distinctions that might emerge in more intensive qualitative studies, particularly if the samples included relatively thoughtful and self-conscious subjects. I think that people who are moral individualists could differ on dimensions captured by three broad questions:

1. To what extent are you concerned about other people’s moral autonomy?

You can believe that your life is your own business and that no one should interfere with it. That belief can be the basis for not feeling compelled to do anything for anyone else. Or you can believe that you and all other humans have the right to be the authors of their own lives and that this principle is worth fighting for.

Let’s say you are an American who believes that every human being has a right to moral autonomy. You should probably conclude that your own moral autonomy is pretty extensive and safe but that other people (from those incarcerated in US prisons to all citizens of North Korea) are not able to decide for themselves what is right. This is a reason to work and even sacrifice to enhance all people’s moral autonomy.

Karpowitz and Patterson ask people to respond to the statement, “Only I can decide what is right. I cannot even trust [my preferred source] to help me decide.” I am curious whether respondents would say that other people should also be allowed to decide what is right for them (most Americans would probably agree so far) and that they have an obligation to defend other people’s freedom (which would probably be rarer). This distinction would divide selfish or egoistic moral individualists from altruistic ones.

2. How demanding is it to decide for yourself what is right?

Karpowitz and Patterson ask for responses to this prompt: “My own judgment is more important than [my favorite source’s] judgment.” Moral individualists agree with that statement.

But what must an individual do to make a judgment? Some people may think of judgment as synonymous with “preference” or even “desire.” Nothing should be binding on me except what I happen to want. But at least some people may think that the burden to decide what is right falls on the individual and is a heavy one.

In breaking with the Catholic Church, Martin Luther upheld the individual obligation of each sinner to discern the actual truth. He was not relativistic or morally permissive (at all) but was a kind of moral individualist.

Michael Foucault defined spirituality as “the search, practice, and experience with which the subject carries out the transformations on himself that are necessary to have access to the truth” (Foucault 1982). According to practitioners of spirituality, to know the truth, one must make oneself deserving of it, which may require intensive study, prayer, meditation, confession, direct engagement with the original Word, or even fasting and self-mortification.

To be sure, spiritual practices can be collective, but they can also be individual or even solitary. Science, on the other hand, presumes that truth arises from organized, transparent, cumulative work that does not require any particular kind of spiritual preparation. Thus we might imagine that some serious practitioners of spirituality are moral individualists, whereas scientists should not be.

We could divide moral individualists between those who think that deciding what is right is hard and those who think it comes automatically. Emerson, cited several times in the book as a moral individualist, may also be a serious spiritual striver, in the way that Foucault means.

3. What is the role of other people in supporting your moral individuality?

Reformation theologians offered a particular kind of moral individualism when they preached the Priesthood of All Believers and the doctrines of Faith Alone and Scripture Alone. They removed the mediation of the organized Church, claiming that each believer stands alone before God.

The question then arose: Why should there be Protestant churches at all? The dominant answer was that although each person is ultimately responsible, we need other people’s support. Someone who holds this view might agree with this item in Karpowitz and Patterson, “My own judgment is more important than [my favorite authority’s] judgment,” even if they’ve chosen their pastor as their authority. God judges you as an individual, weighing your personal faith; you get no points from the clergy’s behavior. Nevertheless, most Protestants have assumed that they are more likely to find their way to truth and good behavior if they belong to an organized community whose congregants and leaders can give them reminders and encouragement.

In sum, I think that moral individualism could be compatible with some altruistic, introspective, and communitarian values. I suspect that those combinations are rare and that most Americans who score high on Karpowitz’ and Patterson’s scale are also selfish, unreflective, and isolated. But the exceptions might be important.

Source: Michel Foucault, L’herméneutique du suject: cours au Collège de France (1981-2) (Gallimard, 2001), pp. 16-18. See also: the classical liberals versus the “egoists”; bootstrapping value commitments; Foucault’s spiritual exercises; why be introspective? etc.

How Do We Renovate American Democracy at the 250th?

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You might think that the USA must change deeply over the next decade, which will unfold 250 years after the decade in which our republic originally took shape and will include the first eight years after the Trump Administration.

You might also think that this change should be “civic.” Perhaps we need reforms to make our republic and society more civic, or we should change our economy, environment, and other aspects of our world in civic ways–or both.

To advance this conversation, we need sharper definitions of the word “civic” and concrete ideas about what civic reforms should look like in the late 2020s and 2030s.

One of the best places to look is the new special issue of Daedalus entitled “How Do We Renovate American Democracy at the 250th?” It grew out of the Commission on the Practice of Democratic Citizenship and is edited by Danielle Allen, Stephen B. Heintz, and Eric P. Liu. It is entirely open-access. I have not yet read every article, but all the contributors are excellent, and the topics are compelling, ranging from congressional reform to high school civic education, from local journalism to tech. platforms.

I offer the concluding contribution, entitled “Building Institutions to Improve Civic Culture.” The abstract says:

Americans must disagree better to sustain a healthier civic culture. This is not only a matter of individual behavior and values but also a question of institutional design. An example of an institution that generally supported disagreement, conversation, and collaboration in the twentieth century was the metropolitan daily newspaper, but its business model has collapsed. To recover civic culture, we need business models (defined broadly) for new institutions that can enable discussion and self-governance.

In the article, I actually argue that disagreeing well is insufficient. We must also produce and protect common-pool resources. For me, that combination comes close to defining the word “civic.”

To quote a bit more from my piece:

I think the main challenge of our moment is to develop civic organizations that can flourish and grow, teach civic skills and values, and serve as venues for constructive disagreement. The “upswing” that furnishes the title of the book by Robert Putnam and Shaylyn Romney Garrett, … was an impressive period of innovation and expansion in U.S. civil society from 1900 to 1960.6 If we saw a similar civic renaissance today, not only would more people participate in familiar groups that discuss issues and manage common-pool resources (such as congregations and other traditional associations) but new forms would emerge to meet the needs of our time.

For example, during the period that Putnam and Romney Garrett label “the upswing,” reliable daily newspapers became prevalent in the United States. By 1972, 69 percent of Americans told the General Social Survey (GSS) that they read a newspaper “every day.”7 It is easy enough to envision a daily publication about serious matters, written by professionals to inform a whole community. The hard part is the business model. Why would many people pay for such a product? The recipe that sustained metropolitan daily newspapers during the 1900s included hard news plus human-interest stories, comics, sports, gossip, and other features aimed at various members of each household, all funded by a combination of revenue from subscribers and occasional readers and advertisers. Once the internet captured advertising revenue, this model disintegrated. By 2014, just one-quarter of respondents told the GSS that they read a newspaper daily; the GSS subsequently retired the question, as it ceased to be a useful measure of news consumption.

Also during the upswing, many colleges and universities offered some measure of civic education while contributing knowledge and culture to their communities and serving as significant venues for public debate. Universities collected state subsidies, tuition, philanthropy, and clinical fees, and they offered economic mobility, access to licensed professions, ambitious research prized by industry and the military, vigorous social life, and quasi-professional sports, along with civic benefits. This model is now under considerable stress, though it has not fully collapsed, as with the daily newspaper.8

Similarly, Putnam and Romney Garrett show that after 1910, high schools rapidly spread across the United States and became another pillar of civic culture, not only preparing students to be more capable citizens but also serving as foci for adult community life.9 No national policy made this happen. Instead, most communities found that they needed at least one high school to be economically competitive, and they taxed themselves to build and maintain their own schools. This model worked in many localities, although spending was never adequate in poor communities or for students of color. This model survives, notwithstanding consolidations that have removed high schools from some smaller towns and growing state subsidies for private schools.

Today, it is not hard to envision a social media platform that serves as an excellent venue for disagreeing well. Any platform must use an algorithm to decide what material each user sees, and a good algorithm would favor substantiative content from a deliberately diverse range of views. The question is how to capitalize such a platform so it can expand to rival the huge for-profit social media outlets of the present, which do the opposite for billions of users, favoring material that induces outrage and reinforces users’ prior assumptions. In other words, the problem is the same as the one that confronted proponents of professional journalism circa 1900, but we haven’t yet found a workable business model for our time.

Source: Peter Levine, “Building Institutions to Improve Civic Culture,” Daedalus 155(3) Summer 2026, pp. 203-207. See also: Putnam and Garrett, The Upswing (a video discussion with me).