AI and Human Happiness

Tyler Cowen interviews Arthur Brooks:

Arthur Brooks reckons he’s on the fourth leg of a spiral-shaped career: French horn player, economist, president of the American Enterprise Institute, and now Harvard professor and evangelist for the science of happiness. His new book, The Meaning of Your Life: Finding Purpose in an Age of Emptiness, argues that happiness isn’t a feeling but a combination of enjoyment, satisfaction, and meaning — the macronutrients of happiness, he calls them — and that most of us are gorging on the wrong ones. Tyler, naturally, wants to know: what’s the marginal value of a book on happiness, and what does spiral number five look like?

Along the way, Tyler and Arthur cover how scarcity makes savoring possible and why knowing you’ll die young sharpens the mind, what twin studies tell us about the genetics of well-being and why that’s not actually depressing, the four habits of the genuinely happy, the placebo theory of happiness books, curiosity as an evolved positive emotion, the optimal degree of self-deception, why Arthur chose Catholicism rather than Orthodoxy, what the research says about accepting death, how he became an economist via correspondence school, AI’s effect on think tanks, the future of classical music, whether Trumpism or Reaganism is the equilibrium state of American conservatism, whether his views on immigration have changed, what he and Oprah actually agree on, which president from his lifetime he most admires, Barcelona versus Madrid, what 60-year-olds are especially good at, why he’s reading Josef Pieper, how he’ll face death, and much more.

The AI and happiness segment from all that is below the asterisks. And I've added a coda about AI and asking the right question. Oh, and the sharp right-brain/left-brain stuff seems a bit old. 

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COWEN: How will artificial intelligence influence politics and the political spectrum? Easy question, right?

BROOKS: It’s a good question. I agree. One of the questions I get mostly, as you can imagine, because of my work, is how is it going to affect happiness? I’ve been thinking about it an awful lot. We discussed a minute ago the hemispheric lateralization theory of Iain McGilchrist, that the right side of the brain is the mystery and meaning and why questions of life, and the left hemisphere of the brain largely adjudicates the what and how to and engineering and technological questions of life. The problem is that in modern society, we’ve been kicking everybody into the left hemisphere of the brain and walling off the right hemisphere because people spend all day on their screens, and the hustle and grind-engineered Silicon Valley culture that we live in has actually eliminated a lot of the mystery and meaning from life and the incentive to actually ask those questions.

That’s a lot of what my new book is about, is how to get back to the right side of your brain, as a matter of fact. Now, AI is a magnificent extension of the left hemisphere of your brain. It’s a how-to and what engine, but it’s not a why engine. Any real why question that matters, you can’t put into ChatGPT and get something meaningful to you to say, “Why am I alive? For what would I be willing to give my life?” You put that into ChatGPT, it’ll start by buttering you up and telling you what a smart question it is, and then it’ll tell you how five different people have answered that question, and you’re left completely unsatisfied as a result of that.

The answer to the basic happiness question, which is an adjunct, which is next to the political questions, I think, is that if you use it for left brain things to free up your time and then go over to the right brain side of your life with your love and your faith and your relationships and beauty and suffering, then your life’s going to get better. It’s a very real possibility, Tyler, that this is what’s going to happen in economics and politics today.

If we went back 150 years or a little bit more, people would say, “Oh, the Industrial Revolution is going to permanently ruin society because it’s urbanizing and people don’t know each other and the traditional folkways are going away.” It had some rough transitions, to be sure, by bringing in market economics and division of labor and specialization, et cetera. The end of the day was a middle class and the weekend. That’s not the fruit of labor unions. That’s the fruit of the Industrial Revolution and the amazing largesse that it created through capitalism.

COWEN: That took a long time, right? This may be 70 years at the interim. What’s our interim going to look like? Will it be more nostalgia and more small-C conservatism?

BROOKS: Yes. I think it will be. I think this will be speeded up. I think within 20 years that we will have something like the post-industrial equivalent of the fruit that was wrought by the Industrial Revolution, that that’s what we’ll see from what’s going on today.

COWEN: Do you think the classical liberal view on AI should be that we don’t much regulate it or that we regulate it like a national security object, the way we might regulate atomic bombs?

BROOKS: I don’t know. I’m wrestling with that, and I don’t know the answer. Can you give me your opinion, please? Otherwise, I’m going to have to just go to your blog and look at it and form my own opinion on the basis of that.

COWEN: I think for now, we don’t know how to regulate it, and it’s changing more quickly than Congress can act intelligently. Maybe Congress cannot, at the moment, act intelligently at all. I’ll say hold off, but leave open the option because we might need to in some important ways.

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COWEN: How long from now do you think it will be before an AI model with good prompting will write a better policy study than, say, the 70th percentile quality study from a good think tank?

BROOKS: That’s a good question. I think AI at not-too-distant future, will do a better job at executing policy analysis, but will do a very poor job at asking the right policy questions. I think that that’s going to be the comparative advantage, is the creativity and the human impulse, the curiosity that humans actually bring to it. The reason is because all large language models are being trained to what people have already done, ideas that people have already had.

What we’re incredibly good at using the right hemisphere, the why hemisphere of our brain, is asking new why questions, which actually leads us to the creativity that we’ll ask the best policy questions going forward. That’s what we’re going to have to specialize in—you, me, and everybody else in the space.