What makes popular academics popular?

While most academics work in obscurity, we still show up in the media more than most professions, and a few of us approach genuine celebrity status. What makes these outliers so popular?

An article in the latest New Yorker on the Jordan Peterson phenomenon makes for an interesting case study, particularly as he suddenly became internet-famous in his mid-’50’s following relative obscurity in his field and with the public.

Popularity outside the field often stems from success within it; winning a Nobel, for instance, guarantees a lot of coverage. But some academics succeed wildly with the public following an indifferent reception by their peers, as Peterson shows. He has other features common to popular academics- working on topics that a lot of people find accessible and interesting, and speaking with confidence that borders on hyperbole (most of us might as well be in a competition for ‘most nuanced’).

Another important example, especially for people who aren’t already at the top of their fields, seems to be focusing on a new communication technology that the more established players aren’t using yet. A lot of current public intellectuals are those who jumped into blogging, podcasting or Twitter early and put a lot of time and effort into it. In economics, Tyler Cowen has succeeded best at converting this internet popularity into the trappings of more traditional public-intellectual success: best-selling books and New York Times columns.

Of course, now blogging, podcasting and Twitter are relatively saturated, and no longer present such an opportunity for those that aren’t already well-known. Oddly for a platform that most Americans use, Facebook still seems underused as a platform for reaching people you don’t already know; in economics, Robert Reich seems to have gained popularity by realizing this, along with a good dose of hyperbole. For Peterson, the underused platform was Youtube- again, hugely popular but not really used by academics to popularize their work.

The most under-appreciated reason for why most academics aren’t popular is probably that most simply don’t want to be. Either they don’t see fame as a positive, or they recognize that if they get lots of attention, much of it is likely to be negative. At a minimum, anyone with much internet presence is guaranteed to get criticized in the comments, and often in the main articles. Perhaps more importantly for academics, while a few media mentions increase your standing in the field, getting too popular with the public and the press is a near-universal recipe for having your own field turn on you. This can be from jealously, envy, disappointment that you are taking time away from “real work”, or the perception that you are using too much dumbing-down and hyperbole. For instance, economists often express disappointment in Paul Krugman’s journey from great economist in the 1980’s, to good economist and good public intellectual in the 1990’s, to not-an-economist and famous-but-mediocre pundit after turning up the hyperbole in the 2000’s.

Paul Krugman, Slavoj Zizek, Neil Degrasse Tyson, Jared Diamond, Niall Ferguson, Stephen Pinker…. you can debate how much the hate is deserved vs misplaced but it is always there. For Peterson it has come with unusual speed and intensity. Is it that his hyperbole and dumbing-down is really worse than other celebrity psychologists or self-help types? Is it his “anti-radical-left” political stances? Much of it seems to stem from his audience being primarily young men. Focusing on an audience largely ignored by other academics is part of how he succeeded in the first place; most of us are targeting middle-aged NYT-reading, NPR-listening types, without explicitly realizing it of course.

The easiest way to win is always to be playing a different game than everyone else.

Personally, I hope to do work that people will find interesting enough to read and discuss, but this level of fame does not seem appealing.

Where Academics Succeed, Where We Fail

Holden Karnofsky’s take from the latest 80,000 Hours podcast on where academics provide the most value and where they could be doing much better aligns a lot with my own, especially as I get ready to write a book that will sum up a lot of the cutting-edge work others have done on US healthcare and try to explain what it all means. Added emphasis is my own:

I used to have this very simplified, “Academia. That’s like this giant set of universities. There’s a whole ton of very smart intellectuals who knows they can do everything. There’s a zillion fields. There’s a literature on everything, as has been written on Marginal Revolution, all that sort of thing.” I really never know when to expect that something was going to be neglected and when it wasn’t. It takes a giant literature review to figure out which is which.

I would say I’ve definitely evolved on that. I, today, when I think about what academia does, I think it is really set up to push the frontier of knowledge, the vast majority, and I think especially in the harder sciences. I would say the vast majority of what is going on in academic is people are trying to do something novel, interesting, clever, creative, different, new, provocative, that really pushes the boundaries of knowledge forward in a new way. I think that’s really important obviously and great thing. I’m really, incredibly glad we have institutions to do it.

I think there are a whole bunch of other activities that are intellectual, that are challenging, that take a lot of intellectual work and that are incredibly important and that are not that. They have nowhere else to live. No one else can do them. I’m especially interested, and my eyes especially light up, when I see an opportunity to … There’s an intellectual topic, it’s really important to the world but it’s not advancing the frontier of knowledge. It’s more figuring out something in a pragmatic way that is going to inform what decision makers should do, and also there’s no one decision maker asking for it as would be the case with Government or corporations.

To give examples of this, I mean I think GiveWell is the first place where I might have initially expected that there was going to be development economics was going to tell us what the best charities are. Or, at least, tell us what the best interventions are. Tell us is bed nets, deworming, cash transfers, agricultural extension programs, education improvement programs, which ones are helping the most people for the least money. There’s really very little work on this in academia.

A lot of times, there will be one study that tries to estimate the impact of deworming, but very few or no attempts to really replicate it. It’s much more valuable to academics to have a new insight, to show something new about the world then to try and nail something down. It really got brought home to me recently when we were doing our Criminal Justice Reform work and we wanted to check ourselves. We wanted to check this basic assumption that it would be good to have less incarceration in the US.

David Roodman, who is basically the person that I consider the gold standard of a critical evidence reviewer, someone who can really dig on a complicated literature and come up with the answers, he did what, I think, was a really wonderful and really fascinating paper, which is up on our website, where he looked for all the studies on the relationship between incarceration and crime, and what happens if you cut incarceration, do you expect crime to rise, to fall, to stay the same? He picked them apart. What happened is he found a lot of the best, most prestigious studies and about half of them, he found fatal flaws in when he just tried to replicate them or redo their conclusions.

When he put it all together, he ended up with a different conclusion from what you would get if you just read the abstracts. It was a completely novel piece of work that reviewed this whole evidence base at a level of thoroughness that had never been done before, came out with a conclusion that was different from what you naively would have thought, which concluded his best estimate is that, at current margins, we could cut incarceration and there would be no expected impact on crime. He did all that. Then, he started submitting it to journals. It’s gotten rejected from a large number of journals by now. I mean starting with the most prestigious ones and then going to the less.

Robert Wiblin: Why is that?

Holden Karnofsky: Because his paper, it’s really, I think, it’s incredibly well done. It’s incredibly important, but there’s nothing in some sense, in some kind of academic taste sense, there’s nothing new in there. He took a bunch of studies. He redid them. He found that they broke. He found new issues with them, and he found new conclusions. From a policy maker or philanthropist perspective, all very interesting stuff, but did we really find a new method for asserting causality? Did we really find a new insight about how the mind of a …

Robert Wiblin: Criminal.

Holden Karnofsky: A perpetrator works. No. We didn’t advance the frontiers of knowledge. We pulled together a bunch of knowledge that we already had, and we synthesized it. I think that’s a common theme is that, I think, our academic institutions were set up a while ago. They were set up at a time when it seemed like the most valuable thing to do was just to search for the next big insight.

These days, they’ve been around for a while. We’ve got a lot of insights. We’ve got a lot of insights sitting around. We’ve got a lot of studies. I think a lot of the times what we need to do is take the information that’s already available, take the studies that already exist, and synthesize them critically and say, “What does this mean for what we should do? Where we should give money, what policy should be.”

I don’t think there’s any home in academia to do that. I think that creates a lot of the gaps. This also applies to AI timelines where it’s like there’s nothing particularly innovative, groundbreaking, knowledge frontier advancing, creative, clever about just … It’s a question that matters. When can we expect transformative AI and with what probability? It matters, but it’s not a work of frontier advancing intellectual creativity to try to answer it.

A very common theme in a lot of the work we advance is instead of pushing the frontiers of knowledge, take knowledge that’s already out there. Pull it together, critique it, synthesize it and decide what that means for what we should do. Especially, I think, there’s also very little in the way of institutions that are trying to anticipate big intellectual breakthroughs down the road, such as AI, such as other technologies that could change the world. Think about how they could make the world better or worse, and what we can do to prepare for them.

I think historically when academia was set up, we were in a world where it was really hard to predict what the next scientific breakthrough was going to be. It was really hard to predict how it would affect the world, but it usually turned out pretty well. I think for various reasons, the scientific landscape maybe changing now where it’s … I think, in some ways, there are arguments it’s getting easier to see where things are headed. We know more about science. We know more about the ground rules. We know more about what cannot be done. We know more about what probably, eventually can be done.

I think it’s somewhat of a happy coincidence so far that most breakthroughs have been good. To say, I see a breakthrough on the horizon. Is that good or bad? How can we prepare for it? That’s another thing academia is really not set up to do. Academia is set up to get the breakthrough. That is a question I ask myself a lot is here’s an intellectual activity. Why can’t it be done in academia? These days, my answer is if it’s really primarily of interest to a very cosmopolitan philanthropist trying to help the whole future, and there’s no one client and it’s not frontier advancing, then I think that does make it pretty plausible to me that there’s no one doing it. We would love to change that, at least somewhat, by funding what we think is the most important work.