What Will We Do After AI Takes Our Jobs?

Christopher Mims predicts that artificial intelligence will increasingly put white collar, professional workers out of work. That means people who blog. ūüôā Muriel Clauson, of Singularity University, says “Education is often touted as the answer to the skills gap, but it is generally a blunt instrument.” She recommends this system:

First, break down every job into the smallest tasks. Then, figure out which of those tasks can be automated. The jobs that include those tasks are the ones at risk.

Second, assess what skills each person has, and compare those skills with the tasks, across all of the jobs, that can’t be automated. That would give you a pretty good idea of how to match up people with the remaining jobs. Each person would probably be missing a few of the tasks for any given job, so this “task mapping” assessment system would tell you how to design universities and other educational organizations.

I’ve always been nervous about designing education based on what jobs currently exist. It’s because today’s jobs¬†are always going away, or transforming, and new jobs are emerging all the time. Those new jobs often involve new “tasks” that wouldn’t show up using any system based on today’s jobs. So the real challenge faced by education reformers, and education researchers like myself, is: What are the deeper, higher level skills that apply broadly across a wide range of tasks? Those are the skills that make you adaptable, ready to grow and change with the economy.

Are You Too Old to Be Brilliant?

When are brilliant scientists the most brilliant? What age are you likely to be when the Nobel committee comes calling? Pick one of the following answers:

  • You need a lot of expertise and wisdom to make a big breakthrough. You need professional connections, lots of research money, and big laboratories.¬†Scientific breakthroughs come from people in middle age, or maybe even at the end of their careers.
  • It’s the young upstarts who have lots of energy and fresh ideas. After all, the old scientists are stuck in ideas from the past. They’re already past their prime. They’re tired and don’t have much energy any more. Am I talking about myself at the ripe old age of 56? I didn’t get much sleep last night, and my knees are kind of sore¬†ūüôā

A new study gives us the answer: None of the above. There’s no relationship between age and creative scientific contribution. The authors of the study analyzed 2,856 physicists, working from 1893 to the present. They found that the best predictor of exceptional creativity is productivity. It’s lots of hard work. The scientists who do the most experiments, and test the most hypotheses, are the ones with the big contributions. The researchers found that once they’d controlled for productivity, age doesn’t add any additional predictive power.

The researchers identified a second variable that’s related to scientific impact: They called it Q, and it includes intelligence, motivation, openness to ideas, ability to write well. Another surprise: The variable Q doesn’t change over your career. (Otherwise, you’d be back to the theory that age predicts creativity.)

It’s still true that younger scientists are more likely to make a significant contribution. But it’s not because¬†a person has more¬†brilliant insights in your 20s, and it’s not because their ideas are fresh and unbound by old-fashioned tradition. It’s¬†because they work harder and¬†that’s why they’re more productive. So if you’re older, there’s still hope.

Now if only I could get a good night’s sleep.

Free Improvisation in Music Groups

There’s almost no research on group musical improvisation, and I’ve wondered about that for years. I’m a jazz pianist, and I’m fascinated by how different people can come together, and collectively create something that no one could have thought of alone.

So I’m excited to see a new study, of group free improvisation in music trios.* Two of my most respected British colleagues co-authored the study: Graeme Wilson and Raymond MacDonald.

They brought together 3 trios of improvising musicians, from Scotland and the North of England. The musicians were from a range of backgrounds, including voice and electronics. And just for extra measure, they also studied 2 more trios of visual artists who work with sound performance. The trios improvised in a studio for about five minutes. Then, the researchers interviewed each performer separately, replaying the tape of their improvisation, and asking them to explain “what they understood to be communicated by their own and other improvisers’ contributions” (p. 1032).

The main finding was that the musicians spent a lot of time thinking about whether to “maintain” what they were playing, or to “change” to something different. If they decided to change, either it was an initiation on their part, or a response to someone else’s contribution. ¬†This is an “active and iterative” process.

If a change was a response, it was either an¬†adoption (doing something really similar to the other musician’s initiation), an¬†augmentation (adopting one element of the partner, but modifying another element), or a¬†contrast (play something really different, but that’s complementary). Here’s the bottom line:

The representation is of an open-ended iterative cycle where all choices lead to a subsequent reconsideration, with each trio member constantly “scanning” the emergent sound of the piece and actions of their collaborators. The improvisation was sometimes characterized by interviewees as an external entity or process, within which events arose independently of those creating it. (p. 1035)

That’s exactly my own experience with group improvisation, and in my own research, every musician that I interviewed spoke in very similar terms, about iteration, interaction, and the emergence of something greater than the individual musicians.

* Wilson, Graeme B., Macdonald, Raymond A. R. (2016). Musical choices during group free improvisation: A qualitative psychological investigation. Psychology of Music, 44(5), 1029-1043.

Creativity is not Localized in the Brain

If you’ve read the chapter on brain imaging in my book Explaining Creativity, you’ll know that the technology has limitations. Specifically: There’s no way to use this research to claim that creativity is located in a particular part of the brain. To their credit, the researchers who do this work would never say that. However, the media tend to hear about these cautious and limited findings, and publish articles with titles like “Now we know where creativity is!”

A new article in The Economist describes these limitations:

The technology has its critics. Many worry that dramatic conclusions are being drawn from small samples (the faff involved in fMRI makes large studies hard). Others fret about over-interpreting the tiny changes the technique picks up. A deliberately provocative paper published in 2009, for example, found apparent activity in the brain of a dead salmon.

The Economist article is about a new study that identifies a serious problem with fMRI methodology. The new study’s findings suggest that the statistics programs that interpret the fMRI results are “seriously flawed.” (And there’s a lot of statistics involved; take a look at my chapter for a quick summary.) The researchers used these fMRI algorithms¬†to compare 499 subjects who were lying in the scanner while not thinking about anything in particular. With the standard fMRI statistical software, they divided this subject pool in half in 3 million different ways, and did comparisons each time. There shouldn’t have been any findings at all. But in fact, 70 percent of the 3 million comparisons resulted in false positives. That means, in 70 percent of these comparisons, there was a statistically significant finding of elevated brain activity, in half of the 499 subjects,¬†in some part of the brain.

Because this study was just published, we can’t yet be sure what it really means. But my advice is: Be skeptical if you read an article claiming that creativity is located in a particular brain region. Creativity is a function of the entire brain, working together.

Sawyer keynote at IDEAS conference in Calgary, Canada

I just delivered the keynote address “Educating for Innovation” at this big event in Calgary, with teachers, school leaders, education professors, and policy types:

2016 Calgary photo

After the keynote, I did a breakout session where I shared my research on how art school professors teach. Then, I asked the audience to work in small groups to apply these practices to their own teaching in math and science. They all had great ideas about how to teach for creativity! The lessons from art and design pedagogy are really powerful.

Books About Complexity and Emergence

I thought the market for complexity books had been saturated, but here’s another one:¬†A Crude Look at the Whole¬† by John H. Miller. (WSJ¬† review here.)

The first wave of complexity books was in the mid 1990s:

The heyday of complexity books was just after 2000 (my own book appeared in 2005):

In just the past few years, we have

According to Ronald Bailey’s WSJ¬† review, Miller’s book covers familiar ground. Like my 2005 book, he argues that “societies are complex systems”;¬†that¬†social phenomena “emerge unpredictably from components”; that “simple parts interact in complex ways to create an emerging whole”. His examples of emergence from complexity¬†are familiar from these earlier books: biological evolution, markets, the Internet, political protests. Bailey’s review is politely critical of the book;¬†he says “it’s hard to see how complexity science is much help to current policy makers or citizens.” I disagree; I think that understanding complexity and emergence has incredible value, especially in understanding social systems. Maybe¬†Miller’s book isn’t the first one you should read, but the long list of earlier books (and their strong sales)¬†demonstrates that this research is helping lots of people.