Christopher Mims predicts that artificial intelligence will increasingly put white collar, professional workers out of work. That means people who blog. 🙂 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.
Professor Marvin Minsky of MIT died at 88 on Sunday January 24. He was one of most important scientists in artificial intelligence (AI): a field of research studying how to develop computers that simulate human thought and behavior. Minsky founded the world’s first AI Lab at MIT in 1959, along with John McCarthy.
Minsky was my undergraduate thesis advisor at MIT, and what I remember most about him was his fascination with music. I graduated in 1982 with a degree in computer science, and I did my thesis research on Minsky’s “Music Cognition” project. His grad student David Levitt was my manager, and we worked on the first-ever screen-based music composition editor. You can display sheet music on any computer these days, but in 1981 home computers could only display white letters on a black background. The AI Lab had radically different computers, with bitmap screens that could display pictures; text in different typefaces and point sizes; pull-down menus; everything controlled by a mouse (with three buttons). These advanced graphics allowed us to display music notation, and allowed composers to edit music on screen.
(BTW it wasn’t the Xerox PARC smalltalk computer, that Steve Jobs famously “borrowed” to create the Apple Mac; our computers were invented and built at MIT and they were called LISP machines.)
Minsky often worked together with Seymour Papert, the MIT professor who developed the LOGO programming language for children. They both worked in the same building in Tech Square (in Cambridge’s Kendall Square); the AI Lab was on the 9th floor and the LOGO lab was on the third floor. One day on my way down in the elevator, I decided to stop at the third floor to check it out; that was the one time I met Papert and saw the original plexiglass LOGO robot.
Back in the early days, computer scientists were idealistic; they believed in open access to everything and everyone. For example, no one’s personal files were password protected. Because I used the same computer as Dr. Minsky, I could access his folders and read every document he was working on. In 1981, I went into his folders and discovered a draft of his book Society of Mind (it wasn’t published until 1985). The book argued that intelligence emerges from the interaction of many smaller, non-intelligent entities inside the mind–something like a “society”. This concept made a huge impact on me, and I kept thinking about emergence and complex systems for two more decades. In 2001, I published my first journal article on the topic, “Emergence in sociology,” and in 2005, I published a book exploring these ideas, Social Emergence: Societies as Complex Systems.
That’s the kind of influence a great scholar has on the world–it lasts for decades.