Hazardous to your health
A Tale of Torn Tendons

27 April 2016 S-14 D

I went out for my constitutional 3-to-5k, almost daily run, carefully avoiding all the roots and rocks on my wooded route. Then, I came home, puttered around a bit and, crash, tripped on step. There was excruciating pain, but only for maybe 15 seconds or so. It still hurt quite a bit to move during the next few days, especially getting up to a vertical position, but I wasn't too concerned when my heath care provider said it would be more than two weeks before I could see a doctor.

I staggered over to my classes using my father-in-law's second-best walker and announced to my students I had a “sports-related injury,” confessing that I tripped on a step. It seemed much less embarrassing, somehow, to speculate that it was a “sports-related injury,” and because it was right after running, Karen (spouse) assures me there was a connection.

5 May 2016 S-6 D

Then, just to be sure I had nothing more than strained quadriceps, I called again, hoping I could get an appointment at least with a nurse. But then, I was granted a miracle: there was a cancelation; I could see a real-live doctor!

My escort to the examination room asked what happened. “Oh, I strained my quads playing rugby,” I said, followed immediately by “just kidding.”

The examination didn't go well. The doctor poked around a little, seemed upset that he couldn't get a patellar reflex, and sent me to the emergency room. When I got there they wanted to know if I had chest pain. I said no and wanted to say I was anticipating a pain in another body part.

Curious onlookers kept looking at me in my ER cubicle. I later found that the rugby story had made it into the record.

I flunked a certain strength test, so I was scheduled for an MRI next day. I thought that would be like an x-ray. Maybe a few minutes to get set up and a second or two of beam. The operators thought it would take an hour a leg, but I was good at holding still so it only took an hour total. The machine sounded like a jackhammer most of the time.

A few hours later came the bad news: transected quadriceps tendons, both legs. Sounds bad. I prefer “torn.” The surgeon (terrific) wanted to do the repairs the same day; it had already been more than a week since the big event and eventually the tendons start to withdraw, making repairs harder. I wanted to wait a week so I could do my final two classes of the term. Then, we did what has to be done in a successful negotiation (teachable moment for my class), we worked hard to understand each other's point of view, we acknowledged that the other side's point of view was legitimate, and compromised. I would do my Monday class, he would work on me the following Wednesday, so I would miss the final class, but not to worry, I would be ably represented by my incredible TAs, Jessica Noss, Nicole Seo, and Rebecca Kekelishvili, along with Kris Brewer (also incredible), who helpfully agreed to record the term-project presentations so I could watch them later.

11 May 16 Surgery day

I showed up at noon and waited. The anesthesiologist came by to discuss options. “You have two,” he said, “general or spinal.”

“What about the whiskey option,” I said.

“Well, 150 years ago, that was the only option, but we don't offer it any more. Not enough demand.” I could see the day was going to be fun.

“Ok, I'll go for the spinal, that way I can supervise.”

“Well, you won't do much supervising. We also give you a sedative, so you will be half asleep.”

“Hmmm.” I thought to myself. “It will be much like a faculty meeting. But still, there will be some sense of participation.” In the end, I wasn't even half awake, but maybe just as well.

Anyway, all seemed to go well with my degloved tendons (technical term). Now I just have to deal with having my legs in immobilizers that keep them completely straight for a month. Try getting out of bed in that condition sometime. It is a challenge at first, especially when you are constantly thinking about how a slip will ruin some very nice surgical work.

There's more; see the rest of the story.

Great Laboratories

A year or two after I finished my PhD, I became director of the MIT Artificial Intelligence Laboratory, succeeding Marvin Minsky and Seymour Papert. Realizing I was young and stupid, I decided to ask various laboratory directors and department chairs what I should do to ensure that the Artificial Intelligence Laboratory would be a great laboratory.

After a dozen or so interviews, I became discouraged. None of the people to whom I talked seemed to have thought about such a question.

Then came the interview with Jay Forrester. It was about 25 years after he led the MIT group that created the Whirlwind computer, a machine with so many firsts that many consider it the first serious electronic computer. Its success enabled the development of the SAGE air defense system.

When I walked into Forrester's office, it was late afternoon. He sat me down at a small round table, outfitted with a white tablecloth, set for tea and cookies. He was wearing a beautifully tailored suit, with a carefully matching tie. I was not. I was scared.

I announced my purpose and he spent 25 minutes explaining why MIT should not have an Artificial Intelligence Laboratory. I cannot remember his reason.

I sensed that the interview was soon coming to a close, so I blurted out something like, “Well, Professor Forrester, it must have been wonderfully exciting to be trying to build the world's first real computer.”

“Young man,” he said, “We weren't trying to build a computer, we were trying to defend the United States against air attack from the Soviet Union.”

The scales fell from my eyes. You don't build great laboratories; great laboratories form around great missions. Being the best is a weak motive. If you develop a great mission, being the best will take care of itself.

Forrester passed away Wednesday,
16 November 2016.

How to spend part of IAP


Sorry if you missed this one. It was about the future of AI with emphansis on business.

21 January 2017

Damn the little gold stars

I confessed. I told my class that whenever a student sends me a message, I either respond immediately or put a little gold star next to the message, indicating that the message is important; I should deal with it soon.

The trouble is, I never seem to go back and look at the messages marked with those little gold stars.

Everyone nodded in understanding. Evidently, I am not the only one.

7 May 2017

Great Books

Why Only Us: If you want to know what makes us different from Chimpanzees and Neanderthals, read Berwick and Chomsky.

Adaptive Markets: If you want to know how markets evolve and work, read Andrew Lo.

Innovating: If you want to know how to change the world by innovating, read Perez-Breva.

Darwin's First Theory: If you want to know what Darwin would be famous for if he hadn't got himself interested in evolution, read Wesson.

What is the common thread? All these important books happen to have been written by friends of mine.

27 May 2017


Whenever you inform or persuade, your success will be determined by how well you speak, by how well you write, and by the quality of your ideas, in that order.

Just about every profession requires you to inform and persuade. You definitely inform and persuade if you work in business, especially in sales and marketing. If you train or educate, you inform and persuade. You inform and persuade if you do research in anything from anthropology to zoology. If you are in defense or law enforcement, you inform and persuade. If you preach or run a non-profit organization, you inform and persuade. You cannot avoid informing and persuading if you practice law, medicine, architecture, or journalism.

Somehow, I feel another book starting to rattle around in my head.

3 September 2017

Artificial Intelligence and Chocolate

In the old days, if you wanted to attract viewers to your page, you mentioned chocolate. Now, you mention Artificial Intelligence.

For those of us who have been around for a while, we are overcome with déjà vu.

The first wave of excitement followed from James Slagle's symbolic integration program in 1961. It did better work than most MIT freshman, so some feared the end of human usefulness was near.

The second wave of excitement came with the introduction of rule-based expert systems in the 1980s. One diagnosed infections of the blood better than primary-care physicians. Many such systems did and still do useful work in areas from resource allocation to medicine, but they are not an existential threat.

Now we have a third wave; we have Machine Learning and the subdiscipline of Deep Neural-Net Learning. Both are best viewed as Computational Statistics, a kind of processing enabled by newly available massive computing on massive data sets.

The Deep Neural Nets classify objects in pictures, invent captions, and translate from one language to another. AlphaGo beat Lee Sedol, a top-ranked human Go player, and the most recent version, announced in a paper in Nature's 19 October 2017 issue, became the world's best Go player by learning from games it played against itself.

All these give the appearance of humanlike understanding but without much actual humanlike understanding. None has any idea what it is doing.

Nevertheless, the world has responded with astonishing gusto. Fantastic headlines appear frequently, such as this one from Forbes in June, 2017: “5 Ways Facebook Uses Artificial Intelligence To Counter Terrorism.”

Important people weigh in, as when Valdimir Putin told Russian school children, in September, 2017: “Artificial intelligence is the future, not only for Russia, but for all humankind. It comes with colossal opportunities, but also threats that are difficult to predict. Whoever becomes the leader in this sphere will become the ruler of the world.”

Hmmm. Déjà vu. I think it useful to see how such headlines and comments sound with statistics substituted for Artificial Intelligence.

Of course all new technology can have unanticipated downsides, and there is no harm in some people thinking about how to mitigate those unanticipated downsides, but for as for me, I think it early to put Artificial Intelligence on par with, say, climate change, engineered pandemics, and nuclear conflagration.

I like Andrew Ng's response to the most extreme form of overexcitement. Ng, who has considerable talent for composing pithy characterizations, said in a conference in March, 2015, that fearing a rise of killer robots is like worrying about overpopulation on Mars.

7 October 2017