Category: General

Virtually every discipline of significant human endeavor has a way explaining itself as fundamental and important. In all the cases I know of, they are both right (they are vital) and wrong (they are not solely vital).

1. Politics. This is the one that everyone is familiar with at the moment. “What could be more important than the process of making decisions?”
2. Science and Technology. This is the one that we-the-academics are familiar with. “The loss of modern science and technology would be catastrophic.”
3. Military. “Without the military, a nation will be invaded and destroyed.”
4. (insert your favorite here)

Within science and technology, the same thing happens again.

1. Mathematics. “What could be more important than a precise language for establishing truths?”
2. Physics. “Nothing is more fundamental than the laws which govern the universe. Understanding them is the key to understanding everything else.”
3. Biology. “Without life, we wouldn’t be here, so clearly the study of life is fundamental.”
4. Computer Science. “Everything is a computer. Controlling computation is fundamental to controlling the world.”

This post is a “me too” for machine learning. The basic claim is that all problems can be rephrased as prediction problems. In particular, for any agent (human or machine), there are things which are sensed and the goal is make good predictions about which actions to take. Here are some examples:

1. Soccer. Playing soccer with Peter Stone is interesting because he sometimes reacts to a pass before it is made. The ability to predict what will happen in the future is a huge edge in games.
2. Defensive Driving is misnamed. It’s really predictive driving. You, as a driver, attempt to predict how the other cars around you can mess up, and take that into account in your own driving style.
3. Predicting well can make you very wealthy by playing the stock market. Some companies have been formed around the idea of automated stock picking, with partial success. More generally, the idea of prediction as the essential ingredient is very common when gambling with stocks.
4. Information markets generalize the notion of stock picking to make predictions about arbitrary facts.

Prediction problems are prevalent throughout our lives so studying the problems and their solution, which is a core goal of machine learning, is essential. From the predictionist viewpoint, it is not about what you know, what you can prove or infer, who your friends are, or how much wealth you have. Instead, it’s about how well you can predict (and act on predictions of) the future.

This is about the hard choices that graduate students must make.

The cultural definition of success in academic research is to:

1. Produce good research which many other people appreciate.
2. Produce many students who go on to do the same.

There are fundamental reasons why this is success in the local culture. Good research appreciated by others means access to jobs. Many students succesful in the same way implies that there are a number of people who think in a similar way and appreciate your work.

In order to graduate, a phd student must live in an academic culture for a period of several years. It is common to adopt the culture’s definition of success during this time. It’s also common for many phd students discover they are not suited to an academic research lifestyle. This collision of values and abilities naturally results in depression.

The most fundamental advice when this happens is: change something. Pick a new advisor. Pick a new research topic. Or leave the program (and do something else with your life).

The first two are relatively easy, but “Do something else with your life” is a hard choice for a phd student to make because they are immersed in and adopt a value system that does not value that choice. Remember here that the academic value system is not a universal value system. For example, many people want to do something that is immediately constructive and find this at odds with academic research (which is almost defined by “not immediate”). The world is big enough and diverse enough to support multiple value systems. Realizing this may be the key to making very good decisions in your life. A number of my friends made this decision and went to google or investment banking places where they are deliriously happier (and more productive) than in their former lives.

I read through some of the essays of Michael Nielsen today, and recommend them. Principles of Effective Research and Extreme Thinking are both relevant to several discussions here.

I tweaked the site in a number of ways today, including:

1. Updating to WordPress 1.5.
2. Installing and heavily tweaking the Geekniche theme. Update: I switched back to a tweaked version of the old theme.
3. Adding the Customizable Post Listings plugin.
4. Installing the StatTraq plugin.
5. Updating some of the links. I particularly recommend looking at the computer research policy blog.
6. Adding threaded comments. This doesn’t thread old comments obviously, but the extra structure may be helpful for new ones.

Overall, I think this is an improvement, and it addresses a few of my earlier problems. If you have any difficulties or anything seems “not quite right”, please speak up. A few other tweaks to the site may happen in the near future.

I found the article on “Political Science” at the New York Times interesting. Essentially the article is about allegations that the US government has been systematically distorting scientific views. With a petition by some 7000+ scientists alleging such behavior this is clearly a significant concern.

One thing not mentioned explicitly in this discussion is that there are fundamental cultural differences between academic research and the rest of the world. In academic research, careful, clear thought is valued. This value is achieved by both formal and informal mechanisms. One example of a formal mechanism is peer review.

In contrast, in the land of politics, the basic value is agreement. It is only with some amount of agreement that a new law can be passed or other actions can be taken. Since Science (with a capitol ‘S’) has accomplished many things, it can be a significant tool in persuading people. This makes it compelling for a politician to use science as a mechanism for pushing agreement on their viewpoint.

Most scientists would not mind if their research is used in a public debate. The difficulty arises when the use of science is not representative of the beliefs of scientists. This can happen in many ways. For example, agreement is uncommon in research which implies that it is almost always possible, by carefully picking and choosing, to find one scientist who supports almost any viewpoint.

Such misrepresentations of scientific beliefs about the world violate the fundamental value of “careful, clear thought”, so they are regarded as fundamentally dangerous to the process of research. Naturally, fundamentally dangerous things are sensitive issues which can easily lead to large petitions.

This combination of mismatched values is what appears to be happening. It is less clear what should be done about it.

One response has been (as the article title suggests) politicization of science and scientists. For example the Union of Concerned Scientists (which organized the petition) has a viewpoint and is pushing it. As another example, anecdotal evidence suggests a strong majority of scientists in the US voted against Bush in the last presidential election.

I would prefer a different approach, which is essentially a separation of responsibilities. Given a sufficient separation of powers, scientists should be the most reliable source for describing and predicting the outcomes of some courses of action and the impact of new technologies. What is done with such information is up to the rest of the world. This style of “sharply defined well-separated powers” has worked fairly well elsewhere. Supreme court judges (who specialize in interpretation of law) are, by design, relatively unaffectable by the rest of politics. A newer example is the federal reserve board who have been relatively unaffected by changes in politics, even though it is easy to imagine their powers could dramatically effect election outcomes. This last example is a matter of custom rather than constitutional law.

Neither of the above examples are perfect—the separation of powers has failed on multiple occasions. Nevertheless, it seems to be a useful ideal.