Science policy

From Academic Kids

Science policy is usually considered the art of justifying, managing or prioritizing support of scientific research and development. It has three major venues: educational institutions, governments, and philanthropic organizations.

Businesses have a comparable function, but since they usually do it for profit, the goals, methods and justifications are very different. Science policy for business is usually called research and development.

Almost all people agree that "science should be supported". Beyond that, consensus quickly breaks down. There are several common positions:

Contents

Utilitarian science policy

Utilitarian policies prioritize scientific projects more highly if they reduce large amounts of pain for many people. The pursuit of pleasure or luxury is far less supported, but nearly everyone supports the reduction of painful and debilitating diseases. The perfect example is arthritis research, which is well-supported.

Utilitarian policymakers characteristically advertise the numbers or people that can be helped by some research strategem. In democracies, utilitarian science is an easy sell to the elected officials and foundation boards that control distribution of funds.

Research is more likely to be supported when it costs less and has greater benefits. Utilitarian research is characteristically rather unexciting for scientists because it often pursues incremental improvements rather than dramatic advancements in knowledge, or break-through solutions, which are more commercially viable. This influences the failure of some projects.

Basic science policy

Basic science attempts to stimulate break-throughs. Break-throughs often lead to an explosion of new technologies and approaches. Characteristically, basic science is cheap. One selects bright, energetic (usually young) theoreticians, and teams them with clever, practical people to test their theories. Once the basic result is developed, it is widely published; however conversion into a practical product is left for the free market.

This model does not automatically bring improvements. For instance, in a command economy the results of basic research are often not fully utilized. The most famous example is the Soviet Union. It supported huge numbers of scientists but their achievements were utilized mainly for military and space programs.

A particular problem is that the military research of even the freest of free market countries is a command economy. Many governments have developed risk-taking research and development organizations to take basic theoretical research over the edge into practical engineering. In the US, this function is performed by DARPA.

Scholastic conservation

This is the policy of the impoverished. Rather than invest in new science, the policy is to efficiently teach all available science to those who can use it. In particular, the goal is not to lose any existing knowledge, and to find new practical ways to apply the available knowledge.

The classic success stories of this method occurred in the 19th century U.S. land-grant universities, which established a strong tradition of research in practical agricultural and engineering methods. More recently, the green revolution prevented mass famine over the last thirty years.

The focus, unsurprisingly, is usually on developing a robust curriculum and inexpensive practical methods to meet local needs. A particular problem with this approach is that there's now a continuing brain drain from impoverished countries (which often have quite good, though small, universities) to the wealthy countries.

Monumental science

This is a policy in which science is supported in order to aggrandize the reputation of the supporter. The emphasis is usually given to large, showy projects, preferably with large, showy facilities, justified in the name of "basic research" or "timeless importance".

The classic justifications of such policymakers speak to national pride, or knowledge of lasting worth. Done well, its supporters get that for which they pay, and the rest of us get to read about it.

The classic success stories of this method are giant telescopes (characteristically named for their benefactors), the "space race" between the US and the Soviet Union, which ended happily in men walking on the moon, and the particle accelerator races that helped develop the standard model of physics.

The focus is usually on basic research involving apparatus of fabulous expense, size, complexity or perfection. No one ever speaks of the fact that such phenomena, and the data from them are normally inapplicable, precisely because they require monumental apparatus of fabulous expense. This is not the point, after all.

Technology development

This is a policy in which science is not supported, so much as engineering, the application of science. The emphasis is usually given to projects that increase important strategic or commercial engineering knowledge.

The classic justifications of such policymakers speak to increased defensive or commercial opportunities.

The most extreme success story is doubtless the Manhattan Project (that developed nuclear weapons). Another remrkable success story was the "X-vehicle" studies that gave the US a lasting (and now eroding) lead in aerospace technologies.

These exemplify two disparate approaches: The Manhattan Project was huge, and spent unblinkingly on the most risky alternative approaches. The project members believed that failure would result in their enslavement or destruction by Nazi Germany.

Each X-project built an aircraft whose only purpose was to develop a particular technology. The plan was to buid a few cheap aircraft of each type, fly a test series, often to the destruction of an aircraft, and never design an aircraft for a practical mission. The only mission was technology development.

A number of high-profile technology developments have failed. The US Space Shuttle failed grotesquely to meet its cost or flight schedule goals. Most observers explain the project as overconstrained: the cost goals too aggressive, the technology and mission too underpowered and undefined.

The Japanese fifth-generation computer project (see Sigma project for details) met every technological goal, but failed to produce commercially-important artificial intelligence. Many observers believe that the Japanese tried to force engineering beyond available science by brute investment. Half the amount spent on basic research rather might have produced ten times the result.

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