Science and Technology

The authors of its 1861 charter named the university the Massachusetts Institute of Technology, not the Massachusetts Institute of Science. It was a moment of increasing industrialization in the United States, and the school’s founders believed that the word technology suggested a vocational emphasis, a hands-on approach to industrial engineering and applied science, with less concern for theoretical science. Engineering technology was about processes and operations, it was meant to be practical. The university’s principal founding donor was the inventor of film production methods. Over the following decades, MIT’s academic leaders have continued to nurture a balance between the basic science work of physics, chemistry, and molecular biology, and the technological practice of product development.

MIT’s nominal commitment to technology but core focus on research and science is illustrative of a distinction between science and technology that has become blurred. In oversimplified, idealized, binary terms, the job of the scientist is to come up with a problem–What could be the structure of a molecule that might explain genetics? How does gene regulation drive protein synthesis?—and to generate explanatory theories and speculative answers. The more universal and convincing the theory, the more credit the scientist collects. Additional rewards come from the discoveries that bolster the theory.

This contrasts with technologists who are less committed to the development of theory. When Thomas Edison sorted through materials for his lightbulb filament, he was searching for not a universal property, but a particular one. The value of high-resistance carbon is derived not from its representation of the material world but from its utility. Engineering and its technologies allow us to do things better, more effectively. Technology has become a shorthand term for the applications of science that reach a market that winnows out winners and losers, effectively choosing which engineering solutions will flourish and which will disappear. Science gets discovery, technology gets innovation and the application of truth.

Of course, there are complementarities between science and technology. Technology certainly springs from basic science. In return, fundamental insights are certainly indebted to developments in technology and practical investigations.

But there are differences in style and institutional behavior. Scientists, usually working in academic settings and dependent on external funding, try to amplify the dissemination of their work to colleagues, editors, and reviewers to gain favor and appear relevant. Those working in industries seeking to monetize inventions, cite and search widely to know less about more. Privacy matters, but so does the tight focus required for patents. There is a contrast between scientific discovery and technological search: For scientists, disciplines and their boundaries (as epitomized by the contents of peer-review journals) and audiences, are clear at all phases of scientific production, publishing, and promotion. However, such distinctions are largely invisible for technological invention and its certification in legally protected patents and marketed products. One ongoing worry, although without evidence, is that the financial excitement and draw of technology could move more and more scientists away from the slower work of theory creation and verification, away from deeper understanding.

Medication discovery, for example, once a scientific problem—how do we go about finding novel medicines that can help patients?—has become an engineering problem—how can we reduce the failure rate in drug development where more than nine out of ten of these medicines fail, and expensively? The promise of AI has made drug discovery and medicinal chemistry no longer about discovering new gene functions and proteins found in esoteric plant species. Rather, it is about how to sift parsimoniously through millions of three-dimensional designs to identify medicines that affect patients positively without too many adverse effects. Drug development is now a data problem and a chip design problem.

But again, a kinship. Academic departments are typically organized around modes of inquiry and explanation (e.g., ecology, physics), and similarly, divisions in industry follow product lines and their markets. The values of researchers in universities and those working in industry are now thoroughly intermixed, creating friction and, at times, workplace inconsistencies. Academic scientists embrace entrepreneurial orientations to raise capital for their science, while in commercial firms, contributions to basic knowledge are increasingly valued.

The physicist Richard Feynman once wrote, “A question of the form: If I do this, what will happen? Is strictly scientific.” If it cannot be put into this form, Feynman believed, it is not in the realm of science. Feynman defined science as a method for, and a body of information obtained by, trying to answer only questions in that form. We would argue that technology is a critical complement to the work of science, taking up the same question but having a particular interest in offering the results or products to markets that provide consumers with control over the world.

Previously in Observing Science: Facts?