Waltz on Automating Science

Columbia Senior Research Scientist David Waltz explains what needs to happen for computers to take the next evolutionary step, in the article “Automating Science” in the April 3 issue of Science. Waltz, the founding director of the Center for Computational Learning Systems at The Fu Foundation School of Engineering and Applied Science at Columbia, co-wrote the piece the journal’s Perspectives section with Bruce G. Buchanan, computer science professor at the University of Pittsburgh.

Waltz and Buchanan write that automation has a long history in computer science and note two studies, also published in the same issue of the journal, that show computers can be used to go beyond data collection to include evaluation and decision making.

“As these reports show,” they write, “it is possible for one computer program to step through the activities needed to conduct a continuously looping procedure that starts with a question, carries out experiments to answer the question, evaluates the results, and reformulates new questions.”
For more complex applications, however, Waltz and Buchanan write that new programs are needed to handle the increasing volume of data, search engines must be refined and computer modeling must be improved. They feel these are possible to achieve.

“For the foreseeable future, the prospect of using automated systems as assistants holds vast promise as these assistants are becoming not only faster but much broader in their capabilities — more knowledgeable, more creative, and more self-reflective. Human-machine partnering systems that match the tasks to what each partner does best can potentially increase the rate of scientific progress dramatically, in the process revolutionizing the practice of science and changing what scientists need to know.”

CCLS, founded in 2003, is composed of 30 research scientists, graduate students, professional staff members, and industry specialists who work in collaboration with Columbia’s Department of Computer Science and other University departments. CCLS has become a hub for basic machine learning research and especially the application of machine learning to large scale business and government systems, systems reliability and security, natural language translation and understanding, computational biology and bioinformatics, and computer vision.