Ed Lazowska: Computational Thinking

Help Center Profiles of Technology Use Ed Lazowska: Computational Thinking

Ed Lazowska
Department of Computer Science
University of Washington, Seattle Campus


Do you know how to devise and express an algorithm? How about the process of stepwise logical fault isolation? Though the terms might be foreign, Ed Lazowska, the Bill & Melinda Gates Chair in Computer Science & Engineering, argues that many of us already use this kind of computational thinking in our lives and its importance and pervasiveness is increasing every day.

Ed Lazowska has taught at the UW for over 30 years. His research and teaching focus on the design, implementation, and analysis of high-performance computing and communication systems. Currently, Lazowska is Director of the UW eScience Institute, which has the objective to create and promote the techniques and technologies of data-intensive science.

PCAST Report – Designing a Digital Future

During the summer of 2010, Lazowska co-chaired the Working Group of the President’s Council of Advisors on Science and Technology (PCAST) that prepared a report titled Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technology.

According to Lazowska, the main messages of the report include:

  • Advances in computer science have been a pivotal driver of economic prosperity over the last two decades.
  • Current and ongoing technological and societal changes situate further advances in computing at the center of nearly every national priority: improved energy efficiency, education, transportation, health, etc.

Lazowska drives home the importance of computing, citing the example of transportation:

“If you want to improve public transportation efficiency, you need to get information on your phone about instantaneous transit availability; you need to integrate multiple streams of data; and you need to route public transport through neighborhoods effectively to get you from your home to the major transit arterial. Planners need to route transit around not just where the congestion is now, but where the congestion will be 20 minutes from now. Historical data needs to be integrated with real-time sensor information to predict how backups flow through the system. Ditto for single-occupancy vehicles. Using technologies available today, like adaptive cruise control, collision-avoidance systems, and stay-in-lane systems, efficiency could be improved greatly. Putting Zipcar on steroids would be a huge contribution, and it’s almost entirely an IT/logistics challenge.”

Lazowska sees transportation efficiency as an example of a national priority that depends critically on advances in computer science. Medical data collection is another area that can benefit from advanced computing methods. Comparing the human body to a car, he wonders why we have the ability to follow the physical performance of an automobile through tracking instruments but don’t have a way to continually record and measure the physical processes of the body. “Why is your automobile so much better instrumented than your car?”

PCAST’s Workforce Analysis

The PCAST report documents that computer science is by far the dominant factor in all U.S. science and technology employment.

Job projections over the next eight years show 2/3 of all newly-created jobs in all fields of engineering and science (including the social sciences) will be computing jobs. Lazowska summarizes the situation bluntly, “The truth is there is no science and technology workforce gap; there is a computer science workforce gap.”

Lazowska emphasizes that it is critically important for the nation to improve STEM (Science, Technology, Engineering, Math) education across the board. Looking at Washington State specifically, Lazowska sees few students graduating with bachelors degrees. Though the UW is a world-class university, Lazowska says it isn’t able to produce enough bachelors degrees to keep the state competitive. Per capita, Washington lags in graduating students with 4-year degrees that are needed in the modern workforce. Lazowska would like the state and the UW to make more intelligent investment decisions that are supportive of STEM, computer science, and producing more bachelors degrees in general as that is what drives the economy and where the jobs are.

Computational Thinking

Acknowledging that not all students want to study computer science, Lazowska suggests emphasizing computational thinking throughout the educational system.

Fields other than those traditionally associated with computing that incorporate computational thinking include linguistics, revolutionized by Noam Chomsky’s theory of generative grammar, and biology, now dominated by biochemistry and DNA (biologists have come to the view that the genome is a digital code implemented in chemistry). According to Lazowska, these and many other fields are becoming increasingly computational.

“The principles of computer science lie in algorithmic thinking, stepwise fault isolation, and other logical concepts that can be applied to scientific as well as everyday problems.”

CMU professor Jeanette Wing’s article on computational thinking, provides the following illustrative example:

“When your daughter goes to school in the morning, she puts in her backpack the things she needs for the day, that’s prefetching and caching. When your son loses his mittens, you suggest he retrace his steps; that’s backtracking. At what point do you stop renting skis and buy yourself a pair; that’s online algorithms. Which line do you stand in at the supermarket; that’s performance modeling for multi-server systems. Why does your telephone still work during a power outage; that’s independence of failure and redundancy in design.”

Lazowska argues that computational thinking, whether or not you’re computing, is becoming absolutely pervasive. He advocates emphasizing these concepts through programming classes. “No matter what they intend on studying or doing, students need to have a grounding in modern computational concepts.”

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