August 14, 2014: People of ACM: Jeannette Wing
Thursday, August 14, 2014
Jeannette Wing's areas of expertise are in trustworthy computing, formal methods, concurrent and distributed systems, programming languages, and software engineering. Her contributions in security and privacy include work on attack graphs and attack surfaces, formalizing privacy policies for automated compliance checking, and trust in networks of humans and computers. Within the computer science community, Wing is well known for her advocacy of "computational thinking," an approach to problem solving, designing systems, and understanding human behavior that draws upon concepts fundamental to computer science.
She is Corporate Vice President, Microsoft Research, where she oversees the organization's core research laboratories around the world. She joined Microsoft Research in 2013 after holding key positions in academia and government, most recently at Carnegie Mellon University and the National Science Foundation.
A Fellow of ACM, the American Academy of Arts and Sciences, the American Association for the Advancement of Science, and the Institute of Electrical and Electronics Engineers (IEEE), Wing received the CRA Distinguished Service Award in 2011 and the SIGSOFT Retrospective Paper Award in 2012. She earned a Ph.D. in Computer Science, a Master's degree in Electrical Engineering and Computer Science, and an SB in Computer Science and Engineering from MIT.
What motivated you to coin the term "computational thinking" and are you optimistic that this concept is reaching the teachers, students, and parents that you hope to engage in this process?
It was 2005. Since the dot-com bust, there had been a steep and steady decline in undergraduate enrollments in computer science with no end in sight. The computer science community was wringing its hands, worried about the survival of their departments on campuses. Instead, I saw a different, much rosier future for computer science. I saw that computing was going to be everywhere.
The use of computational methods and tools will transform the very conduct of all disciplines, professions, and sectors. Someone with the ability to use computation effectively will have an edge over someone without. So, I saw a great opportunity for the computer science community to teach future generations how computer scientists think. Hence "computational thinking." How do computer scientists understand a problem, design a solution, and analyze results?
My vision is that that every child will learn computational thinking along with reading, writing, and arithmetic. Making computational thinking commonplace means we, as part of the broader academic community, have to figure out what makes sense to teach when. For example, when is the right time to teach recursion? Are some computational concepts innate? I realized early on that I was suggesting a new long-term research agenda for the cognitive and learning sciences communities, working in tandem with computer scientists.
I am incredibly optimistic that computational thinking is reaching teachers, students, and parents. The most gratifying impact so far has been in the United Kingdom, where through the combination of a grassroots effort by renown computer scientists (e.g., Simon Peyton-Jones) and a top-down government mandate, all K-12 students starting in fall 2014 will be taught some computer science concepts, appropriate for their grade level. I am rooting for their success! Moreover, I see the computational thinking movement, through different guises, sweeping the US (e.g., through persistent efforts by the ACM, CSTA [Computer Science Teachers Association], NSF, and industry-sponsored consortia such as Code.org). China is embracing computational thinking too.
As an advocate of educating government and society about the power and limits of information technology, what insights can you share on the balance between security and privacy in light of today's extensive practice of data mining?
There are two separate questions here. First, there is a question about the balance between security and privacy. The canonical example is whether we can have accountability and anonymity at the same time. Accountability means that if something bad happens, such as a security breach, we can identify the culprit. Law enforcement agencies want accountability because they want to find the bad guy. Anonymity keeps private the identity of an individual, and thus in this scenario, anonymity means we cannot determine the bad guy.
In the fall of 2012, Rebecca Wright and I ran an NSF Secure and Trustworthy Computing session on tradeoffs between accountability and anonymity. Our discussants came up with a healthcare chatroom as a motivating scenario where one would like both accountability and anonymity; and we discussed how, under certain conditions, it is technically feasible to achieve both. Quoting from our summary:
"People should be able to participate anonymously in the chat room in order to enable safe and comfortable discussion of their health concerns. Furthermore, sometimes posting photos can help convey information. However, this creates opportunities for inappropriate users and uses, such as people posting child porn photos in order to attract potential customers and other kinds of spam messages. In such a setting, it would be desirable to have accountability to deter such misbehavior without compromising anonymity for appropriate use.
"We also noted that accountability and anonymity need not always be in conflict. In particular, through the use of cryptographic techniques with revocable anonymity, it is possible to design systems so that participants can participate anonymously in general, but their anonymity is revoked if they break particular rules."
More generally, security and privacy are not always at odds; we rely on security mechanisms (e.g., cryptography and access control) to enforce privacy policies.
Second, there is a question about the tension between technology and privacy. Ever since Warren and Brandeis's 1890 Harvard Law Review article, "The Right to Privacy," society has been aware of how technology changes the social norms around privacy. Data mining is no different. It gets a lot of attention now because, with each privacy violation reported in the media, people realize that they do not know what others know about them. For each personal interaction with the physical or cyber world, from checking out groceries in a supermarket to walking the streets of London, from searching for medical information on the web to submitting our tax returns online, something about the interaction is recorded by someone—usually, unbeknownst to us. As consumers, we get annoyed when companies cross our personal creepiness line. As citizens, we lose trust in our government when we discover it monitors our behavior without our awareness.
The scale of the Internet has made it easy for a multitude of third parties to acquire information about us. Data mining and machine learning further make it easy to infer our personal habits and preferences so that these third parties can personalize their interactions with us (e.g., recommending what book to buy or reminding us to send a birthday greeting). Individuals, with consent or unknowingly, give up some privacy for more utility.
What we need is better and open communication about privacy concerns: between companies and consumers, government and citizens, technologists and policymakers, computer scientists and social scientists, scientists and ethicists. For example, new technology could allow individuals to know what others know about them. New policy could hasten wide adoption of a single privacy-preserving technology, making it more impactful.
How do you feel about your nickname "Dragon Lady," and does your pursuit of martial arts play into your view of the concept of computational thinking?
I like my nickname "Dragon Lady." It was actually given to me by CMU undergraduates because I had a reputation for being a tough teacher. Later, when I started doing karate, the nickname carried over and stuck. While I see computational thinking in the martial arts (e.g., patterns in the forms we practice), when I spar, I only think about not getting hurt!
As a computing visionary, what advice would you give to students who are pursuing stimulating career challenges?
Be passionate about what you choose to do.