By Allison Barrett
Melanie Mitchell is one woman who is breaking the “boys’ club” misconception of the computer science field. A professor and researcher located at Portland State University as well as an external professor at the Santa Fe Institute, Mitchell specializes in the study of computer science, particularly computational complexity. Her research focuses on topics such as computer models of high-level perception and conceptual “slippage” in the ways computers perceive notions such as analogies.
Mitchell is exceptionally skilled in the art of taking complex ideas and systems and articulating them so that others can understand what’s involved and enjoy the pursuit of comprehension in the field of computer science. Not only has she participated in leading many educational workshops, but her conference tutorial “Introduction to Complexity” has also been offered at numerous universities over the years, and she has dedicated time to K-12 educational activities, acting as a mentor for students interested in science and engineering. In 2010, her book Complexity: A Guided Tour (Oxford University Press, 2009) received The Phi Beta Kappa Society’s Science Book Award.
Having had a father in the computer engineering profession, Mitchell was raised in an environment that fostered a familiarity with computers. However, it was not until she completed her undergraduate education at Brown University, obtaining a degree in mathematics, that she began reading literature that inspired her to investigate the growing field of computer science. Ever since then, Mitchell has dedicated her career to computers. Her greatest interest is in studying human and artificial intelligence, learning, and cognition; exploring complex systems of self-organization; and unearthing how organized behaviors originate. When asked why she chose artificial intelligence as a focus of her research, Mitchell said, “When we learn to make computers intelligent, it makes us learn about our own intelligence.” Mitchell observed that in the process of assembling the “pieces” required to construct artificial intelligence, we “learn parts of thought that might otherwise have been invisible.” In learning about computers, we as humans learn about ourselves.
Mitchell also observed that it is an exciting time for the field of computer science, particularly for the study of artificial intelligence. When asked to offer an example of how her work is applied in the world, she spoke about something of great current interest (and controversy): self-driving vehicles. Through the efforts of scientists like Mitchell who contribute to the research, self-driving cars are becoming proficient to the point that they are being introduced in a variety of locations as a means of transportation. The “smart” vehicles are programmed to predict situations and react accordingly with problem-solving skills—obviously “intelligent” behaviors. Yet, she noted that additional research is required to investigate improving the vehicle’s abilities to respond to more difficult scenarios (e.g., interpreting directions from a human directing traffic in inclement weather).
Mitchell claimed that there are countless questions we can ask of artificial intelligence, such as: Can we make computers intelligent? If so, what parts of intelligence do we want to replicate? How can we measure it? Do we really want to? In order to ask and potentially answer these questions, an interdisciplinary approach is required. In her research, Mitchell said that she has explored computer science’s intersections with other fields of study such as cognitive psychology, cognitive neuroscience, physics, and mathematics. This interdisciplinary approach to revolutionizing fields of study is rapidly becoming a popular and useful approach to research and the creation of new ideas and theories.
However, some aspects of the field remain static. While more disciplines are being incorporated into computer science, the population of computer scientists remains largely male. In 2014, US News analyzed the test-taking patterns of high school students undergoing examinations in Advanced Placement computer science classes and found that boys outnumber girls 4:1. Mitchell recalled that there were very few female mentors in computer science during her graduate education, and that the lack of females is felt. She said that the numbers of females pursuing the degree diminish largely due to societal stereotypes (e.g., boys are meant to play video games while girls play with dolls) and cutthroat competition that reduces interest. It is not simply the absence of women that is felt; Mitchell noted how there is an overall lack of diversity in computer science. “Diversity is important to get good work, to generate new ideas,” she said. In other words, the inclusion of new individuals with varied backgrounds is necessary to develop novel scientific inquiry.
Mitchell said there are programs already attempting to bring about greater inclusion by reaching out to the next generation. Institutions like MIT develop computer games that promote computer-programming education for all genders. Additional endeavors are being made to provide equal learning opportunities, produce more female role models, and transform the conception of the field as a whole to be more gender-balanced. For example, Newsweek featured the Harvey Mudd College in 2015, highlighting how the institution increased their average number of women computer science majors from 10% to 40% after restructuring computer science courses to focus less on “straight programming” and more on creative problem-solving techniques while emphasizing group unity through enjoyable group activities designed to introduce students to the breadth of the field and how it can be used to benefit society. These efforts are designed to erase stereotypes by reconstructing the popular perception of computer science to be more inclusive.
Phi Beta Kappa also works to bring attention to the presence and contributions of women in the sciences. Recalling the ΦBK Science Book Award, Mitchell commented, “The award was great because it brought the book recognition so that it could reach a wider audience.” Awards from organizations such as ΦBK allow women in the sciences like Mitchell to become role models that future researchers can look to for inspiration.
The field of computer science, like Mitchell’s thoughts on artificial intelligence and learning, involves many complex, interweaving parts that construct the whole that is slowly unraveled and reassembled by curious persons—we just need to work hard enough to make every contributing person visible.
Allison Barrett is a senior at St. Mary’s College of Maryland double majoring in Psychology and English. St. Mary’s College of Maryland is home to the Zeta of Maryland Chapter of Phi Beta Kappa.