This was a great interview with Andrew Moore, Dean of CMU’s School of CS.
What’s the most pressing area of research in robotics?
We have a dirty secret. One of the reasons we’re having this renaissance in AI in the last few years is that we’ve become very good at computer vision. We’ve become very good at learning, so that robots no longer need to be programmed for every possible eventuality—they just adapt to their environment. That’s why you’re seeing this big burst in robotics, in car industries and the logistics industries and retail and medicine and so forth. But we have not had the same success in grasping and manipulation. The claw of the hand of the robot being dextrous, quickly moving around and picking things up without breaking them. That’s where we’re devoting a huge amount of effort. Roboticists around the world are focusing on that. Until then, robots will be deployed in areas where they’re not controlling manipulation, but they’re controlling machines and detecting problems, moving large bulky objects around. We’ve given ourselves a 5-year moonshot project. We want to put a robot arm on 100,000 powered wheelchairs in the US. The goal is that the people on those wheelchairs who have high spinal cord injuries or degenerative diseases, can’t use their own arms, look at an object, hold their focus on it, and the robot arm will reach to pick it up and place it where the user looks or indicates. If we can get this problem solved—we think there’s a 50/50 chance to do it in five years—it will be an extremely good thing for all the people who need this help. It’s a big test to see if we’ve broken the barriers of manipulation. This is exactly what we did about 15 years ago with self-driving car technology. That one panned out.
Are schools meeting the demands?
There’s been a lot of progress, and I’m excited by the new inclusion of CS in the New York curriculum. In Queensland, Australia, robotics is becoming an actual part of the required curriculum for kids. The countries that really push the math and statistics behind AI are the ones that will prosper in the long run.
How is CMU dealing with recruiting more women into tech?
We’re really passionate about this. We’re the first university to have broken through the 40% barrier
This article on diversity in AI (or STEM in general) is preaching to the choir here, but I’d like to see more studies / numbers backing up some of the comments.
“There’s a difference between agentic goals, which have to do with your personal goals and your desire to be intellectually challenged, and communal goals, which involve working with other people and solving problems.”
In general, many women are driven by the desire to do work that benefits their communities, desJardins says. Men tend to be more interested in questions about algorithms and mathematical properties. Since men have come to dominate AI, she says, “research has become very narrowly focused on solving technical problems and not on the big questions.”
To close the diversity gap, schools need to emphasize the humanistic applications of artificial intelligence.
via Is the Field of Artificial Intelligence Sexist? – Nextgov.com.
You don’t necessarily have to do anything once you acknowledge your privilege. You don’t have to apologize for it. You don’t need to diminish your privilege or your accomplishments because of that privilege. You need to understand the extent of your privilege, the consequences of your privilege, and remain aware that people who are different from you move through and experience the world in ways you might never know anything about. They might endure situations you can never know anything about. You could, however, use that privilege for the greater good–to try to level the playing field for everyone, to work for social justice, to bring attention to how those without certain privileges are disenfranchised. While you don’t have to do anything with your privilege, perhaps it should be an imperative of privilege to share the benefits of that privilege rather than hoard your good fortune. We’ve seen what the hoarding of privilege has done and the results are shameful.
via Peculiar Benefits – The Rumpus.net.
HT Laura Royden
Well-said. (discussion of privilege.)
Percentage of doctoral scientists and engineers employed in universities and 4-year colleges (S&E occupations) who are tenured, by race/ethnicity and gender (2008)
Percentage of scientists and engineers employed in government who are managers, by race/ethnicity and sex (2006)
Percentage of scientists and engineers employed in business or industry who are S&E managers, by race/ethnicity and gender (2006)
Percentage of scientists and engineers doctorate degree holders employed in business or industry who are S&E managers, by race/ethnicity and sex (2006)
The advancement of Asian female scientists and engineers in STEM careers lags behind not only men but also white women and women of other underrepresented groups. Very small numbers of Asian women scientists and engineers are advancing to become full professors or deans or university presidents in academia, to serve on corporate board of trustees or become managers in industry, or to reach managerial positions in government. Instead, in academia 80% of this population can be found in non-faculty positions, such as postdocs, researchers, and lab assistants, or nontenured faculty positions, and 95% employed in industry and over 70% employed in government are in nonmanagerial positions. In earning power they lag behind their male counterparts as well as behind women of other races/ethnicities in STEM careers.
via Real Numbers: Asian Women in STEM Careers: An Invisible Minority in a Double Bind | Issues in Science and Technology.
only 12.4 percent of students in the EECS major at UC Berkeley are female
via Gender disparity in EECS persists | Dailycal.org.
Well-made clip on gender diversity in EECS at Berkeley.
Somewhat related, it is comforting to learn that gender is not a huge factor in the report titled Ph.D. Student Attrition in the EECS Department at the University of California, Berkeley. The following interpretation is interesting but not fully backed with data.
A possible interpretation of this result … career choices must fit into a larger picture. For men, it is more acceptable to segregate the two. Seymour observed this same phenomenon in a study of undergraduates: “young men… are more willing to place career goals above considerations of personal satisfaction. By contrast, young women show a greater concern to make their education, their career goals, and their personal priorities, fit coherently together.” Another important concept is the idea of the science “mold.” If there are no role-models, no women faculty within the academic mold that appear to enjoy the life graduate student women aspire to achieve, women will seek a career option in which it is easier to integrate career and personal goals.