Integrating Education and Real Research

AAAI Conferences

Popular media has spawned a recent interest in teaching robotics in the classroom. Many different approaches have been attempted, with many that focus on robot competitions. However, following the competition, students often do not know where to turn to keep their curiosity in robotics alive. This paper discusses a collaborative approach that shows students a clear path from early robot competitions through to careers in the field. The approach relies on student participation in real research and a ladder of mentorship through their academic journey.


In computer science, a growing gender gap - The Boston Globe

AITopics Original Links

As a young high school teacher in 1982, Diane Souvaine leapt into graduate school for computer science having taken only one class in the subject. Computers, she believed, offered an exhilarating way to apply her math skills to real-world problems. And because computer science was coming into its own in the feminist age, she also hoped it would be more welcoming to women than her undergraduate math department. Today, Souvaine chairs the Tufts University computer science department, which has more female professors than male. But few younger women have followed in her generation's footsteps.


[Working Life] The questions that opened doors

Science

A couple years ago, I asked my Ph.D. adviser why he decided to give me a position in his lab. "Because you were so focused on finding good questions," he told me. I found this answer amusing, because my early scientific training hadn't fostered this skill at all. In my undergraduate years at the University of El Salvador, the biological world had been presented as a series of known facts, and students were not trained to question them. There is little research tradition in El Salvador, and my professors didn't provide examples of what scientific inquiry is really about.


How Brain Drain from Academia Could Impact the AI Talent Pool

#artificialintelligence

In the emergent war to have the best artificial intelligence capability, academia might have the most casualties. According to the National Science Foundation, 57 percent of new computer-science doctoral graduates in the United States take industry jobs, meaning they leave academia for the private sector. This is compared to 38 percent a decade ago, according to The Wall Street Journal. Given that academia is the primary breeding ground for skills in emerging fields like AI, what would a constant academic exodus of talent in the field mean for the future development of its talent pool? One of the biggest concerns is that there will be fewer graduates with a thorough education in AI. "The number of graduating master's and Ph.D.-level computer scientists may decrease, which is the opposite to what the current market is demanding," said Peter Morgan, chief AI officer at Ivy Data Science, an AI-as-a-service platform and training company based in New York City.


How Brain Drain from Academia Could Impact the AI Talent Pool

#artificialintelligence

In the emergent war to have the best artificial intelligence capability, academia might have the most casualties. According to the National Science Foundation, 57 percent of new computer-science doctoral graduates in the United States take industry jobs, meaning they leave academia for the private sector. This is compared to 38 percent a decade ago, according to The Wall Street Journal. Given that academia is the primary breeding ground for skills in emerging fields like AI, what would a constant academic exodus of talent in the field mean for the future development of its talent pool? One of the biggest concerns is that there will be fewer graduates with a thorough education in AI. "The number of graduating master's and Ph.D.-level computer scientists may decrease, which is the opposite to what the current market is demanding," said Peter Morgan, chief AI officer at Ivy Data Science, an AI-as-a-service platform and training company based in New York City.