McGill AI for Social Good summer lab for women returns for a second year

After the success of last year’s inaugural program, AI for Social Good is back for a second year.

McGill Innovation launched the one month Summer Lab in collaboration with McGill Reasoning and Learning Lab.  It teaches technical concepts in machine learning , in addition to digital product development and design applied to a specific social problem.

The program, which will take place May 14th to June 21st, is exclusive to female-identifying applicants and will feature a machine learning curriculum with weekly mentoring sessions with machine learning researchers, members of the Montreal tech/startup community, and subject matter experts. This year it is a joint effort between OSMO, McGill University, and the Montreal Institute for Learning Algorithms (MILA).

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“I had been thinking a lot about inclusion and diversity in the context of innovation and also, being someone that’s worked in the tech industry for a long time, being excited about the potential for artificial intelligence in Canada,” Angelique Mannella, former Associate Vice Principle of Innovation at McGill told MTLinTECH last year. “Seeing across the country we have research strengths and then in particular in Montreal we have research strengths in our artificial intelligence and two of our lead researchers happen to be women and isn’t that a great thing?”

The researchers Mannella was referring to are Doina Precup and Joelle Pineau, both leading researchers in artificial intelligence (AI) at McGill who have been instrumental in getting the program off the ground. Last January Microsoft gifted the university with $1 million for AI research after acquiring Montreal-based Maluuba, a deep-learning research startup. Indeed the city has been gaining a notable reputation in the AI field over the past year. The Summer Lab program couldn’t come at a more opportune time.

Those responsible for building AI must be representative of the population they intend to serve. With women making up 7% of CTO positions globally, it is clear that we are missing a whole generation of technologists in the development of AI.

“The AI and tech industry is not very inclusive towards women,”Annie-Claude Devriese, General Manager of Notman House and of the organizers of this year’s program told MTLinTECH. “Basically there’s a problem with not having enough women in key positions in AI and tech in general. So the program was created to empower women with developing skills and getting them to have a bigger network. That way when they’re transitioning from studying into the workforce they already have a built-in professional network.”

The six week program includes two weeks of classes in machine learning technology, led by AI professionals such as Doina Precup, graduate students, and others involved in the industry.

READ ALSO: McGill Innovation launches AI For Social Good Summer Lab for women

“After that there’s a full week of workshops. It’s a program where we really want to include our sponsors and have them participate. This year some of them will be giving workshops, such as Element AI and Real Ventures. After that week, the women will break into teams of two or three and they will develop their own project. There is a wrap event and presentation—it’s not called a demo day—but they will be able to present the projects they’ve been working on all summer.”

The program will culminate in a hackathon open to anyone and aimed at solving a designated social problem.

“The hackathon is one part of the program where we wanted to ensure that, while the program is currently only open to female participants, the power of machine learning and AI applied to a social challenge needs lots of people of all different backgrounds to think about and to work on solutions. So we wanted to keep that open to anyone and everyone from Montreal and outside of the city that wants to participate,” Mannella told MTLinTECH.

The AI for Social Good Hackathon will take place May 26th-27th and is open to any member of the public, regardless of gender identification.



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