Posted by Rixa Bugelli

National Learn to Code Day: Women & AI

On September 23rd, 2017, our Ladies Learning Community woke up early to prepare for our Fifth Annual National Learn to Code Day. Our Chapter Leads set-up their events, our Lead Instructors took their stage, our mentors prepared the learners and we plugged in to livestream all for one purpose – to provide women the access to education on Artificial Intelligence and Machine Learning.

This day was months in the making and started through our relationship with Georgian Partners and the goal to challenge ourselves to offer a National Learn to Code Day workshop topic that was relevant and on the forefront of technology. Through Georgian Partners, we were introduced to Parinaz Sobhani, their Director of Machine Learning, to develop content that would expose and educate women on the use and importance of Artificial Intelligence and Machine Learning.

We could not have been more fortunate to spend the months leading up to National Learn Code Day working with Parinaz on developing content that would be presented to over a thousand learners nationwide. We also had Parinaz’s support in delivering comprehensive training for all of our instructors and mentors so that they could champion the delivery at all of our events.

Shortly after we had committed ourselves to developing content centralized on Artificial Intelligence and Machine Learning, we had Accenture jump onboard as our title sponsor for the day. We gained both Accenture’s enthusiasm to support our mission of exposing women to AI, as well as the support from Jodie Wallis, Accenture’s own Managing Director for Artificial Intelligence in Canada, who provided our audience of women inspiring words to explore Artificial Intelligence literacy and who kicked off National Learn to Code Day with her own personal story of becoming personally invested in technology.

Our support from women in the field of Artificial Intelligence and Machine Learning did not stop there. Kathryn Hume, Vice President of Product and Strategy for integrate.ai, contributed to the conversation on Artificial Intelligence and the importance of bridging the bias by presenting insight into what Artificial Intelligence is and why diversity in the field is necessary.

It’s critical that women, as well as Canadians from diverse backgrounds, understand and get engaged in the conversation around AI so that they can help set the goals as what qualifies as intelligent” says Kathryn. The content that we developed didn’t just aim to deliver new skill development, but also illuminated why it was important for more women to be involved in the field of Artificial Intelligence. Kathryn continues that  “we don’t want to create a future in which the tasks that we set for these systems are only representative of the goals of a minority of our population”.

The need to have more women involved in the development of Artificial Intelligence is what stood at the forefront of the content we developed. Before diving into the application of AI and Machine Learning, we started with demystifying Artificial Intelligence and highlighting the impact that Artificial Intelligence will have on the world around us; such as replacing 16% of jobs over the next decade and the unsettling truth that “twice as many women than men are likely to lose their jobs as automation replaces human labor.” according to the World Economic Forum.

From there, we introduced our learners to the key player in Artificial Intelligence and Machine Learning: Data! In order to build AI and get our machines to learn, we need to supply it with a healthy amount of data to use to make predictions and create models.

We had set-out with a goal to have all our 1100+ learners contribute to a singular database and have it stored in one data file. However, we have a history of breaking something during our national initiatives and Google Sheets was not able to handle the number of users accessing the sheet and kicked us all out – a bittersweet moment, We are always prepared and had back-up data files that were accessible to all learners so we migrated to those instead.

From there, we introduce the data software we would be using to create our models called Dataiku. Thanks to support from AWS, all of our 1100+ learners had access to the software nationwide.  We introduced the software, took a tour of it’s functionality  and set out with our learners to help solve a problem, using a core of AI, Machine Learning!

We explored the different methods of Machine Learning: supervised, unsupervised, deep and reinforced. We then worked through the Data Scientist’s Workflow to prepare, train and test different Machine Learning models.

We hosted 37 events and reached 1150+ learners and had the support of over 300 mentors from coast to coast and could not be more touched by the success (and support) that we experienced for this National Learn to Code Day. Our hashtag #llcCodeDay trended in Canada and our learners expressed so much interest and excitement in being provided with the access to learn about Artificial Intelligence and Machine Learning.

We also reached a global audience this year, with women joining us from Hong Kong, Spain and Slovakia, by providing a livestream of one of the workshops. We had 70 viewers join to learn remotely, with women dominating at 76% of the views.

This opportunity to expose women to Artificial Intelligence and Machine Learning concepts has definitely left us feeling that this was our most impactful and innovative National Learn to Code Day yet, and thanks to our title sponsor Accenture and Parinaz Sobhani, Georgian Partners, Jodie Wallis, Kathryn Hume, Dataiku and AWS, we were successful in providing indispensable exposure to women across Canada (and globally!) and making an impact on the future of Artificial Intelligence.