IWD 2017: Interview with Accenture's Manager of AI

International Women’s Day takes place annually on 8 March, providing companies, institutions and individuals with an opportunity to discuss and promote diversity and equality around the world.  The day is celebrated widely throughout the tech and science communities as a way to champion gender parity. We're strong believers that diversity is essential to STEM fields, and that women entering tech and science as well as existing members should be encouraged and supported. To mark this year's International Women’s Day we’re interviewing Rumman Chowdhury, Senior Manager at Accenture AI, who spoke at the 2017 Deep Learning Summit in San Francisco. Rumman's passion lies at the intersection of artificial intelligence and humanity, with a background in economics, policy analysis, quantitative methods and political science. I spoke to her to learn about how she joined her field, the challenges she's faced, and more.Give us an introduction to who you are and what you do? My name is Rumman Chowdhury, and I am a quantitative social scientist, currently focused  on the ethics and responsible implementation of Artificial Intelligence.  What personally motivated you to begin your work in artificial intelligence? My interest lies in the intersection of humanity, data science, and artificial intelligence. Prior  to data science, quantitative social science was my only outlet for using sophisticated  modelling techniques to understand human behaviour. When data science became a field, I  moved to Silicon Valley to join the tech revolution. My motivation to work in ethical AI stems from my political science background. The  decisions we make in government and in big business have a strong moral message,  whether or not it is acknowledged. Tech is often afraid to say that their products have  implicit moral decisionmaking, but it does. Policy makers have struggled with this for ages –  for example – how do you create a policy that will affect millions of people differently? Is  the goal to create policy that helps the most people, or hurts the fewest? What do you do if  those two goals are at odds?  What do you find exciting about your current role? My role at Accenture is with our Global Artificial Intelligence team. My job has two main  parts – first, we are shifting Accenture to be an AI driven company at a rapid pace. That  means coordinating with industry leaders across all of our key clients and incorporating  useful AI solutions customized to their client needs. It’s an exciting and interesting role, as I  get to move beyond theory and into practical AI in fields that are sometimes resistant to  new technologies. The second part of my role is to drive our Responsible and Ethical AI initiatives. I’m deeply  interested in how the AI revolution will affect humanity – psychologically, physically,  economically, and legally. How can government and industry leaders use this technology for  good and to help people? What are the negative externalities of the AI revolution and how  do we mitigate them? There’s never a boring day here – I’m helping write position papers for the IEEE,  understanding international regulations on data security and protection, creating content to  train non-tech people on AI, arranging for prototyped AI technologies to be implemented at  our non-profit partners, and leading the AI portion of industry-changing projects.  How do you feel about being a woman in tech? Have you faced any challenges? Women are underestimated in tech. AI is a fascinating field to be in, because it’s the wild  west – you can accomplish as big as you dare to dream. That’s not aligned with the data  we’ve seen on how people perceive women. We’re expected to be facilitators, not leaders,  and are assessed by our ‘proof’, while men are assessed by their ‘potential’. There’s a clear  problem, then, with providing ‘proof’ for a field that’s new and untested. Any challenges I’ve faced in tech is the industry’s fear of facing these problems. It’s as if  people are allergic to discussing any problems with racism or sexism in the industry. Quite  surprising for a field that claims to thrive on ‘disruption’ and solving problems. There are a  few cases of companies truly implementing solutions, and not surprisingly, they are mostly  driven by women and minorities. Allyship is key, and as an industry, we have to learn not to  take these critiques so personally.  What advice would you give to someone starting a career in technology? Always be learning. Think about what will be big in the next five to ten years and align  yourself accordingly. Don’t get married to one type of technology or coding language. Be  flexible. Make friends in your industry outside of work – go to meetups and meet interesting  people. It’s the best way to remain passionate about the field.  What are your prediction for artificial intelligence in 2017 and over the next 3 years? That’s a hard one to answer! The field is evolving and changing rapidly. Regulation is going  to be big, as larger companies implement these solutions to scale, and we start seeing the  workplace being directly impacted. Government, unions, etc. are going to play a growing  role in Artificial Intelligence as we become concerned with legal and ethical implications.  Companies will be more thoughtful about the AI they produce as the industry will move  beyond making fun toys for tech-savvy types.See our Women in Tech & Science series for more Q&As.Are you working in emerging areas of science and technology, or know of someone who is? Suggest women in STEM fields to speak at a RE•WORK event here.