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
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.
Deep Learning Summit
International Women's Day
Women in Tech