We are publishing a blog series on the brilliant women involved in the Women in Machine Learning program last year.
Whoever you are, and whatever your background we are sure you will find their thoughts on Machine Learning, inclusion and their stories inspirational and inspiring.
Pictured above with Massimo Banzi of Arduino (Image:Ayesha Ahmed), Ayesha is an absolute dynamo. Active in the hacker and open source communities, Ayesha has a talent for communicating complex technologies to a wide audience and a passion for bringing education to low-income countries through technology. Check out her submission for the Breakthrough Junior Challenge here (she was a global finalist and the 2018 champion for Australia!). She also won the 2018 Internet Freedom Hackathon. Currently studying a Bachelor of Science, Data Science Major and interning at Peter MacCallum Cancer Research Centre Ayesha is one to watch!
What gets you excited about Machine Learning, and what makes you want to learn more?
I strongly reverberate with the ethics of hacker culture: find problems and create efficient solutions. I see technology not as an end goal, but as one of the strongest tools we have to create solutions. Machine learning is just one technology in particular that has an incredible amount of potential to solve a huge number of problems in the future. While it isn’t the only instrument, it is definitely a relevant one and one that developers and changers should strive to learn about.
What diversity initiatives would you like to see in the MLAI industry?
I would love to see more frequent women and LGBTQ oriented workshops and scholarships! I know so many talented women and people in minorities that don’t pursue technology in-depth not because they are lacking the skills, but because they think “it isn’t for them” and they are rarely told otherwise. These initiatives will help alleviate this huge gap and help grow an untapped intellectual resource.
What was your favourite part of the Women in Machine Learning program, or what did you get most out of?
As cheesy as this sounds, my favourite part was making mistakes. I love the process of getting closer to figuring something out; it makes one want to achieve more.
What is next for you on your Machine Learning journey?
At the moment, I’m cramming for finals! I’m thinking about working on a project to alleviate algorithmic bias.
What advice do you have for anyone from an underrepresented group in entering a career in tech?
There will always be those who tell you you are not enough, but you must not let this turn into a self-fulfilling prophecy. Speak out, scream, work hard, reach for more than you can grasp, make mistakes, invent, lift others and find a team. Collectively, our voices cannot be silenced if we keep reaching for each other. So do as much as you can.
Do you or your company what to support the Women in Machine Learning program in 2019? Register your interest here.
We will be opening applications for the Women in Machine Learning program later in 2019. Register your details here to be amongst the first to apply.
Interested in a career in Machine Learning? We are hiring, check out our current openings here.