Women in ML Symposium (Dec 7, 2022): Building Better People with AI and ML

Posted by the TensorFlow Team

Join us tomorrow, Dec. 7, 2022, for Dr. Vivienne Ming’s session at the Women in Machine Learning Symposium at 10:25 AM PST. Register here.

Dr. Vivienne Ming explores maximizing human capacity as a theoretical neuroscientist, delusional inventor, and demented author. Over her career she’s founded 6 startups, been chief scientist at 2 others, and launched the “mad science incubator”, Socos Labs, where she explores seemingly intractable problems—from a lone child’s disability to global economic inclusion—for free.

A note from Dr. Vivienne Ming:

I have the coolest job in the whole world. People bring me problems:

  • My daughter struggles with bipolar disorder, what can we do?
  • What is the biggest untracked driver of productivity in our company?
  • Our country’s standardized test scores go up every year; why are our citizens still underemployed?

If I think my team and I can make a meaningful difference, I pay for everything, and if we come up with a solution, we give it away. It’s possibly the worst business idea ever, but I get to nerd out with machine learning, economic modeling, neurotechnologies, and any other science or technology just to help someone. For lack of a more grown up title I call this job professional mad scientist and I hope to do it for the rest of my life.

The path to this absurd career wound through academia, entrepreneurship, parenthood, and philanthropy. In fact, my very first machine learning project as an undergrad in 1999 (yes, we were partying like it was) concerned building a lie detection system for the CIA using face tracking and expression recognition. This was, to say the least, rather morally gray, but years later I used what I’d first learned on that project to build a “game” to reunite orphaned refugees with their extended family. Later still, I helped develop an expression recognition system on Google Glass for autisttic children learning to read facial expressions.

As a grad student I told prospective advisors that I wanted to build cyborgs. Most (quite justifiably) thought I was crazy, but not all. At CMU I developed a convolutional generative model of hearing and used it to develop ML-driven improvements in cochlear implant design. Now I’m helping launch 3 separate startups mashing up ML and neurotech to augment creativity, treat Alzhiemers, and prevent postpartum depression of other neglected hormonal health challenges.

I’ve built ML systems to treat my son’s type 1 diabetes, predict manic episodes, and model causal effects in public policy questions (like, which policies improve job and patent creation by women entrepreneurs?). I’ve dragged you through all of the above absurd bragging not because I’m special but to explain why I do what I do. It is because none of this should have happened—no inventions invented, companies launched, or lives saved…mine least of all.

Just a few years before that CIA face analysis project I was homeless. Despite having every advantage, despite all of the expectations of my family and school, I had simply given up on life. The years in between taught me the most important lesson I could ever learn, which had nothing to do with inverse Wishart Distributions or Variational Autoencoder. What I learned is that life is not about me. It’s not about my happiness and supposed brilliance. Life is about our opportunities to build something bigger than ourselves. I just happen to get to build using the most overhyped and yet underappreciated technology of our time.

There’s a paradox that comes from realizing that life isn’t about you: you finally get to be yourself. For me that meant becoming a better person, a person that just happened to be a woman. (Estrogen is the greatest drug ever invented—I highly recommend it!) It meant being willing to launch products not because I thought they’d pay my rent but because I believed they should happen no matter the cost. And every year my life got better…and the AI and cooler 🙂

Machine learning is an astonishingly powerful tool, and I’m so lucky to have found it just at the dawn of my career. It is a tool that goes beyond my scifi dreams or nerd aesthetics. It’s a tool I use to help others do what I did for myself: build a better person. I’ve run ML models over trillions of data points from hundreds of millions of people and it all points at a simple truth: if you want an amazing life, you have to give it to someone else.

So, build something amazing with your ML skills. Build something no one else in the world would build because no one else can see the world the same as you. And know that every life you touch with your AI superpower will go on to touch innumerable other lives.

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