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Robert Monarch
Helping humans and machines play nicely together
Robert Monarch (formerly known as Robert Munro) is a senior machine learning manager at Apple, leading engineering teams focused on machine learning, annotation, anti-fraud, and privacy-preserving architectures for new products.3 He holds a PhD from Stanford University and is an expert in combining human and machine intelligence.1
Monarch has extensive experience in the tech industry, having worked at major companies including:
- Apple (current position)
- Amazon Web Services (Principal Product Manager)
- Figure Eight (CTO)
- Microsoft (Software Developer)
He has also founded AI startups and developed AI products for companies like Google and Amazon.13
Throughout his career, Monarch has focused on applying AI to critical problems in disaster response and public health. Notable achievements include:
- Managing a team of 2,000 people in the Haitian diaspora for real-time translation during the 2010 Haiti earthquake response2
- Leading the development of a digital archive for over 100 endangered languages3
- Taking AWS's first suite of Natural Language Processing and Neural Machine Translation products from conception to launch3
Monarch is also an author and instructor. He wrote the book "Human-in-the-Loop Machine Learning" and has developed courses on AI applications in climate change, disaster management, and public health.14
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Highlights
I'll be speaking on a panel later today with Andrew Ng, Juan M. Lavista Ferres & Iva Gumnishka. Looking forward to talking about how AI can impact the world positively and how to evaluate the risks!
I recently found that contextual machine learning models like BERT almost always prefer the pronoun "his" over "hers" or "theirs" when predicting the gender of who owns certain items.
When looking for ways to fix this, I found that the major AI technologies did not even recognize "hers" as a pronoun.
This was the lead story in the New York Times Business section yesterday: https://lnkd.in/e5kUrbC
Please also see my original post which sparked this story: https://lnkd.in/eyMY4aR
If you are interested in gender bias in AI, there are 20+ researchers mentioned in my article who are experts in this field
