MLUX SF Networking Night: Google

May 9, 2018 · San Francisco, United States of America

**You must RSVP on Eventbrite to guarantee a spot since space is limited.**

It’s been a while since we have had a chance to chat and meet the folks that make up the MLUX community - it’s time for a happy hour! Join us for a networking night and happy hour at Google with the Kaggle and Trust and Safety team on May 9th from 6-8pm!

Two Google teams have graciously offered to sponsor our bi-annual happy hour and networking night. Unlike our previous tech talks, the focus of this event is to meet our community members and build connections, and share what we do with each other :)

Myles O’Neill is the lead product designer at Kaggle, a platform built to help the world learn from its data. Kaggle hosts a community of more than 1.6MM data scientists from around the world. Data scientists come to Kaggle to learn, collaborate, and compete in data science competitions.

Myles will talk about the problems data scientists face in collaborating with their peers and ensuring their work is reproducible, both on and off Kaggle. He will talk about the tools Kaggle is building to solve these problems and how Kaggle’s design team is able to work with their community to come to better design solutions.

There’s an open UX Designer role available on Myles’ team! - check it out here:

Trust and Safety
Andrew Smart is a user researcher at Google on the Trust & Safety team working on machine learning fairness and ethics. He will talk about the current landscape of ethical concerns around algorithmic fairness and touch on Google’s efforts in pursuing an ethically informed approach to machine learning. As machine learning is being deployed in a broader range of contexts including translation, image recognition, recommendations, medical diagnoses, autonomous vehicles, financial decisions, credit scoring, recruiting and more - questions about what and whose values are being encoded in the algorithms are becoming more urgent.

He will also talk about the need to take a human-centered approach to machine learning explainability and fairness. This means understanding what’s at stake for users from any background, and understanding the impact that increasingly pervasive algorithmic systems have on everyone.

6:00 - Doors Open/Networking
6:30 - Into to MLUX SF/Google Teams
7:00 - More Networking
8:00 - Event ends

This meetup is sponsored by the Center for Technology, Society & Policy fellowship in conjunction with the Algorithm Fairness and Opacity working Group at UC Berkeley.

Event organizers
  • Machine Learning & User Experience (MLUX) - SF Bay Area

    We’re excited about creating a future of human-centered smart products, and we believe the first step to doing this is to connect UX and Data Science/Machine Learning folks to get together and learn from each other. We're a mix of data scientists, designers, machine learning scientists, PMs and more - exploring a human centered approach to machine learning. Come join us! ------------------------------- This meetup is sponsored by the Center for Technology, Society & Policy fellowship in conjunction wit

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