Machine Learning 2016
In AI We Trust? Ethics & Bias in Machine Learning
September 16, 2016
The big data era enabled organizations to store more data at a lower cost, and process data more quickly and efficiently. Organizations now seek ways to transform their data into meaningful insights, insights that inspire new products, drive revenue, or enable automation that impacts the bottom line.
Machine learning is at the center of this next wave of innovation and growth. But to use new algorithms effectively, organizations should first understand how they work, the reality vs. the hype, and the unique challenges and opportunities to the private sector and society at large.
Attendees & Speakers
Matt Abrams
Seven Peaks Ventures
Kathryn Hume
Fast Forward Labs
Clare Corthell
Luminant Data
Ray Velez
Razorfish
Angelique Augereau
Independent Consultant
Jon MIller
Cylance
Ron Talwalkar
Cylance
David Archer
Galois
Bill Welser
RAND Corporation
Jeff Larson
ProPublica
Aaron Rieke
Upturn
Katie Amrine
Insight Data Science
Moises Goldszmidt
Samsung
Scott Penberthy
PwC
Doug Downey
Northwestern University
Diego Klabjan
Northwestern University
Osonde Ope Osoba
RAND Corporation
Amelia Taylor
Insight Data Science Fellow /
Alice Albrecht
Simple Finance
Adam Carroll
Amplion
Jeff Alpen
Blink UX
Tony Falco
Silicon Valley Data Science
Jeff Carr
SlamData
Alex Trisoglio
McKinsey
Yong Bakos
OSU-Cascades
Brian Brennan
Pacific Crest Securities
John Hummel
District Attorney
Christopher Whittam
Nike
Mounir Shita
Kimera Systems
Dave Baiocchi
RAND Corporation
Tom Egan
Launch Capital
Preston Callicut
Five Talent Software
Seth Taylor
Amplion
Silvano Gai
Cisco Fellow
Mark Thompson
Cylance
Bruce Cleveland
Wildcat Venture Partners
Samih Fadli
Publicis.Sapient / Razorfish
Andrew Duchon
Manzama
Argyro Karanasiou
Bournemouth University
Lior Kogot
Oracle
Agenda
Machine Learning Summit Agenda
Welcome Dinner & Reception
09/15/16
5:30pm – 8:00pm
The 1001 Tech Center, 1001 SW Emkay Drive, Bend, OR 97702
Opening Remarks
09/16/16
9:00am – 9:10am
Matt Abrams, Seven Peaks Ventures
Fairness, Bias, Interpretability: The Ethics of Algorithms
9:10am – 9:35am
Kathryn Hume, Fast Forward Labs
Engineering for Ethics
9:35-10:05
Clare Corthell, Luminant Data
Fairness in Practice: Marketing with Machine Learning
10:05am – 10:45am
Ray Velez, Razorfish | Angelique Augereau, Independent Consultant
Security & Trust in the Age of AI: A Business Perspective
11:00am – 11:45am
Jon Miller & Ron Talwalkar, Cylance | David Burke, Galois
Angelique Augereau, Independent Consultant
Machine Learning and the Future of Jobs and Labor
11:45am – 12:30pm
Bill Welser, RAND Corporation
Lunch
12:30pm – 1:30pm
Designing for Conversational AI and ML Interfaces – A Q&A Session on Lessons from the Field
1:30pm – 2:00pm
Jeff Alpen, Blink UX
Algorithmic Law Enforcement: Social Justice Issues
2:00pm – 2:30pm
Jeff Larson, ProPublica | Aaron Rieke, Upturn | Katie Amrine, Insight Data Science
Fact or Fiction? Cutting through the Hype around AI
3:00pm – 3:30pm
Moises Goldszmidt, Samsung | Scott Penberthy, PwC | Kathryn Hume, Fast Forward Labs
Advancements in Academic Research
3:45pm – 4:15pm
Doug Downey & Diego Klabjan, Northwestern
Realities, Obstacles & Requirements for Enterprise AI Startups
4:15pm – 5:15pm
Discussion and Demos from Amplero, Amplion, Enlitic, Gridspace, and Manzama
Dinner
6:00pm – 9:00pm
Breakfast and Outdoor Adventure
09/17/16
8:00am – 11:00am
Informal breakfast and hike in the beautiful local surroundings
Companies
