Put AI to Work
April 15-18, 2019
New York, NY

Schedule: Ethics, Privacy, and Security sessions

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9:00am12:30pm Tuesday, April 16, 2019
Implementing AI
Location: Petit Trianon
Rachel Bellamy (IBM Research), Kush Varshney (IBM Research), KARTHIKEYAN NATESAN RAMAMURTHY (IBM Research), Michael Hind (IBM Research AI)
Rachel Bellamy, Kush Varshney, Karthikeyan Natesan Ramamurthy, and Michael Hind explain how to use and contribute to AI Fairness 360—a comprehensive Python toolkit that provides metrics to check for unwanted bias in datasets and machine learning models and state-of-the-art algorithms to mitigate such bias. Read more.
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11:05am11:45am Wednesday, April 17, 2019
Deepashri Varadharajan (CB Insights)
CB Insights tracks over 3,000 AI startups across 25+ verticals. While every vertical has benefited from deep learning and better hardware processing, the bottlenecks and opportunities are unique to each sector. Deepashri Varadharajan explores what's driving AI applications in different verticals like healthcare, retail, and security and analyzes emerging business models. Read more.
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11:05am11:45am Wednesday, April 17, 2019
Models and Methods
Location: Regent Parlor
Siwei Lyu (University of Albany)
Siwei Lyu reviews the evolution of techniques behind the generation of fake media and discusses several projects in digital media forensics for the detection of fake media, with a special focus on recent work on detecting AI-generated fake videos (DeepFakes). Read more.
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1:50pm2:30pm Wednesday, April 17, 2019
Anand Rao (PwC)
Broader AI adoption and gaining trust from customers requires AI systems to be fair, interpretable, robust, and safe. Anand Rao synthesizes the current research in FAT (fairness, accountability, and transparency) into a step-by-step methodology to address these issues—illustrated with case studies from the financial services and healthcare industries. Read more.
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2:40pm3:20pm Wednesday, April 17, 2019
Anna Gressel (Debevoise & Plimpton LLP), Jim Pastore (Debevoise & Plimpton LLP), Anwesa Paul (American Express)
Average rating: *****
(5.00, 1 rating)
Anna Gressel, Jim Pastore, and Anwesa Paul lead a crash course on the emerging legal and regulatory frameworks governing AI, including GDPR and the California Consumer Privacy Act. They also explore key lawsuits challenging AI in US courts and unpack the implications for companies going forward, helping you mitigate legal and regulatory risks and position your AI products for success. Read more.
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4:55pm5:35pm Wednesday, April 17, 2019
Models and Methods
Location: Grand Ballroom West
Yishay Carmiel (IntelligentWire)
Average rating: *****
(5.00, 1 rating)
In recent years, we've seen tremendous improvements in artificial intelligence, due to the advances of neural-based models. However, the more popular these algorithms and techniques get, the more serious the consequences of data and user privacy. Yishay Carmiel reviews these issues and explains how they impact the future of deep learning development. Read more.
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4:55pm5:35pm Wednesday, April 17, 2019
Implementing AI
Location: Rendezvous
Andrew Zaldivar (Google)
The development of AI is creating new opportunities to improve the lives of all people. It's also raising new questions about ways to build fairness, interpretability, and other moral and ethical values into these systems. Using Jupyter and TensorFlow, Andrew Zaldivar shares hands-on examples that highlight current work and recommended practices toward the responsible development of AI. Read more.
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1:00pm1:40pm Thursday, April 18, 2019
Interacting with AI
Location: Trianon Ballroom
Jeff Thompson (Stevens Institute of Technology)
What's it like to be a mobile phone or to attach a wind sensor to a neural network? Jeff Thompson outlines several recent creative projects that push the tools of AI in new directions. Part technical discussion and part case study for embedding artists in technical institutions, this talk explores the ways that artists and scientists can collaborate to expand the ways that AI can be used. Read more.
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1:00pm1:40pm Thursday, April 18, 2019
AI Business Summit
Location: Sutton North/Center
Joanna Bryson (University of Bath)
Although not a universally held goal, maintaining human-centric artificial intelligence is necessary for society’s long-term stability. Joanna Bryson discusses why this is so and explores both the technological and policy mechanisms by which it can be achieved. Read more.
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1:50pm2:30pm Thursday, April 18, 2019
Interacting with AI
Location: Regent Parlor
Forough Poursabzi-Sangdeh (Microsoft Research NYC)
Forough Poursabzi-Sangdeh argues that to understand interpretability, we need to bring humans in the loop and run human-subject experiments. She describes a set of controlled user experiments in which researchers manipulated various design factors in models that are commonly thought to make them more or less interpretable and measured their influence on users’ behavior. Read more.
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2:40pm3:20pm Thursday, April 18, 2019
Case Studies, Machine Learning
Location: Sutton South
Alina Matyukhina (Canadian Institute for Cybersecurity)
Machine learning models are often susceptible to adversarial deception of their input at test time, which leads to poorer performance. Alina Matyukhina investigates the feasibility of deception in source code attribution techniques in real-world environments and explores attack scenarios on users' identities in open source projects—along with possible protection methods. Read more.
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2:40pm3:20pm Thursday, April 18, 2019
Implementing AI
Location: Trianon Ballroom
Ryan Mukherjee (JHU/APL), Neil Fendley (JHU/APL)
While deep learning has led to many advancements in computer vision, most research has focused on ground-based imagery. Ryan Mukherjee and Neil Fendley offer an overview of functional Map of the World (fMoW), an ImageNet for satellite imagery built to address this issue, and explain how you can attack or defend these deep learning models. Read more.