As we begin to harness the power of artificial intelligence, machine learning, and data science in our everyday lives, we also raise complex ethical and social questions associated with bias, fairness, and transparency of algorithmic intelligence. In this panel we get into the thick of the issue. How can we best use AI with shared responsibilities between humans and systems? How can we balance the need for efficiency and exploration with fairness and sensitivity to users? How do we ensure that individuals and communities can trust these systems? Join our discussion to enrich your understanding of human-AI interaction, and how these questions will be answered in AI research, education and policies, as we strive to improve the human condition.
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AI for Social Good
Social “good” comes in many forms
Better education
Faster, cheaper drug discovery
More effective policy making
Predicting and responding to natural disasters, epidemics
And much more ….
Commonly accepted attributes of “AI for Social Good”
Collaboration of multiple disciplines, especially social sciences and AI
Public-private partnership + nonprofits-academia-industry collaboration
Open access to technological resources
Considerations of bias, fairness, and accountability of ML algorithms
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Current State
Growing investments across academia, industry, and government
Several academia-based centers of “AI for Social Good” or “AI in Society” have emerged in
recent years with diverse themes ranging from algorithms to policy
Industry initiatives span in-house efforts and extramural community creation efforts such as
the NSF-Amazon Fairness Program for funding fairness research in academia
Substantial Government investments – e.g. DARPA LORELEI, Memex, World Modelers, XAI and
many other programs
Emergence of conferences and workshops
FATML – Fairness, Accountability and Transparency in ML
AI for Social Good workshop at NeurIPS
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Current State – AI Stack View
Apps
Toolkits
ML Dev
Environments
Algorithms
Compute / Storage
Mostly Open source (e.g. MXNet) but includes
dev environments like Alexa Skills Kit
Requires targeted funding for fairness,
transparency, etc.
Requires Funding
Cost-effective models of access
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Alexa Skills for Social Good
Organized contest in 2018 to encourage creation of Alexa skills for social good
Red Cross skills: hurricane alerts, scheduling blood donations, and first aid
Environmental consciousness skills: recycle Game, EVIE assistant, compost tracking, bike sharing
Access skills: My Talking Newspaper, Safe and Well (check on status of relatives)
Language Preservation (with the Alexa Cleo Skill)
Cleo skill harnesses the expertise of multilingual Alexa users to teach Alexa new languages or
dialects. Through a crowdsourcing model, users can help expand Alexa to new locales and
languages, bringing the technology to more people around the world.
Users have taught Alexa languages such as Hindi, Korean, Russian, Klingon and many more.
We are conducting an internal pilot to evaluate programs to support language preservation
with Indigenous languages such as Lakota and Ojibwe.
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Doing Well by Doing Good*
“How People with Disabilities Are Using AI to Improve Their Lives”
“It was the first time since he was a toddler playing with a rattler that he was able to interact with
something all by himself,” James says. “This Echo device goes way beyond ordering groceries or looking
up a recipe for us."
--- NPR Nova 30 January 2019
“How the Alexa Robot brought internet-based learning to a remote village school in Maharashtra”
“….. people on ground zero have emerged as change-makers themselves with a little help from Amazon
devices. Here’s one such story that is nothing but a triumph of human imagination.”
“In the hot, dry, and dusty village of Warud in Maharashtra’s Amravati district, a 31-year-old
schoolteacher is using Alexa to impart lessons to kids of farmers and labourers employed in the vicinity.”
--- Yourstory.com and The Hindu newspaper, 4 Feb 2019
*Prof. Andrew Lo at re:MARS 2019
22. Information &
Intelligent Systems
Computing &
Communication Foundations
Computer & Network
Systems
Advanced
Cyberinfrastructure
Panel: AI for Social Good - Fairness, Ethics, Accountability, and Transparency
AWS Public Sector Summit
Jim Kurose
Assistant Director, NSF
Computer & Information Science & Engineering
Federal AI R&D Activities: a view from NSF
23. AI: ongoing US government activities
AI Executive Order
(Feb 2019)
HSST AI Roundtable (May 2019)
Congress
Senate, House
legislative
activities
AI Convening @ NSF (May 2019)
Envisioning National AI R&D Institutes
Policy and principles
Objectives
Roles and responsibilities
Federal Investment in AI R&D
Data, Computing for AI R&D
Guidance for Regulation of AI
Applications
AI and the American workforce
Action Plan for Protection of the United
States Advantage in AI
24. AI principles
Principles for responsible
stewardship of trustworthy AI
Inclusive growth, sustainable
development and well-being
Human-centred values and
fairness
Transparency and explainability
Robustness, security and safety
Accountability
National policies and
international co-operation for
trustworthy
Investing in AI R&D
Fostering a digital ecosystem for AI
Building human capacity,
preparing for labour market
transformation
International cooperation for
trustworthy AI
OECD Principles on AI, May 22, 2019
25. Fairness in the AI System Lifecycle
Artificial Intelligence in Society, June 12, 2019
26. NSF Leadership in AI
NSF invested nearly $450M
in AI research (core,
applications, systems,
infrastructure) in FY18
$
Thought Leadership Across USG
Innovative Programmatics
NSTC Select Committee on AI
NSTC Subcommittee on ML & AI
NSTC AI Interagency Working Group (under
NITRD): 2016, 2019 AI R&D Strategic Plans
OSTP Assistant Director(s) for AI
International: OECD, G7
Research Funding