The document is IBM's response to the White House Office of Science and Technology Policy's request for input on artificial intelligence. It addresses 11 topics, providing an overview of key issues like the use of AI for public good, the social and economic implications of AI, important research gaps, and the need for multi-disciplinary collaboration and open data sets to advance the field safely. It recommends focusing on skills and having a responsible dialogue to develop AI for societal benefit.

1. The Future of Artificial Intelligence:
An IBM Research, Chief Science
Office Cognitive, Perspective
Guru Banavar, IBM VP, Chief Science Office Cognitive
Jim Spohrer, Director, Understanding Cognitive Systems
DRAFT v5: September 7, 2016
Note: This presentation has a companion whitepaper, available on request.
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2. Request:
White House OSTP
• The White House Office of Science and Technology Policy is particularly
interested in responses related to the following topics:
• (1) the legal and governance implications of AI;
• (2) the use of AI for public good;
• (3) the safety and control issues for AI;
• (4) the social and economic implications of AI;
• (5) the most pressing, fundamental questions in AI research, common to
most or all scientific fields;
• (6) the most important research gaps in AI that must be addressed to
advance this field and benefit the public;
• (7) the scientific and technical training that will be needed to take advantage
of harnessing the potential of AI technology;
• (8) the specific steps that could be taken by the federal government,
research institutes, universities, and philanthropies to encourage multi-
disciplinary AI research; and
• (9) the use of open data sets to close fundamental research gaps;
• (10) the role of incentives and prizes to accelerate public benefits;
• (11) any additional information related to AI research or policymaking, not
requested above, that you believe OSTP should consider.
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3. Response: IBM Chief Science Office Cognitive
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4. A. The Use of AI for the Public Good
• Healthcare
• Social Services
• Education
• Financial Services
• Transportation
• Public Safety
• The Environment
• Infrastructure
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5. B. Social and economic
implications of AI
• History: Technologies with broad
potential across industries like AI
increase:
• Productivity
• Earnings
• Job growth
• Adjustment: Social, learning, and
decision making capabilities are
key to acceptance of AI in society
• Underserved: Potential to help
underserved populations and
improve their quality of life
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6. C. Education for
harnessing AI technologies
• Demand: High demand for AI,
machine learning, data science and
related courses; many MOOCs
• Industry Platforms: Growing set of
companies provide learners access to
cognitive service capabilities in their
clouds
• Gap: Need curriculum for learners
with no programming or advanced
mathematics background
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7. D. Fundamental questions
in AI research, and
the most important
research gaps
• Machine learning and reasoning
• Decision techniques
• Domain-specific AI systems
• Data assurance and trust
• Radically efficient computing
infrastructure
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8. E. Data sets that can
accelerate AI research
• Bottleneck: Develop and validate
data sets that are:
• Large and unbiased
• Openly curated
• Publically accessible
• Domains: Novice to expert task
performance is hard to get for all
occupations and industries
• Models: Incentives to share trained
models that require lots of data and
compute time to create
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9. F. Multi-disciplinary
research
• Disciplines: Breadth of disciplines
to tackle issues:
• Psychology and cognitive science,
philosophy, design and art, public
policy and management, law and
regulations
• Systems: Professional associations
to tackle industry and system
issues, including novice to expert
progression on tasks
• Socio-technical system design
loop and smart service systems
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10. G. Role of incentives
and prizes
• Example:
• IBM Watson AI XPrize ($5M)
• Best AI system to empower teams
of people to tackle the world’s
grand challenges
• TED 2020, finalists present
• I-athlon
• More objective scoring
• Rational processes
• Multiple dimensions of intelligence
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11. H. Safety and
control issues for AI
• Trust & Trustworthiness
• Ethical & Social Norms
• Algorithmic Transparency
• Unexpected Interactions
• Safeguards
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12. I. Legal and governance
implications of AI
• Responsible & inclusive dialogue
• Elevate the dialogue
• Algorithmic responsibility
• Individual privacy
• Jobs and workforce transformation
• Safety
• Learn beyond the headlines
• Key: Focus on skills
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13. J. Other issues:
Business models
• Trusted platform
• Training – Unbiased data
• Algorithms - Transparency
• Services - Open API Economy
• Transactions – Blockchain
• Applications – Ethically boosting
creativity and productivity
• Governance – Laws and regulations
• Trust takes time
• Steam engines – boiler explosions
• Cognitive engines – headline hype
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14. Some reactions…
• aitrends
• Artificial Brilliance
• Futurism
• InformationWeek
• Calburn: “IBM: AI Should Stand For
‘Augmented Intelligence’
• PYMNTS
• TechCrunch
• Coldewey: “The White House
requested input on artificial
intelligence, and IBM’s response is a
great AI 101”
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15. White House OSTP
Follow Up
• The White House OSTP received
161 responses and created a 349
downloadable PDF with URL links
• The White House Frontiers
Conference is being planned as a
follow up meeting
• Date: October 13, 2016
• Place: Pittsburgh, PA USA
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16. Acknowledgements
• Sam Adams
• Guru Banavar
• Rob High
• Mark O’Riley
• Francesca Rossi
• Vijay Saraswat
• Anna Sekaran
• John R Smith
• Jim Spohrer
• Peter Williams
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