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Future Work & Education
From an AI PerspectiveSega Cheng (程世嘉 )
Co-founder/CEOStraaS & LIVEhousefb.me/segacheng
About Me
We Enable Your Online Video Business
The world as we know it
Self-Driving Truck OTTO - 2016The world's first shipment by self-driving truck, a 120-mile journey with no driver in front seat.
190 KM trip50,000 cans of beer
Technology
Source: NVIDIA
Deep Learning
ImageNet Challenge 2011 - 2015
What Deep Learning is Capable of
What Deep Learning is Capable of (cont’d)
Artificial General Intelligence
Jobs, Income, Automation
John Henry1870Talcott,West Virginia
“The Influence of machinery on the interests of the
different classes of society”
- David Richardo 1821
“The Return of the Machinery Question”
- The Economist 2016
Jobs
How Susceptible are Jobs to Computerisation?
Carl Benedikt Frey · Michael Osborne - Sep. 2013
Automated Vehicles Case Study (2016)
What Kind of Jobs will AI Create?
1.Engage w/ existing AI technologies
2.Develop new AI technologies
3.Supervise AI technologies in practice
4.Facilitate Societal shifts that accompany AI technologies
Credit: James Hodson
Income(不患寡而患不均 , 孔子 )
Top 0.01% Income Share, 1913 - 2015
Wealth Inequality (World) - 2014
GDP per capita vs. Median Personal Income 2015 (US)
The great decoupling
Non-Farm Labor and Corporate Profits Share of GDP
Trended up over the last 2 years though
Is College Degree Important? Yes
Policy
(1940)
3 Attitudes towards AI
●Optimist: Ray Kurzweil, Peter Diamandis, Larry Page, Sergey Brin
●Pessimist: Stephen Hawking, Elon Musk, Nick Bostrom, Martin Ford
●Pragmaticist: Erik Brynjolfsson, Thomas Davenport
● Research Goal: The goal of A.I. research should be to create not undirected intelligence, but beneficial intelligence.
● Research Funding: Investments in A.I. should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:
○ How can we make future A.I. systems highly robust, so that they do what we want without malfunctioning or getting hacked?
○ How can we grow our prosperity through automation while maintaining people’s resources and purpose?○ How can we update our legal systems to be more fair and efficient, to keep pace with A.I., and to
manage the risks associated with A.I.?○ What set of values should A.I. be aligned with, and what legal and ethical status should it have?
● Science-Policy Link: There should be constructive and healthy exchange between A.I. researchers and policy-makers.
● Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of A.I.
● Race Avoidance: Teams developing A.I. systems should actively cooperate to avoid corner-cutting on safety standards.
● Safety: A.I. systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.
● Failure Transparency: If an A.I. system causes harm, it should be possible to ascertain why.● Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a
satisfactory explanation auditable by a competent human authority.● Responsibility: Designers and builders of advanced A.I. systems are stakeholders in the moral implications of
their use, misuse, and actions, with a responsibility and opportunity to shape those implications.● Value Alignment: Highly autonomous A.I. systems should be designed so that their goals and behaviors can be
assured to align with human values throughout their operation.
The Asilomar A.I. Principles (Jan 2017)
● Human Values: A.I. systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.
● Personal Privacy: People should have the right to access, manage and control the data they generate, given A.I. systems power to analyze and utilize that data.
● Liberty and Privacy: The application of A.I. to personal data must not unreasonably curtail people’s real or perceived liberty.
● Shared Benefit: A.I. technologies should benefit and empower as many people as possible.● Shared Prosperity: The economic prosperity created by A.I.I should be shared broadly, to benefit all of humanity.● Human Control: Humans should choose how and whether to delegate decisions to A.I. systems, to accomplish
human-chosen objectives.● Non-subversion: The power conferred by control of highly advanced A.I. systems should respect and improve,
rather than subvert, the social and civic processes on which the health of society depends.● A.I. Arms Race: An arms race in lethal autonomous weapons should be avoided.● Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on
future A.I. capabilities.● Importance: Advanced A.I. could represent a profound change in the history of life on Earth, and should be
planned for and managed with commensurate care and resources.● Risks: Risks posed by A.I. systems, especially catastrophic or existential risks, must be subject to planning and
mitigation efforts commensurate with their expected impact.● Recursive Self-Improvement: A.I. systems designed to recursively self-improve or self-replicate in a manner that
could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.● Common Good: Superintelligence should only be developed in the service of widely shared ethical ideals, and
for the benefit of all humanity rather than one state or organization.
The Asilomar A.I. Principles (Jan 2017) - Cont’d
Scrutability and Accountability(AI’s Black-Box Problem)
EU: “Right to Explanation” April 2016
Policy Responses - R&D, Education, Safety Net1.Invest in and develop AI for its many benefits
a. Cyberdefense
b. Detection of fraudulent transactions and messages
2.Educate and train people for jobs of the futurea. Expand the availability of job-driven training and opportunities for lifelong learning
3.Aid workers in the transition and ensure broadly shared growtha. Modernize the social safety net
Research & Development Strategic Plan1.Make long-term investments in AI research2.Develop effective methods for human-AI collaboration3.Understand and address the ethical, legal, and societal implications
of AI4.Ensure the safety and security of AI systems5.Develop shared public datasets and environments for AI training
and testing6.Measure and evaluate AI technologies through standards and
benchmarks7.Better understand the national AI R&D workforce needs
0.1%
Education
Return of the MOOC
The current phase of digital unbundling can pave the way to more flexible, lifelong learning journeys
McKinsey & Company
Learn how to re-learn quickly
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