Future work and education - From an AI Perspective

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Future Work & Education From an AI Perspective Sega Cheng ( 程程程 ) Co-founder/CEO StraaS & LIVEhouse fb.me/segacheng

Transcript of Future work and education - From an AI Perspective

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Future Work & Education

From an AI PerspectiveSega Cheng (程世嘉 )

Co-founder/CEOStraaS & LIVEhousefb.me/segacheng

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About Me

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We Enable Your Online Video Business

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straas.io

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The world as we know it

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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

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Technology

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Source: NVIDIA

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Deep Learning

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ImageNet Challenge 2011 - 2015

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What Deep Learning is Capable of

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What Deep Learning is Capable of (cont’d)

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Games for Training AI - Self-Driving Cars

Source: DeepDrive.io

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Artificial General Intelligence

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Jobs, Income, Automation

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John Henry1870Talcott,West Virginia

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“The Influence of machinery on the interests of the

different classes of society”

- David Richardo 1821

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“The Return of the Machinery Question”

- The Economist 2016

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Jobs

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How Susceptible are Jobs to Computerisation?

Carl Benedikt Frey · Michael Osborne - Sep. 2013

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Automated Vehicles Case Study (2016)

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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

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Income(不患寡而患不均 , 孔子 )

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Top 0.01% Income Share, 1913 - 2015

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Wealth Inequality (World) - 2014

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GDP per capita vs. Median Personal Income 2015 (US)

The great decoupling

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Non-Farm Labor and Corporate Profits Share of GDP

Trended up over the last 2 years though

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Is College Degree Important? Yes

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Policy

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(1940)

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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

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● 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)

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● 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

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Scrutability and Accountability(AI’s Black-Box Problem)

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EU: “Right to Explanation” April 2016

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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

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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

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0.1%

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Education

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Return of the MOOC

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The current phase of digital unbundling can pave the way to more flexible, lifelong learning journeys

McKinsey & Company

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Learn how to re-learn quickly

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Follow Me on Facebook

Sega Cheng

And we are hiring!