The Age of Generative AI

Getting the Information Ecosystem Ready for the AI Revolution

Neil D. Lawrence

Future Insights, Judge Business School, University of Cambridge

The Atomic Human

E S A R I N T U L
O M D P C F B V
H G J Q Z Y X K W

Bauby and Shannon

Embodiment Factors

bits/min billions 2,000
billion
calculations/s 		~100 a billion
embodiment 20 minutes 5 billion years

1. Societal Norms

Sistine Chapel Ceiling

The Creation of Adam

For sale: baby shoes, never worn

New Flow of Information

Evolved Relationship

Evolved Relationship

Case Study – Social Media

2016 US Elections

Techonomy 16

. . . the idea that fake news on Facebook . . . influenced the election in any way I think is a pretty crazy idea

Mark Zuckerberg Techonomy 16, 10th November 2016

Facebook estimates that as many as 126 million Americans on the social media platform came into contact with content manufactured and disseminated by the IRA

Facebook evidence, 30th October 2017

2. Impact on People Function

Revolution

The Future of Professions

Intellectual Debt

Technical Debt

  • Compare with technical debt.
  • Highlighted by Sculley et al. (2015).

Separation of Concerns

Intellectual Debt

  • Technical debt is the inability to maintain your complex software system.

  • Intellectual debt is the inability to explain your software system.

Coin Pusher

Case Study – Horizon Scandal

The Horizon Scandal

The Sorcerer’s Apprentice

The Open Society and its Enemies

If in this book harsh words are spoken about some of the greatest among the intellectual leaders of mankind, my motive is not, I hope, to belittle them. It springs rather from my conviction that, if our civilization is to survive, we must break with the habit of deference to great men. Great men may make great mistakes; and as the book tries to show, some of the greatest leaders of the past supported the perennial attack on freedom and reason.

3. Tasking: Composition, performance, tracking

Networked Interactions

The Structure of Scientific Revolutions

suggests that

The MONIAC

HAM

Human Analogue Machine

A Question of Trust

A Question of Trust

Again Univesities are to treat each applicant fairly on the basis of ability and promise, but they are supposed also to admit a socially more representative intake.

There’s no guarantee that the process meets the target.

Onora O’Neill A Question of Trust: Called to Account Reith Lectures 2002 O’Neill (2002)]

Conclusions

  • Information revolution, not intelligence
  • Capabilities typically designed by developer not deployer.
  • Providing opportunities to empower employees, but temptation to treat as automatons
  • Intelligent accountability (Baroness O’Neill) will remain vital.

Thanks!

  • book: The Atomic Human

  • twitter: @lawrennd

  • The Atomic Human pages atomic human, the 13 , Le Scaphandre et le papillon (The Diving Bell and the Butterfly) 10–12, Bauby, Jean Dominique 9–11, 18, 90, 99-101, 133, 186, 212–218, 234, 240, 251–257, 318, 368–369, Shannon, Claude 10, 30, 61, 74, 98, 126, 134, 140, 143, 149, 260, 264, 269, 277, 315, 358, 363, embodiment factor 13, 29, 35, 79, 87, 105, 197, 216-217, 249, 269, 353, 369, Michelangelo, The Creation of Adam 7-9, 31, 91, 105–106, 121, 153, 206, 216, 350, baby shoes 368, Cambridge Analytica 371, Zuckerberg, Mark; Techonomy 16 and 79-80, Facebook; US Senate Intelligence Commitee and 80, Facebook 1-5, 15, 24, 55, 69-71, 77-78, 80-87, 100-102, 107, 114, 140, 229, 234-236, 302, 322, 349, 365, 371-373, cuneiform 337, 360, 390, intellectual debt 84, 85, 349, 365, separation of concerns 84-85, 103, 109, 199, 284, 371, intellectual debt 84-85, 349, 365, 376, Horizon scandal 371, sorcerer’s apprentice 371-374, Popper, Karl The Open Society and its Enemies 371–374, MONIAC 232-233, 266, 343, human-analogue machine (HAMs) 343-347, 359-359, 365-368.

  • podcast: The Talking Machines

  • newspaper: Guardian Profile Page

  • blog posts:

    The Open Society and its AI

References

Lawrence, N.D., 2017. Living together: Mind and machine intelligence. arXiv.
O’Neill, O., 2002. A question of trust. Cambridge University Press.
Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner, D., Chaudhary, V., Young, M., Crespo, J.-F., Dennison, D., 2015. Hidden technical debt in machine learning systems, in: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (Eds.), Advances in Neural Information Processing Systems 28. Curran Associates, Inc., pp. 2503–2511.
Susskind, R.E., Susskind, D., 2015. The future of the professions: How technology will transform the work of human experts. Oxford University Press.