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Worker Productivity 20230628 v1.pptx
This document provides an agenda and materials for a post-industrial forum on knowledge worker productivity hosted by Jim Spohrer at SRI. The document includes: - An introduction and background on Jim Spohrer, a retired industry executive and UIDP senior fellow. - An agenda for a discussion on knowledge worker productivity, including presentations on relevant books and topics like estimation frameworks. - Materials and figures for estimating knowledge worker productivity over time based on metrics like computing power and GDP per employee in the US. - Additional slides on AI progress milestones, types of AI models, and an overview of Jim Spohrer's areas of study and priorities around service science, artificial intelligence, and trust.
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Worker Productivity 20230628 v1.pptx
- 1. Post-Industrial Forum atSRI Knowledge Worker Productivity Jim Spohrer Retired Industry Executive (Apple, IBM) UIDP Senior Fellow Board of Directors (ISSIP, ServCollab) Questions: spohrer@gmail.com Twitter: @JimSpohrer LinkedIn: https://www.linkedin.com/in/spohrer/ Slack: https://slack.lfai.foundation Presentations online at: https://slideshare.net/spohrer Thanks to Frode Odegard for the invitation to discuss Knowledge Worker Productivity Wednesday June 28, 2023, 5:00-8:00pm PT Humankind: A Hopeful History By Dutch Historian, Rutger Bregman <- Thanks To Ray Fisk For suggesting this book, see My summary here. See also ServCollab. Nonzero: The Logic of Human Destiny By USA Journalist, Robert Wright
- 2. Estimating Knowledge WorkerProductivity • Estimation Framework (Time and Money) • Draw seven vertical lines, label them with year from 1960 to 2080 • Draw five horizontal lines, label them with dollars from $1 to $Trillion • Estimating Cost of Computation • Add horizontal lines – that is Moore’s Law – cost of computation as a function of time from Kiloscale (103) to Ronnascale (1027) • Estimating Human-Scale Comparison • Make Exascale (1018) thicker – estimated computing power of 1 person’s brain • Make Ronnascale (1027) thicker – estimated computing power of a billion brains • Estimating Knowledge Worker Productivity • Add GPD/Employee in USA – that is an estimate of knowledge worker productivity
- 3. 1960 1980 20002020 2040 2060 2080 Estimation Framework (Time)
- 4. 1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Estimation Framework (Money)
- 5. 1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Estimating Cost of Computation
- 6. 1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Estimating Human-scale Comparison Human-scale Brains Compute One Exa- (1018) Billion Ronna- (1027)
- 7. 1960 1980 20002020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 GDP/Employee Trend Estimating Knowledge Worker Productivity Based on USA Historical Data Year Value 1960 $10K 1980 $33K 2000 $78K 2020. $151K 2023 $169K
- 8. Estimating Knowledge WorkerProductivity
- 9. 9 September 2018 /© 2018 IBM Corporation Petaflops = 1,000,000,000,000,000 or a million billion = 10 ** 15 Megaflops = 1,000,000 = million = 10 ** 6 Gigaflops = 1,000,000,000 = billion = 10 ** 9 One of the AI Super Computers in the World, = 13 MegaWatts of Power (HOT!)
- 10. 10 September 2018 /© 2018 IBM Corporation Exascale = 1,000,000,000,000,000,000 or a billion billion = 10 ** 18 Megaflops = 1,000,000 = million = 10 ** 6 Gigaflops = 1,000,000,000 = billion = 10 ** 9 Human Brain = 20 Watts (COOL!)
- 11. 6/29/2023 Jim Spohrer(ISSIP.org) 11 (Chorus) AI, AI, enhancing the way, Personalization brightens each day. With tailored recommendations, it's clear, SIR members' interests, AI holds dear. Oh, SIR, SIR, hear this tune so true ChatGPT Prompt: Please transform the essay “AI for SIR members” into a song to the tune of "Daisy, Daisy give me your answer do” DALL-E Prompt: Generate a painting of the essence of technology and camaraderie with a vibrant and engaging image of retired men singing together. Evoke a sense of excitement and showcase the power of AI in enhancing the lives of SIR members.
- 12. Let’s level set– how many of you know about… Ethan Mollick (UPenn Wharton) Don Norman (UC San Diego) Scott Pelley (CBS, 60 Minutes) Tristan Harris and Aza Raskin (Center for Humane Technology) Generative AI Tools To Output: Text/Writing Images Code/Programming Videos Audio Music Game Worlds Digital Twin Other? 6/29/2023 Jim Spohrer (ISSIP.org) 12
- 13. Today’s talk • Intro:AI (by 1955 definition) has arrived • Just took 68 years, but… • What’s really going on? • Your data is becoming your AI… IA transformation • AI Digital Twin = IA (Intelligence Augmentation) • Adjustment period underway… • Part 1: Solving AI: Leaderboards/Profession Exams • Roadmap and implications • Open technologies, innovation • Part 2: Solving IA: Better Building Blocks • Solving problems faster, creates new problems • Identity, social contracts, trust, resilience • Part 3: ”Solving All Problems” • What could go wrong? Be prepared. • 37-year long adjustment period is now underway… 6/29/2023 Jim Spohrer 13
- 14. Icons of AIProgress • 1955-1956: Dartmouth Workshop organized by: • Two early career faculty • John McCarthy (Dartmouth, later Stanford) • Marvin Minsky (MIT) • Two senior industry scientists • Claude Shannon (Bell Labs) • Nathan Rochester (IBM) • 1997: Deep Blue (IBM) - Chess • 2011: Watson Jeopardy! (IBM) • 2016: AlphaGo (Google DeepMinds) • 2017: All you need is attention (Google) - Transformers • Attention heads (working memory) to predict what comes next • 2018: AlphaFold (Google DeepMinds) • 2020: Language models are few-shot learners (OpenAI) • 2022: DALL-E 2 & ChapGPT (OpenAI) • 2022: Constitutional AI (Anthropic) – “Behave yourself!” • 2023: New Bing+ (Microsoft) & GPT-4 (OpenAI) 6/29/2023 Jim Spohrer 14
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- 16. Narrow AI Emerging Broad AI Disruptiveand Pervasive General AI Revolutionary ▼ We are here (2023) 2050 and beyond 16 IBM Research AI © 2018 IBM Corporation The evolution of AI Borrowed from David Cox, IBM-MIT Lead ▼ We were here (2018) ▼ Alan D Thompson AGI prediction (2025)
- 17. Predict the Timeline:GDP/Employee National Academy - Service Systems and AI 17 (Source) Lower compute costs translate into increasing productivity and GDP/employees for nations Increasing productivity and GDP/employees should translate into wealthier citizens AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA Alistair Nolan (OECD AI for Science Productivity): “It has been stated that the number of engineers proclaiming the end of Moore's Law doubles every two years.” Rouse WB, Spohrer JC. (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. 2018 Apr 3;8(1-2):1-21. Read Rouse & Spohrer (2018) enough to understand this slide including what ”exascale” means 11/22/22 Part 1: Solving AI
- 18. Types: Progression ofModels : Verified, Trusted, Wise Models = instruction_set of future: Better building blocks 6/29/2023 Understanding Cognitive Systems 18 Task & World Model/ Planning & Decisions Self Model/ Capacity & Limits User Model/ Episodic Memory Institutions Model/ Trust & Social Acts Tool + - - - Assistant ++ + - - Collaborator +++ ++ + - Coach ++++ +++ ++ + Mediator +++++ ++++ +++ ++ Cognitive Tool Cognitive Assistant Cognitive Collaborator Cognitive Coach Cognitive Mediator Part 2: Solving IA Solving IA also requires All of this and done well As a “bicycle for the mind” To make us stronger, Not weaker When tech is all removed
- 19. Resilience: Rapidly Rebuilding FromScratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. 6/29/2023 Jim Spoihrer (ISSIP) 19 Part 3: “Solving All Problems”
- 20. Jim Spohrer isa Silicon Valley-based Advisor to industry, academia, governments, startups and non-profits on topics of AI upskilling, innovation strategy, and win- win service in the AI era. Most recently with a consulting team working for a top 10 market cap global company, he contributed to a strategic plan for a globally connected AI Academy for achieving rapid, nation-scale upskilling with AI. With the US National Academy of Engineering, he co-led a 2022 workshop on “Service Systems Engineering in the Era of Human-Centered AI” to improve well-being. Jim is a retired IBM Executive since July 2021, and previously directed IBM’s open- source Artificial Intelligence developer ecosystem effort, was CTO IBM Venture Capital Group, co-founded IBM Almaden Service Research, and led IBM Global University Programs. In the 1990’s at Apple Computer, as a Distinguished Engineer Scientist and Technologist, he was executive lead on next generation learning platforms. In the 1970’s, after his MIT BS in Physics, he developed speech recognition systems at Verbex (Exxon) before receiving his Yale PhD in Computer Science/AI. In 1989, prior to joining Apple, he was a visiting scholar at the University of Rome, La Sapienza advising doctoral students working on AI and Education dissertations. With over ninety publications and nine patents, he received the Christopher Lovelock Career Contributions to the Service Discipline award, Gummesson Service Research award, Vargo and Lusch Service-Dominant Logic award, Daniel Berg Service Systems award, and a PICMET Fellow for advancing service science. Jim was elected and previously served as Linux Foundation AI & Data Technical Advisory Board Chairperson and ONNX Steering Committee Member (2020-2021). Today, he is a UIDP Senior Fellow for contributions to industry-university collaborations, and a member of the Board of Directors of the International Society of Service Innovation (ISSIP) and ServCollab. Jim Spohrer, Advisor Retired Industry Executive (Apple, IBM) UIDP Senior Fellow Board of Directors, ServCollab Board of Directors, ISSIP.org Changemaker Priorities 1. Service Innovation 2. Upskilling with AI 3. Future Universities 4. Geothermal Energy 5. Poverty Reduction 6. Regional Development Competitive Parity Technologies 1. AI & Robotics 2. Digital Twins 3. Open Source 4. AR/VR/XR 5. Geothermal 6. Learning Platforms
- 21. Who I am:Take 2 The Three Ages of Man (Giorgione) Thanks to Alan Hartman for kind inspiration (slides) (recording) Service is an actor applying resources (e.g., knowledge) to benefit another Service system entities are responsible actors that give and get service (e.g., people, businesses, universities, nations, etc.) Service science studies service systems as an evolving ecology of responsible actors that interact and change. Service innovations improve win-win interaction and change in business and society Service systems are dynamic configurations of four types of resources 6/29/2023 Jim Spohrer (ISSIP.org) 21 Environmental and ecological sciences ServCollab
- 22. What I study ServiceScience and Open Source AI – Trust is key to both Service Science Artificial Intelligence Trust: Value Co-Creation/Collaboration Responsible Entities Learning to Invest Transdisciplinary Community Trust: Secure, Fair, Explainable Machine Collaborators Open Source Communities