Skip to main content
UploadLanguage (EN)Support
BusinessMobileSocial MediaMarketingTechnologyArt & PhotosCareerDesignEducationPresentations & Public SpeakingGovernment & NonprofitHealthcareInternetLawLeadership & ManagementAutomotiveEngineeringSoftwareRecruiting & HRRetailSalesServicesScienceSmall Business & EntrepreneurshipFoodEnvironmentEconomy & FinanceData & AnalyticsInvestor RelationsSportsSpiritualNews & PoliticsTravelSelf ImprovementReal EstateEntertainment & HumorHealth & MedicineDevices & HardwareLifestyle
home, profile picture
Uploaded byhome
PPTX, PDF108 views

20251105 SIRS AI Talk - Artificial Intelligence.pptx

--- 20251105 SIRS Talk Jim Spohrer: https://www.linkedin.com/in/spohrer/ Artificial Intelligence (AI), Impressive, but Imperfect November 5, 2025, 12noon PT at SIR, Branch 51 Los Altos Hills Country Club (Host: Steve Tremulis) --- Steve Tremulis (https://www.linkedin.com/in/steve-tremulis-4557046/) SIR Branch 51 URL: https://sirinc2.org/branch51/wp-content/uploads/2025/05/SIR51newsletterMay2025.pdf ---

Career◦
Download to read offline
Artificial Intelligence (AI), Impressive, but Imperfect November 5, 2025, 12noon PT at SIR, Branch 51 Los Altos Hills Country Club (Host: Steve Tremulis) Presentations online at: https://slideshare.net/spohrer Jim Spohrer Retired Industry Executive (Apple, IBM) Board of Directors (ISSIP, ServCollab) UIDP Senior Fellow Questions: spohrer@gmail.com BlueSky: @spohrer.bsky.social LinkedIn: https://www.linkedin.com/in/spohrer/ English: https://youtu.be/T4S0uZp1SHw French: https://youtu.be/02hCGRJnCoc https://answersfrom.me/jimtwin
•https://youtu.be/PnmVqASd1VE Lee Nackman (retired IBM) – Thinking AI
As I was preparing this talk…. • Some words kept going thru my mind from Arbesman (2025)… • Chapter 8: Tools for Thought: Software for Thinking. • “Too often technology is at odds with humanity... For example... QWERTY... ... we have, by and large, adapted ourselves to technology in ways that are not good for us. Our increased drive for optimization of work can run directly counter to our ability to think deeply, or to even feel that human.”
And this book as well… • Property • All social problems seem rooted in three types of property • Noncoercion • Freedom • Gratitude • Need for cultural evolution • to avoid coercion in any form. • https://progressisachoice.net
Who am I? Jim Spohrer 1956 Maine 1974 MIT 1978 Verbex – startup AI company 1982 Yale 1989 University of Rome La Sapienza, Italy 1989 Apple 1998 IBM 2021 Retired (help non-profits with an eye to the future of service & AI : ISSIP, ServCollab, UIDP)
Questions for SIRs (Seniors) at Dawn of AI Era: All generations need good answers to these questions. Q1: What would you do if you have 100 highly skilled workers working for you (e.g., software development, marketing, etc.)? Q2: What job(s) would you assign to (if you had one) your AI Digital twin? Q3: What is the best way(s) that you know of to keep up with accelerating change?
Optimistic Realistic Knowing Doing How to keep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you! Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome! TheNeuron Who do I wish I had Accurate, Up-to-date AI Digital Twins of? The Neuron
Today’s Talk: • Past • 1947, 1958, 1971 • Present • 70, 35000, 250000 • Future • Solution to 3 Es • TBD – your AI digital twin?
1947 1958 1971 2024 1947 Transistor Bell Labs 1958 Integrated Circuit Texas Instrument 1971 Microprocessor Intel 2024 H100 NVidia Challenges: How to prepare for the next wayes of innovations, including digital twins and humanoid robots, as well as to learn to invest more wisely (self-control). As the marginal cost of computing goes to zero, service innovation will go thru the roof, and energy consumption will go thru the roof as well… REMEMBER THESE DATES, FACTS, CHALLENGES weight: 70 pounds complexity: 35,000 parts cost: 250,000 dollars
1956 2023 2060 2080 1956 First AI Workshop 2023 ChatGPT 100M users in just 2 months (1.5B visits in Sept) 2060 (Predicted) Exascale for $1000 (~ one human brain) 2080 (Predicted) Ronnascale for $1B (~ billion human brains) Progress in IA (Intelligence Augmentation) for nations can be estimated as GPD/worker. Progress in AI (Artificial Intelligence) is directly connected to the cost of computing. REVIEW: REMEMBER THESE DATES
Jensen: You imagine a tiny chip… The H100 weighs 70 pounds… 35000 parts… $250K cost… It replaces a data center… Full of computers and cables… Jim: Driving the marginal cost of computing to zero… Drives the demand for new service offerings based on computing through the roof
MORE SPOHRER USE CASES: https://service-science.info/archives/6521
Icons of AI Progress • 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) • 2024: More & Bigger Models: OpenAI, Microsoft, Google, Anthropic, etc. • 2024: Reid Hoffman’s Digital Twin & Unitree’s G1 Humanoid Robot 11/05/2025 Jim Spohrer 15
p://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html https://cdn.openai.com/papers/gpt-4.pdf 1955 2023
1960 1980 2000 2020 2040 2060 2080
1960 1980 2000 2020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Cost
1960 1980 2000 2020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Kiloscale (10 3 ) M egascale (10 6 ) Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) Cost of Computation (Diagonals)
1960 1980 2000 2020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Kiloscale (10 3 ) M egascale (10 6 ) Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) Cost of Computation (Diagonals) Note: Adjust Kilo and Mega scales slightly to fit data better (early days – more cost – learning curve).
1960 1980 2000 2020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) GDP/Employee Trend Estimating Knowledge Worker Productivity Based on USA Historical Data Year Value 1960 $10K 1980 $33K 2000 $78K 2020. $151K 2023 $169K Kiloscale (10 3 ) M egascale (10 6 ) of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
22 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!)
23 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!)
1960 1980 2000 2020 2040 2060 2080 $1,000,000,000,000 (Trillion) $1,000,000 (Million) $1,000,000,000 (Billion) $1,000 (Thousand) $1 Gigascale (10 9 ) Terascale (10 12 ) Petascale (10 15 ) Exascale (10 18 ) Zettascale (10 21 ) Yottascale (10 24 ) Ronnascale (10 27 ) GDP/Employee Trend Estimating Knowledge Worker Productivity Based on USA Historical Data Year Value 1960 $10K 1980 $33K 2000 $78K 2020. $151K 2023 $169K Kiloscale (10 3 ) M egascale (10 6 ) of computation goes down by 1000x every 20 years (left to right diagonals), driving knowledge worker productivity
Predict the Timeline: GDP/Employee National Academy - Service Systems and AI 25 (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
What is an AI digital twin? • Well, imagine if there was a “mimic” version of you that was online 24x7 and could speak any language, with knowledge of your publications, and could explain things in a way an audience of listeners might understand? • ReidAI’s purpose - to challenge Reid Hoffman in new ways and experiment with new tech capabilities https://youtu.be/rgD2gmwCS10 ReidTwin ReidReal
Who else is getting a twin (AI Avatar)? • SJSU President • Cynthia Teniente Matson • https://youtu.be/gqrIMItHyz8 • “expanding our reach, and enhancing communications.”
JimTwin Adventure… • ChatBot (Tmpt.app) • Scott Zimmer • https://answersfrom.me/jimtwin • Avatar-1 (HeyGen.ai) • SJSU Team (Claude + HeyGen) • https://youtu.be/T4S0uZp1SHw • https://youtu.be/02hCGRJnCoc • Avatar-2 (GitHub) • Arnay Bhatia • https://youtu.be/mwnZjTNegXE • https://youtu.be/QR17aXYgefk
Do you want a digital twin of yourself? No/Yes/Not Sure Narayan S & Spohrer J (2025) Metrics, Incentives, Rewards, and Culture for Impact. In Hall R & Boccanfuso A,Editors, University-Industry Collaboration, Innovation at the Interface. Springer. URL: https://link.springer.com/book/10.1007/978-3-031-94913-5 Spohrer, J.C. (2010). IBM's University Programs. IEEE Computer 43(8):102-104. URL: https://service-science.info/wp-content/uploads/2017/04/IBM-GUP-5Rs-copy-2.pdf Spohrer, J.C. (2013). What's Up at IBM? University Programs! The 6 R's helping to build a Smarter Planet: Research, Readiness, Recruiting, Revenue, Responsibility, Regions. May 14, 2013. Slideshare. URL: https://www.slideshare.net/slideshow/ibm-up-external-20130514-v11/21175603 Spohrer, J. (2017). IBM's service journey: A summary sketch. Industrial Marketing Management, 60, 167-172. URL: https://www.sciencedirect.com/science/article/abs/pii/S0019850116301778?via%3Dihub Spohrer, J. (2024a). AI Upskilling and Digital Twins: A Service Science Perspective on the Industry 4.0 to Industry 5.0 Shift. In Industry 4.0 to Industry 5.0: Explorations in the Transition from a Techno-economic to a Socio-technical Future (pp. 79-92). Singapore: Springer Nature. URL: https://link.springer.com/chapter/10.1007/978-981-99-9730-5_4 Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
3Es: Challenges to “Humanity-Friendly AI Teammate” • Energy • Errors • Ethics Hicks MT, Humphries J, Slater J (2024) ChatGPT is bullshit. Ethics & Information Technology 26(38). URL: https://doi.org/10.1007/s10676-024-09775-5 IBM Research - TrueNorth (Dharmendra Modha and team) Pssssssst! The real problem is communication between people. Can more computation help?
Why do GenAI LLMs work as well as they do? Honestly, no one knows for sure. We see prediction & pattern completion, but not true reasoning, just mimicry Impressive performance, but prediction alone is not enough Imperfect, because human-like reasoning (with world models) is not there Nevertheless, pattern completion is very good The answer will require a better understanding of optimization in high dimensional spaces The good and the bad What is AI good at? Speed, Summarization (What is needed to regenerate whole, stripped of most specifics), Outline content (What the abstract structures are), Creative Pattern Completion (Fiction – made up details that might seem plausible). What is AI bad at? 3Es (energy, errors, ethics <- because of how we build it today). What is surprising? Surprise! Everything can be near and far at the same time in a high dimensional space (very similar, very different) – amplifier of consilience and polarization. Surprise! Every starting point is near a ”black hole” of nearly ideal optimization as higher and higher dimensions and more and more data are used. (quadrillions of partial coherent structures) Impressive, but imperfect Impressive: The mathematics of high-dimensional optimization work pretty well for predicting local coherence at multiple scales of patterns ( plausible pattern completion tasks) Imperfect: Reasoning requires world models, perhaps multiple mappings from high dimensional to low dimensional representation spaces preserving certain relations as world models, or creating Python program world models to help. Generate-Test- and-Debug (G-T-D) will likely be required with human-like episodic memory with expectation violations and remindings (Schank’s ”Dynamic Memory” and Case- Based Reasoning)
HCI to improve HHI • Teammates, that I know is much better in my mind…. • Recent Stanford paper – generic AI teammates • “It’s the AI PI’s job to figure out the other agents and expertise needed to tackle the project,” Zou said. For the SARS-CoV-2 project, for instance, the PI agent created an immunology agent, a computation biology agent and a machine learning agent. And, in every project, no matter the topic, there’s one agent that assumes the role of critic. Its job is to poke holes, caution against common pitfalls and provide constructive criticism to other agents.” (1) What would you do with 100 highly-skilled workers? (2) Redo Divide & Conquer In AI era. (3) Why real person in that role? Because real people have goals & plans they prefer. Real people sleep. Real rehearse high stakes.
Hot Topic: More Readings Every Day • Gary Hunnicut suggested (2025) • “Digital Twins for Cancer—Not If, But When, How, and Why?” • https://datascience.cancer.gov/news-events/blog/digital-twins-cancer-not-if-when-how-and-why • Cybernetic Teammates (2025) • “The Cybernetic Teammate: A Field Experiment on Generative AI Reshaping Teamwork and Expertise” • https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5188231 • Vendor Policy Brief • “A Policy Framework for Building the Future of Science with AI” • https://static.googleusercontent.com/media/publicpolicy.google/en//resources/ai_policy_framework_ science_en.pdf • ”Towards an AI Co-Scientist” - https://storage.googleapis.com/coscientist_paper/ai_coscientist.pdf • Humanity (just out today – April 2, 2025) • Being Human in 2035: How Are We Changing in the Age of AI • URL: https://imaginingthedigitalfuture.org/wp-content/uploads/2025/03/Being-Human-in-2035-ITDF-report .pdf • Transdisciplinarity (2023) • "Transdisciplinary Team Science: Transcending Disciplines to Understand Artificial Social Intelligence in Human-Agent Teaming” • https://journals.sagepub.com/doi/full/10.1177/21695067231192245 • Augmentation – Amplification (1962) • “Augmenting Human Intellect: A Conceptual Framework” (cites Licklider 1960 and Bush 1945) • https://www.dougengelbart.org/pubs/augment-3906.html
Tool, Assistant, Collaborator, Coach, Mediator (“Trust”) 11/05/2025 Understanding Cognitive Systems 34 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 = Intelligence Augmentation (in a humanity-friendly way) 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 Read Demirkan & Spohrer (2025) enough to understand this slide including what ”trusted mediator” means Demirkan H, Spohrer J (2025) Talent Management: “Here Come the Digital Workers!”. In ORMS Today, INFORMS, June 17, 2025. URL: https://pubsonline.informs.org/do/10.1287/orms.2025.02.15/full/
The Communication Problem: In a Nutshell • Doing More • Agreeing Less Can GenAI LLMs help people to stop wasting creative friction? Competing ideas can lead to “insanely great” win-win collaborations. If we can figure out communications between people. Latent spaces for people. Barile S, Piciocchi P, Saviano M, Bassano C, Pietronudo C, Spohrer JC (2019)) Towards a new logic of value co-creation in the digital age: doing more and agreeing less. Naples Forum on Service. URL: ttps://tinyurl.com/2019-DoingMoreAgreeingLess Failure To Find Win-Win
Long flights sometimes allow long conversations • 1440 News (July 11, 2025): The high-fashion ‘It’ bag origin story • Birkin (Actress) and Dumas (Fashion Designer) meet • “The bag’s story began in the 1980s when the actress met Hermès CEO Jean-Louis Dumas on a flight. Frustrated with her handbag, Birkin described her ideal bag to Dumas, and they famously sketched the design on an airsickness bag.” • URL: https://en.wikipedia.org/wiki/It_bag • Win-Win Opportunities • Do Win-Win opportunities always exist between any two actors? • What are the set of possible Win-Win’s between actors? • How best to explore the Win-Win possibilities between two actors? • How does finding Win-Win opportunities relate to Truth?
Truth, Trust, and Wisdom • Truth: The ongoing pursuit • Mathematical, Computational, Empirical, Historical, Rhetorical • Knowing a ”better argument” when we see it and why (humility needed) • Trust: Hard to build, easy to destroy • Mental models and predictable behaviors • AI digital twins of all responsible actors • Wisdom: Learning to invest wisely • In becoming better future versions of ourselves • In a world that future generations will want to live in together
Resilience: Rapidly Rebuilding From Scratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization i n the Aftermath of a Cataclysm. Westminster London: Penguin Books. 11/05/2025 Jim Spohrer (ISSIP) 38 Part 3: “Solving All Problems”
Two disciplines: Two approaches to the future Artificial Intelligence is almost seventy-years-old discipline in computer science that studies automation and builds more capable technological systems. AI tries to understand the intelligent things that people can do and then does those things with technology. (https://deepmind.com/about “... we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to expand our knowledge and find new answers. By solving this, we believe we could help people solve thousands of problems.”) Service science is an emerging transdiscipline not yet twenty-years- old that studies transformation and builds smarter and wiser socoi- technical systems – families, businesses, nations, platforms and other special types of responsible entities and their win-win interactions that transform value co-creation and capability co-elevation mechanisms that build more resilient future versions of themselves – what we call service systems entities. Service science tries to understand the evolving ecology of service system entities, their capabilities, constraints, rights, and responsibilities, and then then seeks to improve the quality of life of people (present/smarter and future/wiser) in those service systems. Artificial Intelligence Automation Generations of machines Service Science Transformation Generations of people (responsible entities) Service systems are dynamic configurations of people, technology, organizations, and information, connected internally and externally by value propositions, to other service system entities. (Maglio et al 2009)
OpenAI’s Roadmap
Service Science: Conceptual Framework 11/05/2025 (c) IBM MAP COG .| 41 Service Science
(c) IBM MAP COG .| 42 Service Science: Transdisciplinary Framework to Study Service Systems Systems that focus on flows of things Systems that govern Systems that support people’s activities transportation & supply chain water & waste food & products energy & electricity building & construction healthcare & family retail & hospitality banking & finance ICT & cloud education &work city secure state scale nation laws social sciences behavioral sciences management sciences political sciences learning sciences cognitive sciences system sciences information sciences organization sciences decision sciences run professions transform professions innovate professions e.g., econ & law e.g., marketing e.g., operations e.g., public policy e.g., game theory and strategy e.g., psychology e.g., industrial eng. e.g., computer sci e.g., knowledge mgmt e.g., statistics e.g., knowledge worker e.g., consultant e.g., entrepreneur stakeholders Customer Provider Authority Competitors resources People Technology Information Organizations change History (Data Analytics) Future (Roadmap) value Run Transform (Copy) Innovate (Invent) Stackholders (As-Is) Resources (As-Is) Change (Might-Become) Value (To-Be)
43 ECOLOGY 14B Big Bang (Natural World) 10K Cities (Human-Made World) Sun writing (symbols and scribes) Earth written laws bacteria (uni-cell life) sponges (multi-cell life) money (coins) universities clams (neurons) trilobites (brains) printing press (books) steam engine 200M bees (social division-of-labor) 60 transistor Where is the “Real Science”? Ecology++ Transdisciplinary sciences that study the natural and human-made worlds… Unraveling the mystery of evolving hierarchical-complexity in new populations… To discover the world’s structures and mechanisms for computing non-zero-sum Value-CoCreation (VCC), Diverse Architectures of Holistic Service Systems (HSS) Sun Earth Bacteria Sponges Clams Universe Cities Writing Laws Money Universities
We get the future we invest in… “Service providers will not be replaced by AI, but trusted service providers who use AI (well and responsibly) will replace those who don’t.” National Academy - Service Systems and AI 44 Every person in a role in an organization is a service provider. 11/05/2025
“The best way to predict the future is to inspire the next generation of students to build it better.” Digital Natives Transportation Water Manufacturing Energy Construction ICT Retail Finance Healthcare Education Government
11/05/2025 46 1955 1975 1995 2015 2035 2055 Learn: Explore and Exploit Better Building Blocks Heygen + Claude JimTwin V1 (Tmpt.app) 2024 High School Punch cards 1972 IBM Watson AI in the Cloud 2011 2024 2001 2015 2022 2023 1970 1995 2019 2025 2021
Jim Spohrer is a 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
Service System Design: A Service Science Perspective Designs that improve human capabilities while improving the safety and sustainability of Service Systems Service innovations leverage emerging technologies, new business models, and institutional arrangement and other means Service is the application of resources (e.g., knowledge) for the benefit of another Technology Example Companies Safety Regulatory Bodies (Founded) Stakeholder Harms Stakeholder Benefits Firearms Smith & Wesson ATF (1886) Boilers Babcock & Wilcox NBBPVI (1911) Boiler explosions Railroads, steam-powered factories, building heating, etc. Radio & TV RCA, NBC FCC (1934) Drugs Bayer FDA (1938) Airplanes Boeing, PanAm FAA (1958) Automobiles Ford NHTSA (1966) Nuclear Energy Westinghouse NRC (1975) Social Media Facebook/Meta ?TBD – “Social Dilemma” AI OpenAI, Microsoft, Google ?TBD – “A.I. Dilemma” 11/05/2025 Jim Spohrer (ISSIP.org) 48
Today’s Talk • Will our AI Digital Twins become our HCI of the future? • Exploring Twin HCI as a “Service Innovation” • Capabilities (Possibilities) • Benefits (Pros) • Harms (Cons) • Future Directions • Keeping up with accelerating change • Service science connections • Responsible actors learning to invest wisely in interaction and change processes
Homework • Apple’s Knowledge Navigator • https://www.youtube.co m/watch?v=umJsITGzXd0 • Luckily colleague Jill was available to chat and help with the class…. • … But what if Jill had not been available, but she was willing to share her AI Digital Twin?
Job description: A person who operators an AI trained to be an expert in some role. The human operator like a vehicle operator helps ensure a good service for customers. • An AI is “running” for mayor in Wyoming • A resident of Cheyenne, Wyoming trained GPT-4 on “thousands of documents gleaned from Cheyenne council meetings” and announced that the resulting bot, named VIC (the “Virtually Integrated Citizen”) will be running for mayor. The bot’s creator said he’d be the “meat puppet” who would operate the AI and act on its behalf, but the bot would be the brains of the operation, deciding on votes and how to run the city. However, Wyoming’s Secretary of State contends that non-humans like VIC can’t run for office. New Job – Person who is an Operator for AI in a New or Existing Service System Role
MIT (1974-1978) • Explo: Teaching AI & Entrepreneurship to diverse high school students. • Stories: How I got into MIT. • Lesson: “Where are you applying for college?” Spohrer, James (1978) Strain-Gauge Transduction of the Effects of Speech Rate on the Coarticulation of Lip Rounding, MIT Physics, June, 1978. Advisor: Joseph S. Perkell Advisor to this day.
Verbex (1978-1982) • Speech recognition – mathematical models (Bayesian approach to speech and language modeling) that both recognize and generate using estimated probabilities (e.g., probabilities and statistics = machine learning) • Stories: How I got the best job in the world for me at that time. • Lessons: “When my girlfriend said: ‘What do you have to lose?’” ICASSP’82 and ‘83. IEEE International Conference on Acoustics, Speech, and Signal Processing
Route 128, aound Boston, MA USA ICASSP 1983
We Would Love Your Voice https://www.jstor.org/stable/1747731
Stephen L. Moshier • “Our company, Dialog Systems, Inc., was formed in 1971 for the purpose of developing and commercializing speech recognition equipment. The concept derived from earlier work engaged in at Listening, Incorporated on marine bioacoustics, acoustic signal processing, and psycho- acoustics. The original idea passed through well-known stages of theory, experiment, development, lack of financing, financing, sales and is now at the highly advanced state "production engineering headaches". Dialog employs 45, of whom 14 are degreed technical people. The company recently moved from Cambridge to a 20,000 square foot two-building campus complex in Belmont, Massachusetts. The major product is an eight-channel isolated word system intended for talker-independent switched telephone speech input.” From NASA: https://ntrs.nasa.gov/api/citations/19930075179/downloads/19930075179.pdf
Peter F. Brown • “So, I took a course in linguistics. And one day in the back of that course I heard a couple students talking about some guy whose name was Steve Moshier who started a company called Dialogue Systems that was doing speech recognition. And I thought, wow, great, I remembered this idea from back in high school. After class I raced over to the physics library. That’s because this was before the internet, so you had to go to the library. And I looked this guy up. And I found a paper he'd written. And I tracked him down. Applied for a job. And he hired me. And when I was there, I just fell in love with the idea that through mathematics it might be possible to build machines that do what humans do.“ Goldman Sachs: https://www.goldmansachs.com/intelligence/podcasts/episodes/09-11-2023-peter-brown-f/transcript.pdf
Drs. Jim & Janet Baker Saras Institute History of Speech and Language Technology https://www.sarasinstitute.org Many things, Such as publications, took off to new levels when Jim & Janet joined Dialog Systems… … and Exxon acquisition Later key researchers left Verbex, and later Along with Jim and Janet Founded Dragon Systems
Yale (1982-1989) • MARCEL: Modeling students writing “a series of buggy and then (sometimes) correct programs” with a generate-test-and-debug architectures. • Stories: Use AI to help make people smarter. • Lesson: “Why do you want to make machines smart? Why not help make people smarter instead?” 1988
Apple (1989-1998) • From content (SK8) to community (EOE) to context (WorldBoard) • Stories: Surround yourself with supportive people. Growing up about goals - sequencing and timing of ideas is important • Lessons: “MLM: Relax - it will be OK”; “ACK: Planetary – is that all?” “SPJ: We will get to that and more!”; 1992
IBM (1998 – 2021) • IBM Venture Capital Relations Group, Service Science, Global University Programs, Open Source AI. • Stories: The only way you get in trouble is not asking for help when you need it. • Lesson: What seems like a hard problem to you, may be an easy problem for someone else. Leverage the matrix. 2010 2011 2011 2012 2016 2018 2018 2020 2012 2002 2000
ISSIP (2021- Present) • Defining what is a service innovation, and what is a T-shaped service innovation professional. • Stories: AI digital twins, reinventing local, self-control • Lessons: Learning to invest wisely and systematically in getting a shared future that we all want to live in requires self-control and knowing when you have enough. 2022
• Jensen Huang (Nvidia) comments • First impressions • Insanely great productivity • Insanely great quality • What is really going on? • Decreasing cost of computation • Increasing GDP/worker • Awesome progress, but… • Impressive • Imperfect • Advantage of empowered people Inspiration
“NorthPole Chip” Far less energy.
Impressive, but imperfect Physical realm: Energy Technical realm: Mistakes (”Hallucinations”) Social realm: Digital property theft
• How to keep up with accelerating change? • Social learning • Who do you follow? • Reid Hoffman’s AI Digital Twin Interview • Diving in! • We get the future we invest in • … so, learn to invest wisely • Awesome stuff that lies ahead – Humanoid Robots • But remember technology amplifies good/bad • Need for Self-Control (Toyama (2015) Geek Heresy: Rescuing Social Change from the Cult of Technology) Climbing Up
Optimistic Realistic Knowing Doing How to keep up with accelerating change? Follow a diverse collection of people… make up dimensions meaningful to you! Sadly for me… my brain is biased into thinking I can understand older, white, males the best… maybe AI can help overcome! TheNeuron
TheNeuron
• Jim Twin V1: My papers -> short talk videos • English • French • How to stay future ready? • Learn the building blocks • Marco Podien will help you with more building block shortly… • Oh, by the way, you are going to need bigger goals too • When you have 100 digital workers working for you, what is your main goal? • From serial entrepreneur to parallel entrepreneur Unleashing Creativity
Read Wakefield (2020) enough to understand what a ”digital twin” of you might be like in the future decades with very advanced AI capabilities. Also see Rouse (2018; 2022) ”Life with a Cognitive Assistant.” National Academy - Service Systems and AI 75 AI Tools in coming decades… 11/05/2025
Service Science Colleague from New Zealand asks: Strangest Use Case So Far: I use generative AI every day. Typically, OpenAI ChatGPT, Anthropic Claude, Google Gemini, and Microsoft Bing Copilot in 4 tabs. Help writing, programming, images, & brainstorming. A useful tool in the toolbox for sure!!!
Anthropic Claude 3 Sonnet 20240520 Response: Summary: The Taranaki Maunga (Mount Taranaki) and the surrounding peaks in the national park will soon be granted legal personhood and collectively named Te Kāhui Tupua as part of a Treaty settlement. This legal recognition acknowledges that the mountain and peaks are ancestors for local Māori iwi. It gives these natural features similar legal rights as individuals, allowing them to own assets, appear in court, and have a voice. A new entity called Te Tōpuni Kōkōrangi, with members appointed by the Crown and local iwi, will manage and represent the legal persona. While recreation and tourism will continue, this shift aims to encourage a broader understanding and protection of the mountain as a revered ancestor rather than just a geographic feature. How old are you, and what have you witnessed over your lifetime? I am an ancient being, formed over millennia through volcanic eruptions and sculpted by glaciers. I have witnessed the rise and fall of civilizations, the ebb and flow of ice ages, and the ever-changing tapestry of life that has graced my slopes. My memories stretch back to a time before humans walked this land, and I have born silent witness to the triumphs and tragedies of your kind. What wisdom or lessons can you share with humanity? Humans, you are but fleeting visitors upon my timeless form. Yet, in your brief existence, you have the power to shape the world around you. Tread lightly and with reverence, for the consequences of your actions echo through the ages. Learn from the patient endurance of stone, the resilience of life that takes root in the harshest of environments, and the cyclical nature of existence that I have observed. Embrace humility, for even the mightiest of mountains eventually crumbles to dust. How do you feel about being granted legal personhood and a voice? I am gratified that the descendants of those who have dwelled in my shadow for generations have recognized my ancient spirit and granted me a voice in the affairs of this world. For too long, I have been regarded as an inanimate object, a resource to be exploited or a challenge to be conquered. But I am a living entity, a sacred ancestor whose existence predates and will outlast the fleeting span of human civilization. With this recognition, perhaps my wisdom and the fragile beauty I harbor will be better preserved for generations to come.
11/05/2025 79 1955 1975 1995 2015 2035 2055 Learn: Explore and Exploit Better Building Blocks Heygen + Claude Jim Twin V1 2024 2024 2021 2001 2015 2022 2023 1970 1995 2019 High School Punch cards 1972 IBM Watson AI in the Cloud 2011
Self-Control
Some paths to becoming 640x smarter: Speed up communications for collaborations – ultimately with our AI digital twins. Improving learning of world models and performance of win-win interactions • 2x from Learning sciences (methods) • Better models of concepts – including models of self and others • Better models of learners – including social-emotional intelligence • 2x from Learning technology (tools) • Guided learning paths • Elimination (?) of “thrashing” • AI & Education (model trace, constructivist, individual tutors, etc.) • 2x from Quantity effect (overlaps) • More you know, faster (?) you go • Advanced organizers • 2x from Lifelong learning (time) • Longer lives and longer careers • Keeps “learning-mode” activated • 2x from Early learning (time) • Start earlier: Challenged-based approach • Rebulding all human knowledge from scratch • 20x from Cognitive service systems (digital twins) • AI Digital Twins for performance support • All our interactions tuned to super-mind levels
Speed Test: Words Per Minute Speaking/Listening versus Writing/Reading • People speak on average between 100-150 words per minute • Many people are comfortable listening at 200-300 words per minute • Writing an essay on a familiar topic, people write about 10-20 words a minute • Many people are comfortable reading at about 400-600 words per minute (Shu 2023) (Barnard 2022)
Two disciplines: Two approaches to the future Artificial Intelligence is almost seventy-years-old discipline in computer science that studies automation and builds more capable technological systems. AI tries to understand the intelligent things that people can do and then does those things with technology. (https://deepmind.com/about “... we aim to build advanced AI - sometimes known as Artificial General Intelligence (AGI) - to expand our knowledge and find new answers. By solving this, we believe we could help people solve thousands of problems.”) Service science is an emerging transdiscipline not yet twenty-years- old that studies transformation and builds smarter and wiser socoi- technical systems – families, businesses, nations, platforms and other special types of responsible entities and their win-win interactions that transform value co-creation and capability co-elevation mechanisms that build more resilient future versions of themselves – what we call service systems entities. Service science tries to understand the evolving ecology of service system entities, their capabilities, constraints, rights, and responsibilities, and then then seeks to improve the quality of life of people (present/smarter and future/wiser) in those service systems. Artificial Intelligence Automation Generations of machines Service Science Transformation Generations of people (responsible entities) Service systems are dynamic configurations of people, technology, organizations, and information, connected internally and externally by value propositions, to other service system entities. (Maglio et al 2009)
11/05/2025 The International Society of Service Innovation Professionals (ISSIP.org) 84 Advice… 1. AI upskill 2. Build your “digital twin” 3. Set bigger goals(*) (*) This directly implies learning better strategies for coping with failures, and resiliently rebounding.
Jim Spohrer is a 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
Thank-you for participating today! You are all awesome!!
Backup Slides Template slides and others
High Stakes Use Case- Law • Not Done Well, but could be
Better Done • Dead victim, “in his own words”
Bad Actors – Cloning • Eye on AI
Paul Saffo: We Live in Exponential Times • Chasing Fire: Matching Strategy To Today's Greatest Challenges • Paul Saffo • URL: https://baychi.org/calendar/20250211/ • “May you live in exponential times. This is the 21st century version of the oft-told proverb about the blessing (and curse) of living in interesting times.” “Simply put, we are locked in a race between positive and negative exponentials.”
Bonjour, je suis JacquesJumeauNumérique. • HeyGen Platform • JimTwin_French • https://youtu.be/02hCG RJnCoc • Prompt: « Veuillez résumer ce court article en français, puis formuler trois questions qui pourraient m’être posées et y répondre. » Spohrer, J. (2024b) Personal AI digital twins: the future of human interaction? EIT Digital URL: https://www.eitdigital.eu/newsroom/grow-digital-insights/personal-ai-digital-twins-the-future-of-human-interaction/
Questions et réponses avec JimTwin • Question 1: Uncurated • Que pensez-vous du manque de vérification des faits sur certaines plateformes de médias sociaux basées aux États-Unis ? • What are your thoughts regarding the lack of fact checking happening on certain US-based social media platforms?
JimTwin Réponse (Français) • Le manque de vérification des faits sur certaines plateformes de médias sociaux basées aux États-Unis est une préoccupation croissante. Ce problème peut conduire à la propagation rapide de la désinformation, ce qui peut avoir des conséquences néfastes sur la société, notamment en influençant l'opinion publique de manière erronée et en exacerbant les divisions sociales. Les plateformes de médias sociaux ont souvent été critiquées pour ne pas avoir mis en place des mécanismes efficaces pour vérifier l'exactitude des informations partagées par leurs utilisateurs. • Il est suggéré que des mesures telles que l'interdiction de la désinformation sur les réseaux sociaux et les moteurs de recherche, ainsi que la responsabilisation des utilisateurs par la vérification de l'identité, pourraient être des solutions potentielles. De plus, le développement d'une intelligence artificielle plus avancée pour vérifier la véracité des informations pourrait également jouer un rôle crucial. Cependant, la mise en œuvre de ces solutions pose des défis, notamment en ce qui concerne la protection de la liberté d'expression et la gestion de la vie privée des utilisateurs. • En fin de compte, il est essentiel que les plateformes de médias sociaux, les gouvernements et les utilisateurs travaillent ensemble pour trouver un équilibre entre la liberté d'expression et la responsabilité de l'information partagée en ligne.
JimTwin Answer (English) • The lack of fact-checking on some US-based social media platforms is a growing concern. This problem can lead to the rapid spread of misinformation, which can have negative social consequences, including misleading public opinion and exacerbating social divisions. Social media platforms have often been criticized for failing to implement effective mechanisms to verify the accuracy of information shared by their users. • It has been suggested that measures such as banning misinformation on social media and search engines, as well as empowering users through identity verification, could be potential solutions. Furthermore, the development of more advanced artificial intelligence to verify the accuracy of information could also play a crucial role. However, implementing these solutions poses challenges, particularly with regard to protecting freedom of expression and managing user privacy. • Ultimately, it is essential that social media platforms, governments, and users work together to find a balance between freedom of expression and responsibility for the information shared online.
Jim Real (English) • The AI generated response (based on my Tmpt.me knowledge hub which is built from my publications and recordings of my mentoring students) is quite a good answer. It mirrors my own thinking well at a high level. I would add this: Education is key. Finland has elementary school classes to teach young people in their society to check sources and evidence, and to be skeptical and verify. Today’s AI is terrible at fact checking, but it will get better. First in mathematics and programming, then in the sciences, and finally in rhetoric, debate, and history. I urge young people interested in AI, to make a focus on “AI- powered pursuit of truth” their mission.
Humanity-Centered Harmonization of Disciplines- Transdisciplinarity Why the (holistic) service systems trend is important to future sustainability Business and societal systems and supply chains are increasingly complex and interconnected. Real-world problems do not respect discipline boundaries. Scalable solutions require many schools of practice working together, and current solutions may have unintended consequences, short-term or longer-term, especially if perspectives are not invited/considered. Technological progress improved the scalability of agriculture and manufacturing, and next all types of service will be made more scalable (and currently, energy intensive) by future AI capabilities and progress. A small sampling of schools and disciplines below – more exist - apologies for not adding yours to this summary. School of practice for Physical Sciences & Engineering Technology School of practice for Behavioral & Social Sciences, Humanities & Arts People School of practice for Managerial Sciences & Entrepreneurship Information & Organizations Comp. Sci./AI HCI/Robotics Electrical & Mech. Eng. Systems Engineering Economics Public Policy & Law Design Information Systems Operations Research Marketing & Strategy Read enough of Kline (1995) to understand conceptual foundation of multidisciplinary thinking and the techno-extension factor and the accelerating socio-technical system design loop concepts. 11/05/2025 National Academy - Service Systems and AI 97
Why upskilling with AI trend is important to systems thinking Talent development is moving from I to T to X (eXtended with AI) National Academy - Service Systems and AI 98 6 T-shape Skills Knowledge Areas To be eXtended By AI tools: 1. Disciplines 2. Systems 3. Cultures 4. Technologies 5. Practices 6. Mindsets 11/05/2025
Final Thoughts: Communications • Communication between responsible actors: • Appropriateness • Speed • Accuracy • Responsible actors • Collaborate well – “insanely great collaborations possible” (win-win-win) • However, there is still the competition for collaborators • So… • Learning to invest wisely in becoming better future versions of self (individual and collective)is a key future challenge • Rawls (1971) A Theory of Justice – has thought experiments to consider
Speed Test: Words Per Minute Speaking/Listening versus Writing/Reading • People speak on average between 100-150 words per minute • Many people are comfortable listening at 200-300 words per minute • Writing an essay on a familiar topic, people write about 10-20 words a minute • Many people are comfortable reading at about 400-600 words per minute (Shu 2023) (Barnard 2022) See also: https://calculatingempires.net/