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Spohrer PHD_ICT_KES 20230316 v10.pptx
This document summarizes Jim Spohrer's presentation on service in the humanity-centered AI era. Some key points include: - AI has progressed significantly since its inception in the 1950s but still has a long way to go, and the focus is shifting from artificial intelligence to intelligence augmentation to help people upskill. - There are different views on service and AI from different disciplines like economics, computer science, and service science, with service science taking a broader view of responsible actors upskilling with AI to improve service. - Upskilling entire nations with AI while also decarbonizing will be two of the greatest challenges of the 21st century. - Responsible actors need to learn
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Spohrer PHD_ICT_KES 20230316 v10.pptx
- 1. 2023 PhD_ICT_KES Service inthe Humanity-Centered AI Era 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 Arianit Kurti for the invitation to discuss Service in the Humanity-Centered AI Era Thursday March 16, 2023, 16:00 CET Highly recommend: Humankind: A Hopeful History By Dutch Historian, Rutger Bregman <- Thanks To Ray Fisk For suggesting this book, see My summary here. See also ServCollab.
- 2. PHD ICT KES– https://phdictkes.eu/about/ University academic disciplines should not compete with each other, because they are all on a transdisciplinary journey. Real world problems do not respect discipline boundaries. The “real mission” is to better empower and motivate autodidacts (lifelong learners) to identify and work on important/meaningful problems. The core of “service in the humanity-centered AI era” is about asking better questions and working on important problems.
- 3. How, What, andWhy? Inspiring AI upskilling (IA) • How to learn • AI-powered search can help people - motivated people – to learn about whatever they put their minds to learning • What to learn • AI technological capabilities and limitations – foundational models • AI applications that can actually improve processes for how things get done (case studies - productivity, quality, compliance, sustainability, decarbonization) • AI-as-a-service investment cases to motivate stakeholders to change to better win-win interactions in business and societal service systems (investment pitch) • The “startup of you” investment case – learning to invest systematically and wisely (startup pitch) • Why learn? • Challenge and opportunity - nations must upskill with AI and decarbonize • Motivation is key – find the very best free online videos/courses and subscribe • Universities will play an increasingly important role as industry research partners and venture testbeds even as learners can do more and more on their own with online curriculum National Academies – Service Systems and AI 3
- 4. We get thefuture we invest in: AI tools to experiment with today • #1 Magic Eraser • #2 Craiyon • #3 Rytr And GPT-3, ChatGPT, GPT-4, Bing • #4 Thing Translator • #5 Autodraw • #6 Fontjoy • #7 Talk to Book • #8 This Person Does Not Exist • #9 Namelix • #10 Let's Enhance Thanks to @TessaRDavis for compiling this list: “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 4 Try at least two from the list as soon as possible What do you think? , DALL-E and Stable Diffusion Every person in a role in an organization is a service provider. 3/16/2023
- 5. “The best wayto 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
- 6. Today’s talk • Introduction •Service in the humanity-centered AI Era • From artificial intelligence (AI) to intelligence augmentation (IA) - AI Upskilling (focus on people) • Why I am optimistic • Responsible actors (with digital twins coming soon) are learning to invest in giving and getting better service • AI (by 1955 definition) has arrived • What’s really going on? It took 68 years, but… • Your data is becoming your AI… IA transformation • Part 1: Solving AI: Leaderboards • Roadmap and implications • Open technologies, innovation • Part 2: Solving IA: Better Building Blocks • Solving problems faster, creates new problems • Identity, social contracts, trust, resilience 3/16/2023 IBM Code #OpenTechAI 6
- 7. Icons of AIProgress • 1955-1956: Dartmouth Conference 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) • 2018: AlphaFold (Google DeepMinds) • 2022: DALL-E 2 & ChapGPT (OpenAI) • 2023: GPT-4 (OpenAI) & Microsoft (Bing) 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 7
- 8.
- 9. Narrow AI Emerging Broad AI Disruptiveand Pervasive General AI Revolutionary ▼ We are here 2050 and beyond 9 IBM Research AI © 2018 IBM Corporation The evolution of AI Borrowed from David Cox, IBM-MIT Lead
- 10. Smartphones pass entranceexams? When? 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 10 … when will your smartphone be able to take and pass any online course? And then be your coach, so you can pass too? OpenAI Answer: 2023 My Question: 2017
- 11. Artificial Intelligence (AI)has come a long way in almost seven decades… From David Michaelis, I4J Forum
- 12. … but westill have a long way to go. https://blog.irvingwb.com/blog/ January 26, 2023 Technical challenges no longer the hardest part, the AI to IA adjustment period is about responsible actors upskilling.
- 13. Overlap Acknowledgement: E. Noei,S. Brisson, Y. Liu Via Kelly Lyons, NAE Talk Oct 2022 2010 2019 13 Service science has come a long way in two decades… 2004-2011
- 14. … but westill have a long way to go. https://blog.irvingwb.com/blog/ December 1, 2022
- 15. Today’s Books Service isthe application of resources (e.g., knowledge) for the benefit of another* * another includes your future self and future generations as well. The two greatest challenges of the 21st century are simultaneously upskilling entire nations with AI (knowledge infrastructure, digital transformation) while decarbonizing entire nations (energy infrastructure, physical transformation). And accomplishing both with globally sustainable as-a-service models - servitization.
- 16. Three views onservice and AI Discipline View on Service View on AI Broader View Economics Service sector Productivity Sector productivity & quality – better economic systems Automation Technology improved agriculture and manufacturing, service sector is next up Computer Science Web services Capabilities AI provides human capabilities on tasks as technological capability – better tools Automation Robots will further automate agriculture and manufacturing, and eventually service sector as well Service science, based on Service-Dominant Logic Value cocreation Service is the application of resources (e.g., knowledge) for the benefit of another Augmentation Responsible actors (service system entities) upskilling with AI to give and get better service Humanity-Centered Responsible actors learning to invest in improved win-win interaction and change
- 17. Three views onservice and AI Discipline View on Service View on AI Broader View Economics Service sector Productivity Sector productivity & quality – better economic systems Automation Technology improved agriculture and manufacturing, service sector is next up Computer Science Web services Capabilities AI provides human capabilities on tasks as technological capability – better tools Automation Robots will further automate agriculture and manufacturing, and eventually service sector as well Service science, based on Service-Dominant Logic Value cocreation Service is the application of resources (e.g., knowledge) for the benefit of another Augmentation Responsible actors (service system entities) upskilling with AI to give and get better service Humanity-Centered Responsible actors learning to invest in improved win-win interaction and change
- 18. Three views onservice and AI Discipline View on Service View on AI Broader View Economics Service sector Productivity Sector productivity & quality – better economic systems Automation Technology improved agriculture and manufacturing, service sector is next up Computer Science Web services Capabilities AI provides human capabilities on tasks as technological capability – better tools Automation Robots will further automate agriculture and manufacturing, and eventually service sector as well Service science, based on Service-Dominant Logic Value cocreation Service is the application of resources (e.g., knowledge) for the benefit of another Augmentation Responsible actors (service system entities) upskilling with AI to give and get better service Humanity-Centered Responsible actors learning to invest in improved win-win interaction and change
- 19. Three views onservice and AI Discipline View on Service View on AI Broader View Economics Service sector Productivity Sector productivity & quality – better economic systems Automation Technology improved agriculture and manufacturing, service sector is next up Computer Science Web services Capabilities AI provides human capabilities on tasks as technological capability – better tools Automation Robots will further automate agriculture and manufacturing, and eventually service sector as well Service science, based on Service-Dominant Logic Value cocreation Service is the application of resources (e.g., knowledge) for the benefit of another Augmentation Responsible actors (service system entities) upskilling with AI to give and get better service Humanity-Centered Responsible actors learning to invest in improved win-win interaction and change
- 20. Humanity-Centered Harmonization ofAI for Service
- 21. Humanity-Centered Harmonization ofDisciplines - 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 soci—technical system design loop concepts. 3/16/2023 National Academy - Service Systems and AI 21
- 22. Why upskilling withAI 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 22 6 T-shape Skills Knowledge Areas To be eXtended By AI tools: 1. Disciplines 2. Systems 3. Cultures 4. Technologies 5. Practices 6. Mindsets 3/16/2023
- 23. June 12, 2022– The Economist Magazine Cover March of the machines A SPECIAL ISSUE ON ARTIFICIAL INTELLIGENCE June 21, 2022 – COSMOPOLITAN Magazine Cover – The A.I. Issue Meet the World’s First Artificially Intelligent Magazine Cover And it only took 20 seconds to make Historic Examples of AI’s Foundational Models Becoming Useful
- 24.
- 25. DALL-E Prompt: Create animage that illustrates a person upskilling with AI, showing their determination and resilience in the face of uncertainty and change. The image should convey the idea that upskilling with AI is a way for individuals to stay ahead in the job market and be prepared for the future of work. The person in the image should be depicted as confident and focused, surrounded by technology and tools that symbolize their journey towards upskilling in AI. The overall feel of the image should be modern, sleek, and inspiring. Upskilling with AI: Staying Resilient in Uncertain Times
- 26. Upskilling with AI:Staying Resilient in Uncertain Times DALL-E Prompt: Create a magazine cover image that captures the theme of "Upskilling with AI: Staying Resilient in Uncertain Times". The image should show a person who is determined and optimistic, despite the challenges of the current job market and economic uncertainty. They should be depicted as actively engaged in learning and improving their AI skills, surrounded by cutting-edge technology.
- 27. Read Wakefield (2020) enough to understandwhat 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 27 AI Tools in coming decades… 3/16/2023
- 28. Call to Action:Create SIRs • Responsible actors need to learn to invest wisely in getting the future service innovations we want with AI – guided by “Service Innovation Roadmaps (SIRs).” National Academy - Service Systems and AI 28 Read enough of IfM and IBM (2008) to understand what a “Service Innovation Roadmap (SIR)” is – and who should be creating them. 3/16/2023
- 29. Concluding Remarks: TwoBooks 3/16/2023 Jim Spohrer (ISSIP.org) 29
- 30. Better Models (Spohrer,Maglio, Vargo, Warg 2022) • Increasing complex, interconnected world • All models are wrong, some are useful • Better models are needed of • the world – both physical, social, virtual (science) • people and win-win interactions (logics) • organizations and win-win change (architecture) • technologies (AI) • Better models for better investing • “We get the future we invest in, so responsible actors must learn to invest wisely and systematically in improved win-win interaction and change.” 3/16/2023 Jim Spohrer (ISSIP.org) 30
- 31. Service in the AIera Science science Service dominant (S-D) logic Service Dominant Architecture (SDA) Service in the AI era revisited Core message? Better automation and augmentation improve service processes Better science improves understanding (learning) processes Better logics improve interaction processes Better architectures improve change processes X+AI requires learning to invest systematically and wisely to improve service Where are the better models? Technology Disciplines Minds Enterprise Disciplines + AI Minds + AI Enterprise + AI What type of model? Digital twins Digital twins Digital twins Digital twins Digital twins Service in the AI Era: Science, Logic, and Architecture Perspectives (Spohrer, Maglio, Vargo, Warg – request your digital copy – Spohrer@gmail.com)
- 32. From Human-Centered toHumanity-Centered Design (Norman 2023) • Human-Centered Design 1. Solve the core, root issues, not just the problem as presented (which is often the symptom, not the cause). 2. Focus on the people. 3. Take a systems point of view, realizing that most complications result from the interdependencies of the multiple parts. 4. Continually test and refine the proposed designs to ensure they truly meet the concerns of the people for whom they are intended. 3/16/2023 Jim Spohrer (ISSIP.org) 32 • Humanity-Centered Design 1. Solve the core, root issues, not just the problem as presented (which is often the symptom, not the cause). 2. Focus on the entire ecosystem of people, all living things, and the physical environment. 3. Take a long-term, systems point of view, realizing that most complications result from the interdependencies of the multiple parts and that many of the most damaging impacts on society and the ecosystem reveal themselves only years or even decades later. 4. Continually test and refine the proposed designs to ensure they truly meet the concerns of the people and ecosystem for whom they are intended. 5. Design with the community and as much as possible support designs by the community. Professional designers should serve as enablers, facilitators, and resources, aiding community members to meet their concerns.
- 33. Discussion • Are youpositive or negative about AI? • If positive, are you using any specific AI tools today? • See list of AI tools to try on a previous slide • How are you investing in upskilling with AI? • If negative, do you have a specific concern (“ditch to avoid”) – for example…? • AI will take away my job • AI will be used primarily by “bad actors” for mischief • Or used by social media platforms to generate more clicks/attention thru angry reactions • AI will try to take over people and planet • AI will deskill and weaken people over time • … or other concerns about AI? • Do you believe responsible actors (e.g., people, businesses, universities, governments, etc.) are learning to to invest systematically and wisely in getting the future we want? If not, why not – what is needed? • Join ISSIP.org (free for individuals) if you would like to continue the conversation! National Academy - Service Systems and AI 33 Read enough of pages 45-54 of Spohrer, Maglio, Vargo, Warg (2022) to formulate an opinion on the topic of “investing wisely to get the future service systems we want.” 3/16/2023
- 34. Part 1: SolvingAI • Technical challenges and social adjustment period 3/16/2023 Jim Spohrer (ISSIP.org) 34
- 35. Questions • What isthe timeline for solving AI and IA? • TBD: When can a CEO buy AI capability <X> for price <Y>? • Who are the leaders driving AI progress? • What will the biggest benefits from AI be? • What are the biggest risks associated with AI, and are they real? • What other technologies may have a bigger impact than AI? • What are the implications for stakeholders? • How should we prepare to get the benefits and avoid the risks? 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 35
- 36. Timeline: Short History 3/16/2023 ©IBM Cognitive Opentech Group (COG) 36 Dota 2 “Deep Learning” for “AI Pattern Recognition” depends on massive amounts of “labeled data” and computing power available since ~2012; Labeled data is simply input and output pairs, such as a sound and word, or image and word, or English sentence and French sentence, or road scene and car control settings – labeled data means having both input and output data in massive quantities. For example, 100K images of skin, half with skin cancer and half without to learn to recognize presence of skin cancer.
- 37. Timeline: Every 20years, compute costs are down by 1000x • Cost of Digital Workers • Moore’s Law can be thought of as lowering costs by a factor of a… • Thousand times lower in 20 years • Million times lower in 40 years • Billion times lower in 60 years • Smarter Tools (Terascale) • Terascale (2017) = $3K • Terascale (2020) = ~$1K • Narrow Worker (Petascale) • Recognition (Fast) • Petascale (2040) = ~$1K • Broad Worker (Exascale) • Reasoning (Slow) • Exascale (2060) = ~$1K 37 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 2080 2040 2000 1960 $1K $1M $1B $1T 2060 2020 1980 +/- 10 years $1 Person Average Annual Salary (Living Income) Super Computer Cost Mainframe Cost Smartphone Cost T P E T P E AI Progress on Open Leaderboards Benchmark Roadmap to solve AI/IA
- 38. Timeline: GDP/Employee 3/16/2023 (c)IBM 2017, Cognitive Opentech Group 38 (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
- 39. Timeline: Leaderboards Framework AIProgress on Open Leaderboards - Benchmark Roadmap Perceive World Develop Cognition Build Relationships Fill Roles Pattern recognition Video understanding Memory Reasoning Social interactions Fluent conversation Assistant & Collaborator Coach & Mediator Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions Chime Thumos SQuAD SAT ROC Story ConvAI Images Context Episodic Induction Plans Intentions Summarization Values ImageNet VQA DSTC RALI General-AI Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation WMT DeepVideo Alexa Prize ICCMA AT Learning from Labeled Training Data and Searching (Optimization) Learning by Watching and Reading (Education) Learning by Doing and being Responsible (Exploration) 2018 2021 2024 2027 2030 2033 2036 2039 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 39 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level -> +3 See: https://paperswithcode.com/sota
- 40. Who is winning 3/16/2023(c) IBM 2017, Cognitive Opentech Group 40 https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
- 41. Robots by Country •Industrial robots per 10,000 people by country 3/16/2023 IBM #OpenTechAI 41 34
- 42. Sweden 3/16/2023 (c) IBMMAP COG .| 42
- 43. Economic Growth Rates2035: AI Projected Impact 3/16/2023 (c) IBM MAP COG .| 43
- 44. AI Benefits • Accessto expertise • “Insanely great” labor productivity for trusted service providers • Digital workers for healthcare, education, finance, etc. • Better choices • ”Insanely great” collaborations with others on what matters most • AI for IA = Augmented Intelligence and higher value co-creation interactions 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 44
- 45. AI Risks • JobLoss • Shorter term bigger risk = de-skilling • Super-intelligence • Shorter term bigger risk = bad actors 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 45
- 46. Other Technologies: Biggerimpact? Yes. • Augmented Reality (AR)/ Virtual Reality (VR) • Game worlds grow-up • Trust Economy/ Security Systems • Trust and security immutable • Advanced Materials/ Energy Systems • Manufacturing as cheap, local recycling service (utility fog, artificial leaf, etc.) 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 46
- 47. Part 2: SolvingIA • Rapidly advancing technology and social adjustment (regulations) period 3/16/2023 Jim Spohrer (ISSIP.org) 47
- 48. 3/16/2023 © IBM 2015,IBM Upward University Programs Worldwide accelerating regional development 48 Cognitive Mediators for all people in all roles
- 49. Occupations = ManyTasks 3/16/2023 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 49
- 50. Watson Discovery Advisor 3/16/2023 ©IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 50 Simonite, T. 2014. Software Mines Science Papers to Make New Discoveries. MIT. November 25, 2014. URL: http://m.technologyreview.com/news/520461/software-mines-science-papers-to-make-new-discoveries/
- 51. 10 million minutesof experience 3/16/2023 Understanding Cognitive Systems 51
- 52. 2 million minutesof experience 3/16/2023 Understanding Cognitive Systems 52
- 53. Hardware < Software< Data < Experience < Transformation 3/16/2023 Understanding Cognitive Systems 53 Value migrates to transformation – becoming our future selves; people, businesses, nations = service system entities Pine & Gilmore (1999) Transformation Roy et al (2006) Data Osati (2014) Experience Life Log
- 54. Courses • 2015 • “Howto build a cognitive system for Q&A task.” • 9 months to 40% question answering accuracy • 1-2 years for 90% accuracy, which questions to reject • 2025 • “How to use a cognitive system to be a better professional X.” • Tools to build a student level Q&A from textbook in 1 week • 2035 • “How to use your cognitive mediator to build a startup.” • Tools to build faculty level Q&A for textbook in one day • Cognitive mediator knows a person better than they know themselves • 2055 • “How to manage your workforce of digital workers.” • Most people have 100 digital workers. 3/16/2023 54 Take free online cognitive classes today at cognitiveclass.ai
- 55. Types: Progression ofmodels Models = instruction set of future 3/16/2023 Understanding Cognitive Systems 55 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
- 56. Trust: Two Communities 3/16/2023IBM Code #OpenTechAI 56 Service Science OpenTech AI Trust: Value Co-Creation, Transdisciplinary Trust: Ethical, Safe, Explainable, Open Communities Special Issue AI Magazine? Handbook of OpenTech AI?
- 57. 3/16/2023 © IBM 2015,IBM Upward University Programs Worldwide accelerating regional development 57 I have… Have you noticed how the building blocks just keep getting better?
- 58. Learning to program: Myfirst program 3/16/2023 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 58 Early Computer Science Class: Watson Center at Columbia 1945 Jim Spohrer’s First Program 1972
- 59. 3/16/2023 59 1955 19751995 2015 2035 2055 Better Building Blocks
- 60. Artificial Leaf • DanielNocera, a professor of energy science at Harvard who pioneered the use of artificial photosynthesis, says that he and his colleague Pamela Silver have devised a system that completes the process of making liquid fuel from sunlight, carbon dioxide, and water. And they’ve done it at an efficiency of 10 percent, using pure carbon dioxide—in other words, one-tenth of the energy in sunlight is captured and turned into fuel. That is much higher than natural photosynthesis, which converts about 1 percent of solar energy into the carbohydrates used by plants, and it could be a milestone in the shift away from fossil fuels. The new system is described in a new paper in Science. 3/16/2023 IBM Code #OpenTechAI 60
- 61. Food from Air •Although the technology is in its infancy, researchers hope the "protein reactor" could become a household item. • Juha-Pekka Pitkänen, a scientist at VTT, said: "In practice, all the raw materials are available from the air. In the future, the technology can be transported to, for instance, deserts and other areas facing famine. • "One possible alternative is a home reactor, a type of domestic appliance that the consumer can use to produce the needed protein." • According to the researchers, the process of creating food from electricity can be nearly 10 times as energy efficient as photosynthesis, the process used by plants. 3/16/2023 IBM Code #OpenTechAI 61
- 62. Exoskeletons for Elderly •A walker is a “very cost-effective” solution for people with limited mobility, but “it completely disempowers, removes dignity, removes freedom, and causes a whole host of other psychological problems,” SRI Ventures president Manish Kothari says. “Superflex’s goal is to remove all of those areas that cause psychological-type encumbrances and, ultimately, redignify the individual." 3/16/2023 IBM Code #OpenTechAI 62
- 63. Be Prepared • Understandopen AI code + data + models + stacks + communities • Leaderboards • Ethical conduct • Learn 3 R’s of IBM’s Cognitive Opentech Group (COG) • Read arXiv • Redo with Github • Report with Jupyter notebooks on DSX and/or leaderboards • Improve your team’s skills of rapidly rebuilding from scratch • Build your open code eminence • Understand open innovation • Communities + Leaderboards 3/16/2023 (c) IBM 2017, Cognitive Opentech Group 63 1972 used Punch cards 2016 used IBM Watson Open APIs to win… 2022 OpenAI DALL-E 2 and ChatGPT 2023 GPT-4
- 64. Resilience: Rapidly Rebuilding FromScratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. 3/16/2023 IBM Code #OpenTechAI 64 What if the ”bad actors” get the upper hand?
- 65. 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
- 66. 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
- 67. 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
- 68. 3/16/2023 The International Societyof Service Innovation Professionals (ISSIP.org) 68
- 69. IA Progression –Tool, Assistant, Collaborator, Coach, Mediator 3/16/2023 Jim Spohrer (ISSIP) 69 Rouse & Spohrer (2018) Siddike, Spohrer, Demirkan, Kodha (2018) Araya (2018) Spohrer& Siddike (2018)
- 70. Intelligence Augmentation (IA)= Socio-Technical Extension Factor on Capabilities • Engelbart (1962) • Spohrer & Engelbart (2002) 3/16/2023 Jim Spohrer (ISSIP) 70 Dedicated to Douglas E. Engelbart, Inventor The Mouse (Pointing Device) The Mother of All Demos Bootstrapping Practice/Augmentation Theory Note: Bush (1945) and Licklider (1960) created funding programs that benefitted Engelbart in building working systems.
- 71. IA as Socio-TechnicalExtension Factor on Capabilities & Values IA (human values) is not AI (technology capability) Difference 1: IA leads to more capable people even when scaffold removed Difference 2: IA leads to more responsible people to use wisely the capabilities 3/16/2023 Jim Spohrer (ISSIP) 71 Superminds Malone (2018) Things that Make Us Smart Norman (1994) Worldboard Augmented Perception Spohrer (1999) Bicycles for the Mind Kay & Jobs (1984) Techno-Extension Factor Measurement & Accelerating Socio-Technical Design Loop Kline (1996)
- 72. 3/16/2023 Jim Spohrer(ISSIP.org) 72 0 25 50 100 125 150 Automobile 75 Years 50 100 Telephone Electricity Radio Television VCR PC Cellular % Adoption Capability Augmentation and Adoption Rate Increases
- 73. Learning to invest •Run = Routine Activities • Transform = Copy Activities • Innovate = Invent and Apply Activities 3/16/2023 Jim Spohrer (ISSIP.org) 73 Innovate Invest in each type of change
- 74. 74 How responsible entities(service systems) learn and change over time History and future of Run-Transform-Innovate investment choices • Diverse Types • Persons (Individuals) • Families • Regional Entities • Universities • Hospitals • Cities • States/Provinces • Nations • Other Enterprises • Businesses • Non-profits • Learning & Change • Run = use existing knowledge or standard practices (use) • Transform = adopt a new best practice (copy) • Innovate = create a new best practice (invent) Innovate Invest in each type of change Spohrer J, Golinelli GM, Piciocchi P, Bassano C (2010) An integrated SS-VSA analysis of changing job roles. Service Science. 2010 Jun;2(1-2):1-20. March JG (1991) Exploration and exploitation in organizational learning. Organization science. 1991 Feb;2(1):71-87. URL: exploit explore
- 75. “The best wayto 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
- 76. 3/16/2023 76 1955 19751995 2015 2035 2055 Better Building Blocks
- 77. Additional Resources • ArthurWB (2019) Foundations of Complexity Economics. Nature Review Physics. • Dietrich BL, Plachy EC, Norton MF (2014) Analytics Across the Enterprise. • Donofrio N, DeMarco M (2022) If Nothing Changes, Nothing Changes: The Nick Donofrio. • Fleming M (2022) Breakthrough: The Growth Revolution (in an Era of Artificial Intelligence and Worker Engagement). • IfM and IBM (2008) Succeeding through service innovation: A service perspective for education, research, business and government. • Larson RC (2022) Model Thinking for Everyday Life Working Wonders with a Blank Sheet of Paper. (Coming Soon). • Lebovitz S, Lifshitz-Assaf H, Levina N (2022) To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis. Organization Science. • Madhavan G, Poste G, Rouse W (2020) Complex Unifiable System. Editors' Note: Systemic Vistas. Winter 2020. The Bridge. • Maglio PP, Kieliszewki CA, Spohrer JC (2010) Handbook of Service Science • Maglio PP, Kieliszewki CA, Spohrer JC, Lyons K, Patrício L, Sawatani Y (2019) Handbook of Service Science, Vol II • McDermid JA (2022) Safe, Ethical & Sustainable: A Mantra for All Seasons? • Munn L (2022) The uselessness of AI ethics. • Norman D (2023) Design for a Better World: Meaningful, Sustainable, Humanity Centered • Rouse WB (2018) Life with a cognitive assistant. (2022) Emily 2.0.. • Rouse WB, Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation. • Schneiderman (2022) Human-Centered AI. • Spohrer J (2017) Imagination Challenge: Quantify and graph cost of digital workers and GDP per employee USA from 1960-2080. • Spohrer J, Maglio, PP (2009) Service Science: Toward a Smarter Planet. In Service Engineering. • Spohrer J, Maglio PP, Vargo SL, Warg M (2022) Service in the AI Era: Science, Logic, and Architecture Perspectives. • US 110th Congress (2007) SEC. 1005. STUDY OF SERVICE SCIENCE. • Vargo SL, Lusch RF (2016) Institutions and Axioms: An Extension and Update of Service-Dominant Logic. JAMS. • Wakefield J (2022) Why you may have a thinking digital twin within a decade. BBC News Online. • West S, Meierhofer J, Mangla U (2022) Smart Services Summit: Smart Services Supporting the New Normal. • West S, Stoll O, Muller-Csernetzky P (2022) A Handbook for Smart Service Design - The design of Smart Services in a world of people, process and things. • Wladalsky-Berger I (2016) The Continuing Evolution of Service Science. (2019) The Increasing Demand for Hybrid, “T-Shaped” Workers . (2021) The Supply Chain Economy - A New Categorization of the US Economy (2022) A New Measurement Framework for the Digital Economy. (2022) Foundation Models: AI’s Exciting New Frontier. Service Systems Engineering in the Human-Centered AI Era 77
- 78. 3/16/2023 Jim Spohrer(ISSIP.org) 78 APPLE https://podcasts.apple.com/us/podcast/service-science-and-the-impending-ai-revolution/id1612743401?i=1000583800244 SPOTIFY: https://open.spotify.com/episode/0n3h9rgX6UYDCwxgTzokoK?si=yVF0mtHsRZSmdfy-aMi8DA GOOGLE https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5idXp6c3Byb3V0LmNvbS8xOTQ5NTE3LnJzcw?sa=X&ved=2ahUKEwiPzL-Zxvv6AhXzjo4IHVbTAuUQ9sEGegQIARAC
- 79. Service Systems Engineeringin the Human-Centered AI Era 79 Value Science Engineering Policy Investing in Skills for Diverse Systems to Sustainably Serve People and Planet in the AI Era Management Service Science Management Engineering Many disciplines Many sectors Many regions/cultures (understanding & communications) Deep in one sector Deep in one region/culture Deep in one discipline T-Shaped Skills Depth and Breadth People-centered Data-intensive +Design-Arts- Public-Policy
- 80. Service Science: ConceptualFramework 3/16/2023 (c) IBM MAP COG .| 80 Service Science
- 81. (c) IBM MAPCOG .| 81 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)
- 82. 82 Time ECOLOGY 14B Big Bang (Natural World) 10K Cities (Human-Made World) Sun writing (symbols andscribes) 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
- 83. 83 University Trend: “SisterCampuses” (People Flows) University sub-systems Disciplines in Schools (circles) Innovation Centers (squares) E.g., CMU Website (2009) “Research Centers: where it all happens – to solve real-world problems” Disciplines in Schools Award degrees Single-discipline focus Research discipline problems Innovation Centers (ICs) Industry/government sponsors Multi-disciplinary teams Research real-world systems D D D D D D water & waste transportation health energy/grid e-government food & supply chain
- 84. 84 City Trend: “SisterCities” (People Flows) World as System of Systems World (light blue - largest) Nations (green - large) Regions (dark blue - medium) Cities (yellow - small) Universities (red - smallest) Cities as System of Systems -Transportation & Supply Chain -Water & Waste Recycling -Food & Products ((Nano) -Energy & Electricity -Information/ICT & Cloud (Info) -Buildings & Construction -Retail & Hospitality/Media & Entertainment -Banking & Finance -Healthcare & Family (Bio) -Education & Professions (Cogno) -Government (City, State, Nation) Nations: Innovation Opportunities - GDP/Capita (level and growth rate) - Energy/Capita (fossil and renewable) Developed Market Nations (> $20K GDP/Capita) Emerging Market Nations (< $20K GDP/Capita) IBM UP WW: Tandem Awards: Increasing university linkages (knowledge exchange interactions)