Jim Spohrer directs IBM's open-source AI efforts and gives a presentation on the future of AI, discussing timelines for solving different AI challenges, leaders in the field, and implications for stakeholders in preparing for both the benefits and risks of advanced AI. The document also includes slides on AI progress benchmarks, computing costs over time, economic growth projections with AI, and other emerging technologies that could have a larger impact than AI.
The document discusses the future of artificial intelligence (AI) and business value from a service science perspective. It begins by noting that the COVID-19 pandemic is accelerating digital transformation. It then provides a service science perspective, viewing transformation as collaborating with people and responsible entities. An AI perspective is presented as focusing on automation by collaborating with machines. An intelligence augmentation perspective is discussed as involving collaboration with both people and machines. The document outlines how service science views the future as smarter and wiser service systems transforming to better versions of themselves by competing for collaborators through win-win games.
Jim Spohrer is the director of IBM's open-source Artificial Intelligence developer ecosystem effort. He has a background in physics, speech recognition, and service science. The document discusses the future of AI, including timelines for solving AI, who the leaders are, the potential benefits and risks of AI, and how other technologies may have a bigger impact. It emphasizes that AI should augment human intelligence and capabilities rather than replace humans.
The document discusses the future of artificial intelligence (AI) and post-pandemic society from a service science perspective. It notes that the 2020 pandemic accelerated digital transformation, including online work, learning, and socializing. Service science predicts that as businesses and society transform, competing for collaborators will increasingly shape value co-creation between entities. The document provides a decade-by-decade view of information technologies, AI, society, and service science from 2020 to 2080.
20210325 jim spohrer sir rel future_ai v10 copyISSIP
Jim Spohrer directs IBM's open-source AI developer ecosystem. The document provides biographical information about Spohrer, including his educational background in physics, computer science, and AI. It then outlines Spohrer's career path at Apple, IBM, and as founder of IBM's Service Research group. The final sections advertise Spohrer's upcoming presentation on service innovation roadmaps and responsible learning entities. The presentation will discuss how various entity types can create roadmaps to optimize existing knowledge, adopt new practices, and create new practices through different levels of investment in learning and upskilling activities.
The document summarizes Jim Spohrer's presentation on creating good community outcomes. Some key points:
- Most communities and their members aspire to continuously improve and transform into better future versions of themselves through mutual learning and support.
- Mastering new technologies is a common goal that community members help each other achieve through sharing knowledge from basic to advanced levels.
- The future of communities and artificial intelligence will likely involve greater collaboration between people and digital technologies to accelerate transformations.
The document discusses the future of AI and society from a service science perspective. It argues that the COVID-19 pandemic is accelerating digital transformation and the shift to online platforms. Service science predicts that in this new environment, entities will increasingly compete for collaborators through value co-creation interactions to jointly elevate their capabilities. The document outlines how service science and AI view the future differently, with service science focusing on transforming systems of people and AI focusing on automation. It provides a framework for understanding smarter and wiser service systems over time.
Jim Spohrer provides considerations for AI projects. He recommends performing an audit of existing AI projects and evolving evaluation criteria to include performance and trust. Spohrer also emphasizes the importance of celebrating victories, rewarding talent development through diversity and upskilling, and monitoring technology developments. He warns against underestimating ongoing costs and overestimating short-term impacts. Spohrer outlines timelines for AI progress based on compute costs and provides frameworks for benchmarking and evaluating AI capabilities.
The document discusses the future of artificial intelligence (AI) and business value from a service science perspective. It begins by noting that the COVID-19 pandemic is accelerating digital transformation. It then provides a service science perspective, viewing transformation as collaborating with people and responsible entities. An AI perspective is presented as focusing on automation by collaborating with machines. An intelligence augmentation perspective is discussed as involving collaboration with both people and machines. The document outlines how service science views the future as smarter and wiser service systems transforming to better versions of themselves by competing for collaborators through win-win games.
Jim Spohrer is the director of IBM's open-source Artificial Intelligence developer ecosystem effort. He has a background in physics, speech recognition, and service science. The document discusses the future of AI, including timelines for solving AI, who the leaders are, the potential benefits and risks of AI, and how other technologies may have a bigger impact. It emphasizes that AI should augment human intelligence and capabilities rather than replace humans.
The document discusses the future of artificial intelligence (AI) and post-pandemic society from a service science perspective. It notes that the 2020 pandemic accelerated digital transformation, including online work, learning, and socializing. Service science predicts that as businesses and society transform, competing for collaborators will increasingly shape value co-creation between entities. The document provides a decade-by-decade view of information technologies, AI, society, and service science from 2020 to 2080.
20210325 jim spohrer sir rel future_ai v10 copyISSIP
Jim Spohrer directs IBM's open-source AI developer ecosystem. The document provides biographical information about Spohrer, including his educational background in physics, computer science, and AI. It then outlines Spohrer's career path at Apple, IBM, and as founder of IBM's Service Research group. The final sections advertise Spohrer's upcoming presentation on service innovation roadmaps and responsible learning entities. The presentation will discuss how various entity types can create roadmaps to optimize existing knowledge, adopt new practices, and create new practices through different levels of investment in learning and upskilling activities.
The document summarizes Jim Spohrer's presentation on creating good community outcomes. Some key points:
- Most communities and their members aspire to continuously improve and transform into better future versions of themselves through mutual learning and support.
- Mastering new technologies is a common goal that community members help each other achieve through sharing knowledge from basic to advanced levels.
- The future of communities and artificial intelligence will likely involve greater collaboration between people and digital technologies to accelerate transformations.
The document discusses the future of AI and society from a service science perspective. It argues that the COVID-19 pandemic is accelerating digital transformation and the shift to online platforms. Service science predicts that in this new environment, entities will increasingly compete for collaborators through value co-creation interactions to jointly elevate their capabilities. The document outlines how service science and AI view the future differently, with service science focusing on transforming systems of people and AI focusing on automation. It provides a framework for understanding smarter and wiser service systems over time.
Jim Spohrer provides considerations for AI projects. He recommends performing an audit of existing AI projects and evolving evaluation criteria to include performance and trust. Spohrer also emphasizes the importance of celebrating victories, rewarding talent development through diversity and upskilling, and monitoring technology developments. He warns against underestimating ongoing costs and overestimating short-term impacts. Spohrer outlines timelines for AI progress based on compute costs and provides frameworks for benchmarking and evaluating AI capabilities.
This document summarizes a presentation on the future of artificial intelligence given by Jim Spohrer. Some key points:
- AI and digital technologies are accelerating the transformation of society, including how people work, learn, and interact.
- Service science predicts that as business and society transform, responsible entities will increasingly compete for collaborators through win-win interactions that improve capabilities.
- The future of AI involves "Responsible Entities Learning" - both people and machines learning and collaborating.
- Measuring socio-technical capabilities and determining what tasks can be safely delegated to machines will be important questions going forward.
The document provides an overview of future artificial intelligence (AI) and intelligence augmentation (IA) from a service science perspective. It discusses how the COVID-19 pandemic is accelerating digital transformation and the shift to more online activities. Service science predicts that in this transformation, competing for collaborators through win-win interactions will shape how value is co-created between different entities. The document then provides a decade-by-decade view from 2020 to 2080 on how technologies like IT, AI and IA may impact society and interact with service science concepts. It compares the perspectives of AI which focuses on automation, and service science which focuses on transformation of people and responsible entities.
20201213 jim spohrer icis augmented intelligence v6ISSIP
Jim Spohrer is the director of IBM's Cognitive OpenTech group. He has a background in physics, computer science, and artificial intelligence. Spohrer discusses the concept of Intelligence Augmentation (IA), which aims to enhance human capabilities through socio-technical systems rather than just develop autonomous AI systems. IA is defined as not just developing technology capabilities but also focusing on more responsible and capable people. Spohrer outlines how IA can progress from being a tool, to an assistant, collaborator, coach and mediator. He also discusses the importance of trust between the AI/service science and open source communities.
This document discusses University-Based Entrepreneurial Ecosystems (U-BEEs) and their role in accelerating regional development. It notes that universities are usually top job creators in regions when they have associated incubators, science parks, data centers, hospitals, schools and other facilities. These U-BEEs connect information flows between ecosystems in cities. The document also provides an outline of its discussion on trends of universities becoming more locally connected research centers and the evolution of cities becoming smarter.
The document summarizes perspectives on the online platform economy and gig workers in the US. It discusses both the opportunities and challenges, noting growing flexibility but also lack of benefits. While reskilling efforts exist, they remain limited and siloed. Moving forward will require upskilling workers with T-shaped skills across technologies, work practices, and mindsets. Platforms and policies should aim to balance winner-take-all approaches with improving opportunities for all.
Some key points:
- Jim Spohrer directs IBM's open-source AI developer ecosystem efforts and has a background in physics, computer science, and service science.
- Service science views the future as one where entities like businesses and societies will compete for collaborators to co-create value and elevate capabilities together over time.
- The future of AI will bring greater acceleration of digital transformation through technologies like IA, which involves collaboration between people, machines, and the organizations that produce the machines.
- Service science and AI take different approaches
The document discusses scaling excellence in service systems. It notes that service systems involve stakeholders, technology, shared information, and organizations connected through value propositions. Scaling service systems requires investment in roadmaps for smarter buildings, universities, and cities. A service science perspective considers the evolving ecology of entities within service systems, how value is co-created, and how capabilities are elevated. Cognitive systems and cognitive assistants can help scale service innovation excellence and close the skills gap between knowing and doing.
Jim Spohrer discusses service innovation roadmaps and responsible entities learning in an AI era. He notes that service science focuses on transforming responsible entities like people, businesses, and nations to apply knowledge for mutual benefit, while AI focuses on automating tasks. Spohrer advocates for service innovation roadmaps to help responsible entities learn and become better versions of themselves through running existing practices, transforming by adopting new best practices, and innovating to create new best practices.
20211129 jim spohrer wsif digital_entrepreneurship v8ISSIP
This document discusses digital entrepreneurship and the World Social Innovation Forum (WSIF) panel on the topic. It provides background on Jim Spohrer, the panelist invited to speak. Spohrer recommends the book "Humankind" by Rutger Bregman. The document then poses the question "What does it mean to become a digital entrepreneur?" and provides some potential responses and resources on digital entrepreneurship, AI, and developing a digital workforce. It shares quotes on the relationship between AI and entrepreneurship. The rest of the document provides biographical information on Spohrer and what he studies regarding service science and open source AI.
20211107 jim spohrer otago entrepreneurship v6ISSIP
Jim Spohrer gave a presentation on the future of AI to an entrepreneurship class at Otago University. Some key points from the presentation include:
- Compute costs for AI are decreasing exponentially every 20 years, which will lower the costs of digital workers and AI systems.
- Lower compute costs can translate to increased productivity and GDP per employee for nations.
- AI progress can be measured using open benchmarks and leaderboards that track progress in tasks like computer vision, natural language processing and robotics.
- The future of many industries and jobs may be transformed by AI, with jobs that utilize AI likely to replace those that do not.
2021004 jim spohrer alan hartman_retirement v3ISSIP
(1) The document discusses the future of artificial intelligence and service science in a post-pandemic society from a service science perspective. (2) It compares AI, which aims to automate human intelligence, to service science, which studies how systems like businesses and societies can transform and improve lives through cooperation. (3) The document outlines how service science views systems as evolving over time through running existing practices, transforming by adopting new practices, and innovating to create new practices.
The document discusses how technology is increasingly performing work tasks through digital workers, freeing up opportunities for people. It suggests educational technology could help people realize those opportunities. The document outlines how costs of computing are decreasing exponentially, and how AI and machine learning have advanced through deep learning techniques applied to large datasets. It envisions a future where cognitive systems/mediators could take online courses and coach students, with tools enabling much faster development of such systems. Overall, the document presents an optimistic view of how educational technology and cognitive systems could help improve learning and opportunities.
Jim Spohrer gave a presentation at Purdue University on service innovation in the AI era. Some key points from the presentation include:
- Service science is an emerging field that studies how responsible entities can transform through win-win interactions to improve quality of life, while AI aims to automate tasks performed by people.
- As computing costs decrease exponentially every 20 years due to Moore's law, AI capabilities will become much more accessible, with narrow tasks being solved by 2040 and broad human-level abilities by 2060.
- This will greatly increase productivity and GDP per employee over time if the benefits of AI are shared widely. However, there are also risks like job loss that need to be addressed.
Jim Spohrer was invited to be a panelist for John Hagel's presentation at the Fall 2021 Berkeley Innovation Forum. Spohrer recommends the book "Humankind: A Hopeful History" by Rutger Bregman. He notes his experience at IBM of facing fears of product to service and proprietary to open source transformations, which led IBM to acquire Red Hat for $34B and spin off Kyndryl. Spohrer serves on the board of ISSIP.org and is a retired IBM executive focusing his studies on service science and open source AI, where trust is key.
20211103 jim spohrer oecd ai_science_productivity_panel v5ISSIP
Jim Spohrer serves on the board of directors for ISSIP.org and as a contributor to the Linux Foundation AI and Data Foundation. He previously directed IBM's open-source AI developer ecosystem effort and other roles. Spohrer discusses service science and open source AI, noting that trust is key to both. He provides background on his career and research interests in service science and comparisons between AI and service science approaches. Spohrer outlines a conceptual framework for service science and discusses the future of smarter and wiser service systems where entities transform to better versions through win-win games and collaborating.
This document discusses IBM's global research capabilities and focuses on inventing things that matter to the world. It provides an overview of IBM's research areas such as healthcare, government, financial services, industry cloud, IoT, blockchain, cognitive robotics, and more. It highlights IBM's leadership in patents and the deep skills of its scientists. It also discusses IBM's investments in quantum computing, AI, healthcare/life sciences, and more. The document emphasizes that foundational breakthroughs have led to recognition like Nobel Prizes and that IBM outpaces competitors in patents. It aims to convey that IBM researchers invent things that can make a difference globally.
HICSS-55 Meeting - Minitrack: Recording for full session will be uploaded to ISSIP.or YouTube channel
Case studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms[4]Co-Chairs: Maarit Palo (IBM, Finland), Pekka Neittaanmaki (UJyvaskyla, Finland), Jim Spohrer (IBM Retired, ISSIP.org, USA)
2021006 jim spohrer mc gill_precision_convergence_panel v3ISSIP
Jim Spohrer served as a panelist for a webinar on global value chain resilience hosted by Gary Gereffi. Spohrer is on the board of ISSIP.org and contributes to the Linux Foundation AI and Data Foundation. He retired from IBM in 2021 after a career in speech recognition, service science research, and open source AI. Spohrer posed questions on how trust and resilience are related in global value chains and how artificial intelligence and digital services may impact resilience.
2021020 jim spohrer ai for_good_conference future_of_ai v4ISSIP
Jim Spohrer serves on the Board of Directors of ISSIP and previously worked at IBM, where he directed various AI and service science initiatives. He discusses the future of AI, predicting that compute costs will decrease by a factor of 1000 every 20 years, enabling digital workers to become more capable and affordable. He presents a timeline and framework for benchmarking AI progress on open leaderboards to achieve human-level performance in various tasks over time. The best way to predict the future, he says, is to inspire students to build a better future.
Inventing Things tTht Matter to the World; Inventing Things tht that Matter to the WOrld; Inventing Things That Matter to the WOrld; Inventing Things That Matter to the World (correct)
The document discusses the future of AI, including how AI has progressed over time from early systems like Deep Blue and Watson to current advances in deep learning for pattern recognition, but that commonsense reasoning will still take many more years of research. It outlines a timeline for solving different AI problems based on leaderboards and benchmarks, and discusses implications for stakeholders in preparing for both the benefits and risks of advancing AI technologies.
This document summarizes a presentation on the future of artificial intelligence given by Jim Spohrer. Some key points:
- AI and digital technologies are accelerating the transformation of society, including how people work, learn, and interact.
- Service science predicts that as business and society transform, responsible entities will increasingly compete for collaborators through win-win interactions that improve capabilities.
- The future of AI involves "Responsible Entities Learning" - both people and machines learning and collaborating.
- Measuring socio-technical capabilities and determining what tasks can be safely delegated to machines will be important questions going forward.
The document provides an overview of future artificial intelligence (AI) and intelligence augmentation (IA) from a service science perspective. It discusses how the COVID-19 pandemic is accelerating digital transformation and the shift to more online activities. Service science predicts that in this transformation, competing for collaborators through win-win interactions will shape how value is co-created between different entities. The document then provides a decade-by-decade view from 2020 to 2080 on how technologies like IT, AI and IA may impact society and interact with service science concepts. It compares the perspectives of AI which focuses on automation, and service science which focuses on transformation of people and responsible entities.
20201213 jim spohrer icis augmented intelligence v6ISSIP
Jim Spohrer is the director of IBM's Cognitive OpenTech group. He has a background in physics, computer science, and artificial intelligence. Spohrer discusses the concept of Intelligence Augmentation (IA), which aims to enhance human capabilities through socio-technical systems rather than just develop autonomous AI systems. IA is defined as not just developing technology capabilities but also focusing on more responsible and capable people. Spohrer outlines how IA can progress from being a tool, to an assistant, collaborator, coach and mediator. He also discusses the importance of trust between the AI/service science and open source communities.
This document discusses University-Based Entrepreneurial Ecosystems (U-BEEs) and their role in accelerating regional development. It notes that universities are usually top job creators in regions when they have associated incubators, science parks, data centers, hospitals, schools and other facilities. These U-BEEs connect information flows between ecosystems in cities. The document also provides an outline of its discussion on trends of universities becoming more locally connected research centers and the evolution of cities becoming smarter.
The document summarizes perspectives on the online platform economy and gig workers in the US. It discusses both the opportunities and challenges, noting growing flexibility but also lack of benefits. While reskilling efforts exist, they remain limited and siloed. Moving forward will require upskilling workers with T-shaped skills across technologies, work practices, and mindsets. Platforms and policies should aim to balance winner-take-all approaches with improving opportunities for all.
Some key points:
- Jim Spohrer directs IBM's open-source AI developer ecosystem efforts and has a background in physics, computer science, and service science.
- Service science views the future as one where entities like businesses and societies will compete for collaborators to co-create value and elevate capabilities together over time.
- The future of AI will bring greater acceleration of digital transformation through technologies like IA, which involves collaboration between people, machines, and the organizations that produce the machines.
- Service science and AI take different approaches
The document discusses scaling excellence in service systems. It notes that service systems involve stakeholders, technology, shared information, and organizations connected through value propositions. Scaling service systems requires investment in roadmaps for smarter buildings, universities, and cities. A service science perspective considers the evolving ecology of entities within service systems, how value is co-created, and how capabilities are elevated. Cognitive systems and cognitive assistants can help scale service innovation excellence and close the skills gap between knowing and doing.
Jim Spohrer discusses service innovation roadmaps and responsible entities learning in an AI era. He notes that service science focuses on transforming responsible entities like people, businesses, and nations to apply knowledge for mutual benefit, while AI focuses on automating tasks. Spohrer advocates for service innovation roadmaps to help responsible entities learn and become better versions of themselves through running existing practices, transforming by adopting new best practices, and innovating to create new best practices.
20211129 jim spohrer wsif digital_entrepreneurship v8ISSIP
This document discusses digital entrepreneurship and the World Social Innovation Forum (WSIF) panel on the topic. It provides background on Jim Spohrer, the panelist invited to speak. Spohrer recommends the book "Humankind" by Rutger Bregman. The document then poses the question "What does it mean to become a digital entrepreneur?" and provides some potential responses and resources on digital entrepreneurship, AI, and developing a digital workforce. It shares quotes on the relationship between AI and entrepreneurship. The rest of the document provides biographical information on Spohrer and what he studies regarding service science and open source AI.
20211107 jim spohrer otago entrepreneurship v6ISSIP
Jim Spohrer gave a presentation on the future of AI to an entrepreneurship class at Otago University. Some key points from the presentation include:
- Compute costs for AI are decreasing exponentially every 20 years, which will lower the costs of digital workers and AI systems.
- Lower compute costs can translate to increased productivity and GDP per employee for nations.
- AI progress can be measured using open benchmarks and leaderboards that track progress in tasks like computer vision, natural language processing and robotics.
- The future of many industries and jobs may be transformed by AI, with jobs that utilize AI likely to replace those that do not.
2021004 jim spohrer alan hartman_retirement v3ISSIP
(1) The document discusses the future of artificial intelligence and service science in a post-pandemic society from a service science perspective. (2) It compares AI, which aims to automate human intelligence, to service science, which studies how systems like businesses and societies can transform and improve lives through cooperation. (3) The document outlines how service science views systems as evolving over time through running existing practices, transforming by adopting new practices, and innovating to create new practices.
The document discusses how technology is increasingly performing work tasks through digital workers, freeing up opportunities for people. It suggests educational technology could help people realize those opportunities. The document outlines how costs of computing are decreasing exponentially, and how AI and machine learning have advanced through deep learning techniques applied to large datasets. It envisions a future where cognitive systems/mediators could take online courses and coach students, with tools enabling much faster development of such systems. Overall, the document presents an optimistic view of how educational technology and cognitive systems could help improve learning and opportunities.
Jim Spohrer gave a presentation at Purdue University on service innovation in the AI era. Some key points from the presentation include:
- Service science is an emerging field that studies how responsible entities can transform through win-win interactions to improve quality of life, while AI aims to automate tasks performed by people.
- As computing costs decrease exponentially every 20 years due to Moore's law, AI capabilities will become much more accessible, with narrow tasks being solved by 2040 and broad human-level abilities by 2060.
- This will greatly increase productivity and GDP per employee over time if the benefits of AI are shared widely. However, there are also risks like job loss that need to be addressed.
Jim Spohrer was invited to be a panelist for John Hagel's presentation at the Fall 2021 Berkeley Innovation Forum. Spohrer recommends the book "Humankind: A Hopeful History" by Rutger Bregman. He notes his experience at IBM of facing fears of product to service and proprietary to open source transformations, which led IBM to acquire Red Hat for $34B and spin off Kyndryl. Spohrer serves on the board of ISSIP.org and is a retired IBM executive focusing his studies on service science and open source AI, where trust is key.
20211103 jim spohrer oecd ai_science_productivity_panel v5ISSIP
Jim Spohrer serves on the board of directors for ISSIP.org and as a contributor to the Linux Foundation AI and Data Foundation. He previously directed IBM's open-source AI developer ecosystem effort and other roles. Spohrer discusses service science and open source AI, noting that trust is key to both. He provides background on his career and research interests in service science and comparisons between AI and service science approaches. Spohrer outlines a conceptual framework for service science and discusses the future of smarter and wiser service systems where entities transform to better versions through win-win games and collaborating.
This document discusses IBM's global research capabilities and focuses on inventing things that matter to the world. It provides an overview of IBM's research areas such as healthcare, government, financial services, industry cloud, IoT, blockchain, cognitive robotics, and more. It highlights IBM's leadership in patents and the deep skills of its scientists. It also discusses IBM's investments in quantum computing, AI, healthcare/life sciences, and more. The document emphasizes that foundational breakthroughs have led to recognition like Nobel Prizes and that IBM outpaces competitors in patents. It aims to convey that IBM researchers invent things that can make a difference globally.
HICSS-55 Meeting - Minitrack: Recording for full session will be uploaded to ISSIP.or YouTube channel
Case studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms[4]Co-Chairs: Maarit Palo (IBM, Finland), Pekka Neittaanmaki (UJyvaskyla, Finland), Jim Spohrer (IBM Retired, ISSIP.org, USA)
2021006 jim spohrer mc gill_precision_convergence_panel v3ISSIP
Jim Spohrer served as a panelist for a webinar on global value chain resilience hosted by Gary Gereffi. Spohrer is on the board of ISSIP.org and contributes to the Linux Foundation AI and Data Foundation. He retired from IBM in 2021 after a career in speech recognition, service science research, and open source AI. Spohrer posed questions on how trust and resilience are related in global value chains and how artificial intelligence and digital services may impact resilience.
2021020 jim spohrer ai for_good_conference future_of_ai v4ISSIP
Jim Spohrer serves on the Board of Directors of ISSIP and previously worked at IBM, where he directed various AI and service science initiatives. He discusses the future of AI, predicting that compute costs will decrease by a factor of 1000 every 20 years, enabling digital workers to become more capable and affordable. He presents a timeline and framework for benchmarking AI progress on open leaderboards to achieve human-level performance in various tasks over time. The best way to predict the future, he says, is to inspire students to build a better future.
Inventing Things tTht Matter to the World; Inventing Things tht that Matter to the WOrld; Inventing Things That Matter to the WOrld; Inventing Things That Matter to the World (correct)
The document discusses the future of AI, including how AI has progressed over time from early systems like Deep Blue and Watson to current advances in deep learning for pattern recognition, but that commonsense reasoning will still take many more years of research. It outlines a timeline for solving different AI problems based on leaderboards and benchmarks, and discusses implications for stakeholders in preparing for both the benefits and risks of advancing AI technologies.
Jim from IBM discusses the future of AI. He notes that while AI is currently hyped, pattern recognition using deep learning only works because of the large amounts of data and computing power now available. True AI requiring commonsense reasoning is still 5-10 years away. He outlines a timeline for solving different AI problems and notes IBM's $240 million partnership with MIT to advance AI. The benefits of AI include access to expertise and improved productivity, but risks include job loss and potential issues with superintelligence. Other technologies like augmented reality may have a larger impact. Stakeholders in AI include individuals, organizations, governments, and industries. [END SUMMARY]
This document discusses the future of AI and provides an overview of key topics including:
- AI is currently at the peak of hype but deep learning depends on large datasets and computing power which are now available. Commonsense reasoning remains a challenge.
- IBM and MIT have invested $240 million over 10 years in an AI mission to advance capabilities.
- The timeline for solving AI involves benchmarks like image recognition, translation, and general AI. Full human-level AI may be 5-10 years away.
- Leaders in AI include companies investing heavily in research like IBM, Google, and Microsoft. Economic benefits are predicted but job losses and risks from advanced AI also exist.
- Other technologies like augmented
The document discusses future directions and timelines for artificial intelligence (AI). It provides a projected timeline for when different AI capabilities may be achieved and at what cost. Some key points discussed include:
- By 2040, "narrow AI" systems capable of specific tasks like recognition may cost around $1,000, and "broad AI" systems capable of reasoning may follow by 2060 at similar costs.
- Labor costs are projected to decrease over time relative to the decreasing costs of AI systems, with digital workers potentially outcompeting human labor on a cost basis.
- An framework of AI progress and capabilities is presented, spanning perception, cognition, relationships and roles. Milestones and benchmark leaderboards are discussed
This document discusses the future of artificial intelligence (AI) and provides timelines and considerations. It addresses key questions such as the timeline for solving AI, leaders in the field, potential benefits and risks of AI, other impactful technologies, implications for stakeholders, and how to prepare for AI. The presentation outlines a framework for progress in AI capabilities from narrow to broad to general AI. It also discusses emerging technologies like augmented reality, blockchain, advanced materials and their potential impacts.
Jim from IBM discusses the future of AI. He talks about successes in AI such as image recognition and challenges such as commonsense reasoning. IBM has launched various initiatives related to AI such as the IBM-MIT collaboration and IBM Quantum. The Center for Open Source Data and AI Technologies (CODAIT) aims to make AI solutions easier to create and deploy using open source. The talk discusses types of AI systems, where AI is in the hype cycle, and how data is becoming AI. It outlines a roadmap for solving AI using leaderboards and better building blocks and discusses implications for identity, trust and resilience.
Jim Spohrer from IBM gave a talk on the future of AI. Some key points:
1) IBM is heavily involved in open source AI through its Cognitive Opentech Group and projects on GitHub. Leaderboards like SQuAD are used to measure progress.
2) The timeline for solving difficult AI problems like commonsense reasoning and learning from experience is 5-10 more years. Job and skills impacts will be felt sooner.
3) Stakeholders at all levels need to participate in and learn about open source AI to help build the future and prepare for changes. Understanding how to rapidly rebuild systems from scratch will be important.
Jim Spohrer, director of IBM Cognitive OpenTech, discusses AI at IBM including its past, present, and future. Some key points include:
- IBM made early contributions to AI through projects like Deep Blue (chess-playing computer) and Watson (Jeopardy-playing computer).
- The present state of AI is focused on deep learning for pattern recognition tasks due to available data and computing power.
- The future of AI will require capabilities beyond deep learning like commonsense reasoning, which will take additional research over the next 5-10 years.
- IBM is working on technologies like quantum computing and blockchain to advance AI and tackle challenges like explainability, security, and ethics.
- Open source projects and
The document summarizes an AI4Good Hackathon event. It provides details on several building blocks that are improving for AI and sustainability applications, including an artificial leaf that can produce liquid fuel from sunlight more efficiently than photosynthesis, and a protein reactor that can create food from electricity nearly 10 times more efficiently than photosynthesis. It also discusses an exoskeleton being developed to help the elderly move with more dignity and freedom. The document promotes the Call for Code initiative, which challenges developers to create applications to address humanitarian issues using AI and cloud technologies. It provides an overview of the 2018 challenge and highlights the winning Project OWL application and some of the other top finalists.
Jim from IBM discusses various topics related to artificial intelligence including:
- The timeline for solving different AI problems and reaching human-level performance on benchmarks.
- Leaders and communities driving progress in open source AI.
- Potential benefits of AI including increasing productivity and GDP, as well as risks that need to be addressed.
- Preparing students and citizens for future jobs and skills needed in an increasingly automated world.
- The importance of open source communities working on challenges like bias and fairness in AI.
Jim Spohrer gave a presentation on preparing for the future with open artificial intelligence from a service science perspective. He thanked the organizers for the invitation and discussed four books related to scientific progress and responsibility to future generations. Spohrer explained that service science draws from various disciplines to study value co-creation phenomena and the evolution of complex service systems. He outlined IBM's involvement in establishing service science and discussed concepts like service-dominant logic. Spohrer concluded by taking questions on topics like the timeline for solving AI and implications for stakeholders.
Jim Spohrer (IBM) gave a presentation at the UCLA BIT Conference on July 19, 2018 about the future of AI. He discussed how AI is currently at the peak of hype but deep learning requires large amounts of data and computing power. He presented a roadmap to solve AI through open technologies, innovation, and service system evolution. Spohrer argued stakeholders should prepare for the AI future by learning skills like coding on platforms like GitHub and competing on AI leaderboards to advance progress.
This document discusses trust in interactions with cognitive assistants. It begins by defining cognitive assistants as new decision tools that can augment human capabilities by understanding our environment with depth and clarity. Cognitive assistants can provide high-quality recommendations to help people make better data-driven decisions, and significantly augment people's problem-solving abilities through interaction. The document then discusses components of trust from different academic disciplines, such as ability, benevolence, integrity, predictability, and shared values. It poses questions about what jobs will remain for humans and ethical issues regarding situations like domestic violence. The document conjectures that AI combined with other information sources could surpass average professionals in some areas. It also speculates that societies of AI may form to optimize tasks in
This document provides an overview of artificial intelligence and machine learning. It discusses the evolution of AI from narrow AI to emerging broad AI to revolutionary general AI. It notes that currently we are in the era of narrow AI. The document also includes timelines showing the increasing capabilities of AI and decreasing costs of computing over time. It highlights areas where AI and machine learning are being applied such as image tagging, language translation, and quantum computing. Examples of innovative technologies discussed include an artificial leaf that can produce liquid fuel from sunlight, air, and water, and exoskeletons to help the elderly move with dignity.
This document summarizes a presentation about the future of AI and Fabric for Deep Learning (FfDL). It discusses how deep learning has advanced due to increased data and computing power, but that commonsense reasoning will require more research. FfDL is introduced as an open source project that aims to make deep learning accessible and scalable across frameworks. It uses a microservices architecture on Kubernetes to manage training jobs efficiently. Research is ongoing to further develop explainable and robust AI capabilities.
This document discusses the role of companies in open source software development. It notes that while open source software was traditionally developed by volunteers, companies are now playing a more active role through acquiring open source companies, bringing development in-house, and spinning off proprietary versions. However, this could endanger the future viability and security of open source software. To help maintain open source software, the summary recommends that companies should have a clear open source policy that encourages employee contributions, raise awareness of the open source software they use and its vulnerabilities, and incentivize contributions that focus on security, maintenance as well as features useful to the company.
Magic Eraser allows users to easily remove unwanted objects and distractions from photos with just a few clicks. Craiyon is an AI image generator that lets users create new images from text prompts. Rytr is a voice assistant that helps schedule meetings, set reminders, and answer questions using natural language conversations. Thing Translator is a machine translation tool that can translate between over 100 languages with state-of-the-art neural models.
Similar to 20210128 jim spohrer ai house_fund v4 (20)
Host Santokh Badesha: https://www.linkedin.com/in/santokh-badesha-24b72916/
Recommended Readings (If Possible, Skim Before the Talk)
Patent: Management of Usage Costs of a Resource (IBM)
Jim Spohrer patent: Graphical Interface for Interacting Constrained Actors (Apple)
Jim Spohrer's Google Scholar Profile, includes open publications as well as patents
Apple's ATG Authoring Tools - Balancing Open and Proprietary Work
Forbes - Cognitive World
AI Magazine - Role of Open Source in AI
AI and Education 20240327 v16 for Northeastern.pptxISSIP
Prof. Mark L. Miller (https://www.linkedin.com/in/mlmiller751/), Northeastern University, class on AI and Education
Speaker: Jim Spohrer (https://www.linkedin.com/in/spohrer/)
===
Speaker: Dr. Jim Spohrer, retired Apple and IBM executive, currently Board of Directors for ISSIP.org (International Society of Service Innovation Professionals).
Title: AI and Education: A Historical Perspective and Possible Future Directions
Abstract: This talk will briefly survey my 50 years working in the area of AI & Education. At MIT (1974- 1978), MIT's summer EXPLO schools for AI and entrepreneurship classes. At Verbex (1978-1982), speech recognition, language models, early generative AI. At Yale (1982-1989), MARCEL, a generate- test-and-debug architecture and student model of programming bugs. At Apple (1989-1998), from content (SK8) to community (EOE) to context (WorldBoard). At IBM (1999 - 2021), service science and open source AI. At ISSIP (2021-present), generative AI and digital twins.
Bio:Jim’s Bio (142 words):
Jim Spohrer is a student of service science and open-source, trusted AI. He is a retired industry executive (Apple, IBM), who is a member of the Board of Directors of the non-profit International Society of Service Innovation Professionals (ISSIP). At IBM, he served as Director for Open Source AI/Data, Global University Programs, IBM Almaden Service Research, and CTO IBM Venture Capital Relations Group. At Apple, he achieved Distinguished Engineer Scientist Technologist (DEST) for authoring and learning platforms. After MIT (BS/Physics), he developed speech recognition systems at Verbex (Exxon), then Yale (PhD/Computer Science AI). With over ninety publications and nine patents, awards include AMA ServSIG Christopher Lovelock Career Contributions to the Service Discipline, Evert Gummesson Service Research, Vargo-Lusch Service-Dominant Logic, Daniel Berg Service Systems, and PICMET Fellow for advancing service science. In 2021, Jim was appointed a UIDP Senior Fellow (University-Industry Demonstration Partnership).
Readings:Apple's ATG Authoring Tools:
URL: https://dl.acm.org/doi/pdf/10.1145/279044.279173 Blog: WorldBoard
URL: https://service-science.info/archives/2060 Blog: Reflecting on Generative AI and Digital Twins
URL: https://service-science.info/archives/6521 Book: Service in the AI Era
Attached: Pages 46-54.Video: Speech Recognition (History)
URL: https://youtu.be/G9z4VAsw_kw
Thanks, -Jim
--Jim Spohrer, PhDBoard of Directors, ISSIP (International Society of Service Innovation Professionals) Board of Directors, ServCollab ("Serving Humanity Through Collaboration")Senior Fellow, UIDP ("Strengthening University-Industry Partnerships")Retired Industry Executive (Apple, IBM)
March 20, 2024
Host Ganesan Narayanasamy (https://www.linkedin.com/in/ganesannarayanasamy/)
Uploaded here:
===
Event 20230320
https://www.linkedin.com/posts/ganesannarayanasamy_productnation-semiconductorproductnation-activity-7174119132114620418-jvpx
Themed Shaping a Sustainable $1 Trillion Era, semicondynamics.org 2024 will gather industry experts on March 20th at Milpitas, California , for insights into the latest trends and innovations Accelerating AI with Semiconductor RTL Front end services and workforce development. The event will feature keynotes from the Semiconductor ecosystem, academia and Industries.
March 20, 2024
Host Ganesan Narayanasamy (https://www.linkedin.com/in/ganesannarayanasamy/)
Uploaded here:
===
Event 20230320
https://www.linkedin.com/posts/ganesannarayanasamy_productnation-semiconductorproductnation-activity-7174119132114620418-jvpx
Themed Shaping a Sustainable $1 Trillion Era, semicondynamics.org 2024 will gather industry experts on March 20th at Milpitas, California , for insights into the latest trends and innovations Accelerating AI with Semiconductor RTL Front end services and workforce development. The event will feature keynotes from the Semiconductor ecosystem, academia and Industries.
Jim Spohrer is an advisor to industry, academia, governments, startups and non-profits on topics of AI upskilling, innovation strategy, and win-win service in the AI era. He is a retired IBM executive and was previously the director of IBM's open-source AI developer ecosystem effort. In this talk, Spohrer discusses topics such as how to keep up with accelerating change, verifying results from generative AI, and understanding how generative AI works through concepts like monkeys at typewriters in high dimensional spaces. He emphasizes balancing hype with realism and doing work alongside gaining knowledge.
This document contains notes from a presentation by Jim Spohrer on leadership, career experiences, and technology topics. The presentation covers collaborating with others, teamwork practices, storytelling, communication skills, leadership habits and mindsets. It includes links to Spohrer's online profiles and resources. Tables provide estimates of increasing GDP per employee over time and a timeline of Spohrer's career highlights and accomplishments in the fields of service science and artificial intelligence.
It my pleasure to be with you all today – thanks to my host for the opportunity to speak with you all today.
Host: Leonard Walletzky <qwalletz@fi.muni.cz> (https://www.linkedin.com/in/leonardwalletzky/) +420 549 49 7690
Google Scholar: https://scholar.google.com/citations?user=aUvbsmwAAAAJ&hl=cs
Katrina Motkova (https://www.linkedin.com/in/kateřina-moťková-mba-a964a3175/en/?originalSubdomain=cz)
Speaker: Jim Spohrer <spohrer@gmail.com> (https://www.linkedin.com/in/spohrer/) +1-408-829-3112
I am Jim Spohrer, a retired Apple and IBM Executive, and currently a UIDP Senior Fellow, on the Board of Directors of ISSIP and ServCollab.
I am retired, meaning my primary activities are family-oriented – families are the oldest and most important type of service systems
I volunteer to help non-profits, mentor students, professionals, and retiree (some in retirement communities where the average age is 85) on AI & service science
My hobbies are hiking, reading, programming, and building my AI digital twin and humanoid robots for maintaining farms and farming equipment.
My hobbies are also trying to understand as much as I can about the system called the universe and mult-verse, and robots to rapidly rebuild civilization including themselves from scratch.
2001 - Nonzero: The Logic of Human Desitiny (Wright) - https://en.wikipedia.org/wiki/Nonzero:_The_Logic_of_Human_Destiny
2015 - Geek Heresy: Rescuing Social Change from the Cult of Technology - https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X
2021 - Humankind: A Hopeful History (Bregman) - https://en.wikipedia.org/wiki/Humankind:_A_Hopeful_History
Humankind - https://www.amazon.com/Humankind-Hopeful-History-Rutger-Bregman/dp/0316418536
Humankind Book Review - https://service-science.info/archives/5654
2022 - Service in the AI Era: Science, Logic, and Architecture Perspectives (2022) by Spohrer, Maglio, Vargo, Warg - https://www.amazon.com/Service-AI-Era-Architecture-Perspectives/dp/1637423039
2023 - Design for a Better World: Meaningful, Sustainable, Humanity-Centered (2023) by Don Norman - https://www.amazon.com/Design-Better-World-Meaningful-Sustainable/dp/0262047950/
It my pleasure to be with you all today – thanks to my host for the opportunity to speak with you all today.
Host: Leonard Walletzky <qwalletz@fi.muni.cz> (https://www.linkedin.com/in/leonardwalletzky/) +420 549 49 7690
Google Scholar: https://scholar.google.com/citations?user=aUvbsmwAAAAJ&hl=cs
Katrina Motkova (https://www.linkedin.com/in/kateřina-moťková-mba-a964a3175/en/?originalSubdomain=cz)
Speaker: Jim Spohrer <spohrer@gmail.com> (https://www.linkedin.com/in/spohrer/) +1-408-829-3112
I am Jim Spohrer, a retired Apple and IBM Executive, and currently a UIDP Senior Fellow, on the Board of Directors of ISSIP and ServCollab.
I am retired, meaning my primary activities are family-oriented – families are the oldest and most important type of service systems
I volunteer to help non-profits, mentor students, professionals, and retiree (some in retirement communities where the average age is 85) on AI & service science
My hobbies are hiking, reading, programming, and building my AI digital twin and humanoid robots for maintaining farms and farming equipment.
My hobbies are also trying to understand as much as I can about the system called the universe and mult-verse, and robots to rapidly rebuild civilization including themselves from scratch.
2001 - Nonzero: The Logic of Human Desitiny (Wright) - https://en.wikipedia.org/wiki/Nonzero:_The_Logic_of_Human_Destiny
2015 - Geek Heresy: Rescuing Social Change from the Cult of Technology - https://www.amazon.com/Geek-Heresy-Rescuing-Social-Technology/dp/161039528X
2021 - Humankind: A Hopeful History (Bregman) - https://en.wikipedia.org/wiki/Humankind:_A_Hopeful_History
Humankind - https://www.amazon.com/Humankind-Hopeful-History-Rutger-Bregman/dp/0316418536
Humankind Book Review - https://service-science.info/archives/5654
2022 - Service in the AI Era: Science, Logic, and Architecture Perspectives (2022) by Spohrer, Maglio, Vargo, Warg - https://www.amazon.com/Service-AI-Era-Architecture-Perspectives/dp/1637423039
2023 - Design for a Better World: Meaningful, Sustainable, Humanity-Centered (2023) by Don Norman - https://www.amazon.com/Design-Better-World-Meaningful-Sustainable/dp/0262047950/
Brno-IESS 20240206 v10 service science ai.pptxISSIP
It my pleasure to be with you all today – thanks to my host for the opportunity to speak with you all today.
Host: Leonard Walletzky <qwalletz@fi.muni.cz> (https://www.linkedin.com/in/leonardwalletzky/) +420 549 49 7690
Google Scholar: https://scholar.google.com/citations?user=aUvbsmwAAAAJ&hl=cs
Katrina Motkova (https://www.linkedin.com/in/kateřina-moťková-mba-a964a3175/en/?originalSubdomain=cz)
Speaker: Jim Spohrer <spohrer@gmail.com> (https://www.linkedin.com/in/spohrer/) +1-408-829-3112
NordicHouse 20240116 AI Quantum IFTF dfiscussionv7.pptxISSIP
Jim Spohrer presented on AI and quantum computing. He discussed the history of AI from the 1955 Dartmouth workshop to modern advances like AlphaGo, GPT-3, and DALL-E 2. Spohrer noted that computation costs have decreased exponentially over time, driving increases in knowledge worker productivity. He highlighted several experts and resources he follows to stay informed on AI capabilities and implications. Spohrer sees opportunities to improve learning and performance through advances in learning sciences, technology, lifelong learning, and early education. The talk addressed how generative AI works and challenges around verification.
20240104 HICSS Panel on AI and Legal Ethical 20240103 v7.pptxISSIP
20240103 HICSS Panel
Ethical and legal implications raised by Generative AI and Augmented Reality in the workplace.
Souren Paul - https://www.linkedin.com/in/souren-paul-a3bbaa5/
Event: https://kmeducationhub.de/hawaii-international-conference-on-system-sciences-hicss/
Congratulations to the organizers of the “Symposium for Celebrating 40 Years of Bayesian Learning in Speech and Language Processing” and to Prof. Chin-Hui Lee of Georgia Tech the Honorary Chair of the Symposium.
Thanks to Huck Yang (Amazon) for the invitation to record this short message.
Huck Yang
URL: https://www.linkedin.com/in/huckyang/
Event: https://bayesian40.github.io
Recording:
Slides:
URL: https://professionalschool.eitdigital.eu/generative-ai-essentials
Course on Generative Al
Description:
Generative AI is a world-changing power tool that is getting better by the day. So now is the time to get truly inspired, climb up the learning curve, and unleash more of your creative potential.
Learning Topics:
* Inspiration: What is Generative AI in the context of AI's history, present, and future
* Climbing Up: Ways to accelerate your learning trajectory
* Unleashing Creativity: Ways to stay future-ready in the AI era
What You'll Take Away:
By the end of this session, you'll understand the importance of upskilling with today's generative AI tools to get more work done, both faster and at higher quality, as well as some pitfalls to avoid, all within the broader context of the past, present, and future of Artificial Intelligence (AI) and Intelligence Augmentation (IA).
Learning Topics
Inspiration: What is Generative AI in the context of AI's history, present, and future.
Climbing Up: Ways to accelerate your learning trajectory.
Unleashing Creativity: Ways to stay future-ready in the AI era.
Deep dive into ChatGPT's features.
Techniques for basic and advanced prompting and real-world applications.
- Service science has progressed significantly in the past two decades since its inception in the early 2000s.
- However, there is still a long way to go to fully realize the potential of service science and its role in areas like upskilling with AI.
- Looking ahead, some of the biggest challenges will be upskilling entire nations with AI for digital transformation, while also decarbonizing nations through sustainable energy infrastructure - both accomplished through service-based business models.
Spohrer Open Innovation Reflections 20230911 v2.pptxISSIP
September 11, 2023
Berkeley Innovation Forum
Open Innovation Journey
Henry Chesbrough, Solomon Darwin, Jim Spohrer
https://corporateinnovation.berkeley.edu/wp-content/uploads/2023/07/BIF-Fall2023-7.28.23.pdf
Pre-Event: Monday, September 11, 2023 at The CITRIS Innovation Hub
UC Berkeley, 330 Sutardja Dai Hall, MC 1764
7:45pm - 8:30pm
8:45pm
Fireside Chat: The Open Innovation Journey - Moderated by Henry Chesbrough
Henry Chesbrough
Faculty Director, Garwood Center for Corporate Innovation, UC Berkeley
Olga Diamandis
Former Disney, Smuckers, Mattel, P&G Executive
Jim Spohrer
Former Exec: IBM, Distinguished Scientist at Apple, Director of IBM AI
Nitin Narkhede
General Manager, Emerging Technologies and Innovation, Wipro
Bus pick-up to Hotel Shattuck Plaza
Henry Chesbrough is a professor at the Haas Business School, UC Berkeley, and faculty director of the Garwood Center for Corporate Innovation. An internationally acclaimed author, Dr. Chesbrough’s Open Innovation concept was first introduced in his award-winning book, Open Innovation: The New Imperative for Creating and Profiting from Technology (2003). When he coined the term Open Innovation, he defined an approach that companies around the globe now use to innovate. Today, Chesbrough works directly with companies through Garwood’s programs to apply the principles of Open Innovation, and he continues to refine our understanding through his research and books.
Olga Diamandis is the senior manager at TE Connectivity. Previously, she served as principal technical architect at the Walt Disney Company. She also worked as principal scientst of innovation & knowledge management at The J.M. Smucker Company. Before that, she served as senior manager of Open Innovation at Mattel. She also has experience as a manager of global business development at Procter & Gamble, alongside a previous managerial role at Nestle.
Jim Spohrer previously served as IBM Director of Cognitive OpenTech - which includes open source AI/ML/DL - as well as director of IBM’s deep question-answering system Watson. Prior to that, he worked as a Distinguished Scientist in Learning Research at Apple Computer, Inc. where he developed SK8, Educational Object Economy - an open source learning object community - as well as WorldBoard which served as a vision for Planetary Augmented Reality system.
Nitin Narkhede is General Manager of Emerging Technologies and Innovation at Wipro Technologies. He is responsible for the development of new services and solutions based on emerging trends and technologies at Wipro. Nitin has been in the forefront of a number of technology and business model transitions during his 20 years of work at Wipro. Prior to his current assignment, he managed Wipro’s e-Business Solutions Practice in the Americas. Nitin has over 23 years of experience in the technology industry spanning IT strategy and planning, information systems and software product development, technology strategy and innovation management.
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
IGCSE Biology Chapter 14- Reproduction in Plants.pdf
20210128 jim spohrer ai house_fund v4
1. Future AI Break-Out Challenge
Jim Spohrer
Director, IBM Cognitive OpenTech
January 28, 2021
Questions: spohrer@gmail.com
Twitter: @JimSpohrer
LinkedIn: https://www.linkedin.com/in/spohrer/
Slack: https://slack.lfai.foundation
Presentations on line at: https://slideshare.net/spohrer
Thanks to Conrad for the invitation!
Conrad Voorsanger
The House Fund
2. Jim Spohrer, IBM Director, Cognitive OpenTech
Jim Spohrer directs IBM’s open-source Artificial Intelligence
developer ecosystem effort. After his MIT BS in Physics, he
developed speech recognition systems at Verbex (Exxon) before
receiving his Yale PhD in Computer Science/AI. In the 1990’s, he
attained Apple Computers’ Distinguished Engineer Scientist and
Technologist role for next generation learning platforms. He was
CTO IBM Venture Capital Group, co-founded IBM Almaden Service
Research, and led IBM Global University Programs. With over ninety
publications and nine patents, he received the 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 as LF AI Technical
Advisory Board Chairperson and ONNX Steering Committee
Member (2020-2021).
1/29/2021 (c) IBM 2020, Cognitive Opentech Group 2
5. Timeline: Leaderboards Framework
AI Progress 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
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 5
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
6. Timeline: Every 20 years,
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
6
1/29/2021 (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
7. Timeline: GDP/Employee
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 7
(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
10. Accelerating digital transformation and shift to robotics…
How will COVID-19 effect the need for and use of
robots in a service world with less physical contact?
Will robots improve or harm livelihoods/jobs?
Robots Rule Retail?
Taking away jobs
Telepresence Robot World?
Adding more jobs
Robots at Home?
Reducing need to have a job
T-shaped (L)earners
You will be assigned to a small team to discuss. Please have a team member to take notes of
the most important insights and/or questions that emerge from your discussion. Your notes
will be crucial for us to create a conference report, send to contact@creatingvalueconf.com
What is most probable to happen? What is desirable?
Spohrer
15. Breakout challenge
• Many startups are trying to create new labor or capital platforms.
• Your AI startup see them as customer.
• Use open-source Data and AI tools to help them organize their data.
• Pick a problem to discuss to the class as the basis of a startup.
• Who is the person who struggles with the problem?
• Describe that struggle.
• What is the data that's available to analyze?
• How do you address your end-user's problem?
• Come back in 10 minutes ready to present your idea in less than 90 seconds
speaking time.
1/29/2021 (c) IBM MAP COG .| 15
17. Future of AI
• What is the timeline for solving AI and IA?
• TBD: When can a CEO/anyone 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?
1/29/2021 (c) IBM 2020, Cognitive Opentech Group 17
18. Who is winning
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 18
https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
19. Robots by Country
• Industrial robots per 10,000 people by country
1/29/2021 IBM #OpenTechAI 19
34
22. AI Benefits
• Access to 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
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 22
23. AI Risks
• Job Loss
• Shorter term bigger risk
= de-skilling
• Super-intelligence
• Shorter term bigger risk
= bad actors
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 23
24. Other Technologies: Bigger impact? Yes.
• Augmented Reality (AR)/
Virtual Reality (VR)
• Game worlds
grow-up
• Blockchain/
Security Systems
• Trust and security
immutable
• Advanced Materials/
Energy Systems
• Manufacturing as cheap,
local recycling service
(utility fog, artificial leaf, etc.)
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25. “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
26. Artificial Leaf
• Daniel Nocera, 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.
1/29/2021 IBM Code #OpenTechAI 26
27. 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.
1/29/2021 IBM Code #OpenTechAI 27
28. 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."
1/29/2021 IBM Code #OpenTechAI 28
31. Smartphones pass entrance exams? When?
1/29/2021 (c) IBM 2017, Cognitive Opentech Group 31
… when will
your smartphone
be able to take and
pass any online
course? And then
be your coach, so
you can pass too?
32. Resilience:
Rapidly Rebuilding From Scratch
• Dartnell L (2012) The Knowledge: How to
Rebuild Civilization in the Aftermath of a
Cataclysm. Westminster London: Penguin
Books.
1/29/2021 IBM Code #OpenTechAI 32
33. Artificial Intelligence/
Computer Science
• "Computer science is the study of the phenomena surrounding computers. ... We
build computers and programs for many reasons. We build them to serve society
.... One of the fundamental contributions to knowledge of computer science has
been to explain, at a rather basic level, what symbols are. ... Symbols lie at the
root of intelligent action, which is, of course, the primary topic of artificial
intelligence. For that matter, it is a primary question for all of computer science.
For all information is processed by computers in the service of ends, and we
measure the intelligence of a system by its ability to achieve stated ends in the
face of variations, difficulties and complexities posed by the task environment.”
• Tenth Turing Awards Lecture: Allen Newell and Herbert A. Simon, “Computer
Science as Empirical Inquiry: Symbols and Search,”Communications of the ACM.
vol. 19, No. 3, pp. 113-126, March,1976. Available online at:
• https://www.cs.utexas.edu/~kuipers/readings/Newell+Simon-cacm-76.pdf
1/29/2021 (c) IBM MAP COG .| 33
34. IBM-MIT $240M
over 10 year AI mission
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55. Outline
• Context
• Disciplines (and the entities they study)
• Computer Science, AI, SD logic, Service Science
• Part 1: AI
• Seven Questions
• Better Building Blocks
• Your data is becoming your AI… transformation
• Part 2: Service Science
• Covid accelerating AI, Robotics adoption
• Open Technologies: From Smarter to Wiser
• Access Rights: Trust and Responsibility
1/29/2021 IBM Code #OpenTechAI 55
“there is nothing as practical as a good abstraction.”
56. Icons of AI Progress
• 1956: Dartmouth Conference
organized by:
• John McCarthy (Dartmouth, later
Stanford)
• Marvin Minsky (MIT)
• and two senior scientists:
• Claude Shannon (Bell Labs)
• Nathan Rochester (IBM)
• 1997: Deep Blue (IBM) - Chess
• 2011: Watson Jeopardy! (IBM)
• 2016: AlphaGo (Google DeepMinds)
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57. AI at IBM: Past (Nathan Rochester)
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58. Disciplines and some of the key entities they study
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Computer Science: Hardware, Software, Algorithms
Physical Symbol System Entities
AI: Intelligence, “NN Models”
Digital Cognitive System Entities
Chemistry: Atoms, Molecules, States of Matter,
Auto-Catalytic Molecular System Entities
Biology: Cells, DNA,
Biological Cognitive System Entities
Service science: Service, Value Co-Creation, Service system entities
Service science studies the evolving ecology
of service system entities,
their capabilities, constraints, rights, and responsibilities
their value co-creation and
capability co-elevation interactions, as well as
their outcome identities and reputations.
59. Brian Arthur - Economist
• The term “technological unemployment” is from John Maynard Keynes’s 1930 lecture,
“Economic possibilities for our grandchildren,” where he predicted that in the future, around
2030, the production problem would be solved and there would be enough for everyone, but
machines (robots, he thought) would cause “technological unemployment.” There would be
plenty to go around, but the means of getting a share in it, jobs, might be scarce. We are not quite
at 2030, but I believe we have reached the “Keynes point,” where indeed enough is produced by
the economy, both physical and virtual, for all of us. (If total US household income of $8.495
trillion were shared by America’s 116 million households, each would earn $73,000, enough for
a decent middle-class life.) And we have reached a point where technological unemployment is
becoming a reality. The problem in this new phase we’ve entered is not quite jobs, it is access to
what’s produced. Jobs have been the main means of access for only 200 or 300 years. Before
that, farm labor, small craft workshops, voluntary piecework, or inherited wealth provided access.
Now access needs to change again. However this happens, we have entered a different phase for
the economy, a new era where production matters less and what matters more is access to that
production: distribution, in other words—who gets what and how they get it. We have entered
the distributive era.
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Arthur WB (2017) Where is technology taking the economy. McKinsey Quarterly. October.
60. 1/29/2021 (c) IBM MAP COG .| 60
https://www.youtube.com/watch?v=WGK8MY8iZHA
61. Service-Dominant logic worldview and mindset
Year Publication Service Resource Integrators
2004 Vargo SL, Lusch RF (2004)
Evolving to a new dominant
logic for marketing. Journal of
marketing. 68(1):1-7.
The application of specialized skills
and knowledge is the fundamental
unit of exchange.
Operant resources are resources that
produce effects
2011 Vargo SL, Lusch RF (2011) It's
all B2B… and beyond: Toward
a systems perspective of the
market. Industrial marketing
management. 40(2):181-7.
The central concept in S-D logic is
that service — the application of
resources for the benefit of another
party — is exchanged for service
That is, all parties (e.g. businesses,
individual customers, households, etc.)
engaged in economic exchange are
similarly, resource-integrating, service-
providing enterprises that have the
common purpose of value (co)creation —
what we mean by “it is all B2B.”
2016 Vargo SL, Lusch RF.
Institutions and axioms: an
extension and update of
service-dominant logic.
Journal of the Academy of
Marketing Science. 2016 Jan
1;44(1):5-23.
value creation can only be fully
understood in terms of integrated
resources applied for another
actor’s benefit (service) within a
context, including the institutions
and institutional arrangements that
enable and constrain value creation.
To alleviate this limitation and facilitate a
better understanding of cooperation (and
coordination), an eleventh foundational
premise (fifth axiom) is introduced, focusing
on the role of institutions and institutional
arrangements in systems of value
cocreation: service ecosystems.
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62. Service Science the study of service systems entities
Year Publication Service Science Service System
2007 Spohrer J, Maglio, PP, Bailey J,
Gruhl, D (2007) Steps toward
a science of service
systems, IEEE Computer,
(40)1:71-77.
Services science is an emerging field
that seeks to tap into these and
other relevant bodies of knowledge,
integrate them, and advance three
goals—aiming ultimately to
understand service systems, how
they improve, and how they scale.
The components of a service system are
people, technology, internal and external
service systems connected by value
propositions, and shared information (such
as language, laws, and measures.
2008 Spohrer, J, Vargo S, Caswell N,
Maglio PP (2008) The service
system is the basic abstraction
of service science, HICSS-41,
NY: IEEE Press, Pp. 1-10.
Service science is the study of the
application of the resources of one
or more systems for the benefit of
another system in economic
exchange.
Informally, service systems are
collections of resources that can
create value with other service systems
through shared information.
2008 Maglio PP, Spohrer J (2008)
Fundamentals of service
science. Journal of the
academy of marketing
science. 36(1):18-20.
Service science is the study of
service systems, aiming to create a
basis for systematic service
innovation.
Service systems are value-co-creation
configurations of people, technology, value
propositions connecting internal and
external service systems, and shared
information (e.g., language, laws, measures,
and methods).
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63. Service Science the study of service system entities
1/29/2021 (c) IBM MAP COG .| 63
Year Publication Service Science Service System
2009 Spohrer J, Maglio PP (2009)
Service science: Toward a
smarter planet. In
Introduction to service
engineering, Eds. Karwowski
and Salvendy. Pp. 3-10
Service science is a specialization of
systems science. So service science
seeks to create a body of knowledge
that accounts for value-cocreation
between entities as they interact…
Service system entities are dynamic
configurations of resources. As described
below, resources include people,
organizations, shared information, and
technology.
2012 Spohrer J, Piciocchi P, Bassano
C (2012) Three frameworks
for service research: exploring
multilevel governance in
nested, networked systems.
Service Science. 4(2):147-160.
SSME+D is built on top of the
Service-Dominant logic (SD Logic)
worldview
A service system entity is a dynamic
configuration of resources (at least one of
which, the focal resource, is a person with
rights).
2013 Spohrer J, Giuiusa A,
Demirkan H, Ing D (2013)
Service science: reframing
progress with universities.
Systems Research and
Behavioral Science. 30(5):561-
569
Service science is an emerging
branch of systems sciences with a
focus on service systems (entities)
and value cocreation (complex non-
zero-sum interactions).
… complex adaptive entities - service
systems - within an ecology of nested,
networked entities… From a service science
perspective, progress can be thought of in
terms of the rights and responsibilities of
entities
64. Service Science the study of service system entities
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Year Publication Service Science Service System
2014 Spohrer J, Kwan SK, Fisk RP
(2014)Marketing: a service sci
ence and arts perspective,
Handbook of Service Market
ing Research, Eds. Rust RT,
Huang MH, NY:Edward Elgar,
pp. 489-526.
Service science (short for Service
Science, Management, Engineering,
Design, Arts, and Public Policy) is an
emerging transdiscipline for the (1)
study of evolving service system
entities and value co-creation
phenomena, as well as (2) pedagogy
for the education of 21st century T-
shaped service innovators from all
disciplines, sectors, and cultures.
So like all early stage scientific
communities, the language for talking
about service systems and value co-creation
phenomena continues to evolve. … Service
system entities are economic and social
actors, which configure (or integrate)
resources. … A formal service system entity
(SS-FSC3) is a legal, economic entity with
rights and responsibilities codified in
written laws.
2015 Spohrer J, Demirkan H,
Lyons (2015) Social Value: A
Service Science Perspective.
In: Kijima K. (eds) Service
Systems Science. Translational
Systems Sciences, vol 2.
Tokyo: Springer. Pp. 3-35.
Service science is an emerging
transdiscipline for the (1) study of
evolving service system entities and
value co-creation phenomena and
(2) pedagogy for the education of
twenty-first-century T-shaped
service innovators from all
disciplines, sectors, and cultures
Formal service system entities (as opposed
to informal service system entities) can be
ranked by the degree to which they are
governed by written (symbolic) laws and
evolve to increase the percentage of their
processes that are explicit and symbolic.
65. Service Science the study of service system entities
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Year Publication Service Science Service System
2016 Spohrer J (2016) Services
Science and Societal
Convergence. In W.S.
Bainbridge, M.C. Roco
(eds.),Handbook of Science
and Technology Convergence,
pp. 323-335
Service science is an emerging
transdiscipline for the (1) study of
evolving ecology of nested,
networked service system entities
and value co-creation phenomena,
as well as (2) pedagogy for the
education of the twenty-first-
century T-shaped (depth and
breadth) service innovators from all
disciplines, sectors, and cultures.
As service science emerges, we can begin
by “seeing” and counting service system
entities in an evolving ecology, working to
“understand” and make explicit their
implicit processes of valuing …
2016 Spohrer J (2016) Innovation
for jobs with cognitive
assistants: A service science
perspective, In Disrupting
Unemployment ,
Eds. Nordfors, Cerf,
Seng, Missouri: Ewing Marion
Kauffman Foundation, Pp.
157-174.
Service science is the emerging
transdiscipline that studies the
evolving ecology of nested,
networked service system entities,
their capabilities, constraints, rights,
and responsibilities.
There are perhaps twenty billion formal
service system entities in the world today,
each governed in part by formal written
laws. Every person, household, university,
business, and government is a formal
service system entity, but my dog, my
smartphone, and my ideas are not.
66. Service Science the study of service system entities
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Year Publication Service Science Service System
2017 Spohrer J, Siddike MAK,
Kohda Y (2017) Rebuilding
evolution: a service science
perspective. HICSS 50.
Service science is the study of the
evolving ecology of service system
entities, complex socio-technical
systems with rights and
responsibilities – such as people,
businesses, and nations.
Service systems are dynamic configurations
of people, technology, organization and
information that interact through value
proposition and co- create mutual value.
2019 Pakalla D, Spohrer J (2019,
forthcoming) Digital Service:
Technological Agency in
Service Systems. HICSS 52.
For the purposes of this paper,
service science can be summarized
as the study of the evolving ecology
of service system entities, their
capabilities, constraints, rights, and
responsibilities, including their
value co-creation and capability co-
elevation mechanisms .
Service systems are a type of socio-
technical system, such as people,
businesses, and nations, all with unique
identities, histories, and reputations based
on the outcomes of their interactions with
other entities.
67. Service Research
• Artificial Intelligence in Service
• "The theory specifies four intelligences required for service tasks—mechanical,
analytical, intuitive, and empathetic—and lays out the way firms should decide
between humans and machines for accomplishing those tasks.”
• Huang MH and Rust RT (2018) Artificial Intelligence in Service. Journal of
Service Research. 21(2):155–172.
• Customer Acceptance of AI in Service Encounters: Understanding
Antecedents and Consequences
• "expand the relevant set of antecedents beyond the established constructs and
theories to include variables that are particularly relevant for AI applications
such as privacy concerns, trust, and perceptions of “creepiness.”
• Ostrom AL, Foheringham D, Bitner MJ (2018, forthcoming) Customer
Acceptance of AI in Service Encounters: Understanding Antecedents and
Consequences. In Handbook of Service Science, Volume 2, Eds, Maglio,
Kieliszewski,Spohrer,Lyons,Patricio,Sawatani. New York: Springer. Pp. x-y.
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68. 1/29/2021 (c) IBM MAP COG .| 68
Microsoft acquiring GitHub $7.5B
2018 John Marks on Open Source
Models will run the world
Why SW is eating the world
69. Step Comment
GitHub Get an account and read the guide
MAX CODAIT’s Model Asset Exchange
Learn 3 R's - Read, Redo, Report Read (Medium/arXiv), Redo (GitHub), Report (Jupyter Notebook)
PapersWithCode Stay on top of recent advances; Do 3 R’s.
Kaggle Compete in a Kaggle competition
Leaderboards Compete to advance AI progress
Linux Foundation AI Help end-to-end open source industry AI & Data infrastructure
Mozilla Common Voice Donate your speech; Label and verify data; Recruit others.
Figure Eight Generate a set of labeled data (also Mechanical Turk)
Design New Challenges Build for Call for Code/Code and Response; Build your AI Helper;
Build test-taker, that can switch to tutor-mode; Etc.
Open Source Guide Establish open source culture in your organization
1/29/2021 IBM Code #OpenTechAI 69
70. Is it fair?
Is it easy to
understand?
Is it accountable?
So what does it take to trust a decision made by
a machine?
(Other than that it is 99% accurate)?
Did anyone
tamper with it?
#21, #32, #93
#21, #32, #93
72. Is it fair?
Is it easy to
understand?
Is it accountable?
Did anyone
tamper with it?
FAIRNESS EXPLAINABILITY
ROBUSTNESS
LINEAGE
Our vision for Trusted AI
Pillars of trust, woven into the lifecycle of an AI application
75. Join: https://callforcode.org/
75
This multi-year global initiative rallies developers to create practical, effective, and high-quality applications based on cloud, data, and artificial
intelligence that can have an immediate and lasting impact on humanitarian issues. Call for Code brings startup, academic, and enterprise developers
together and inspires them to solve the most pressing societal issues of our time - for example, faster and more resilient recovery from natural disasters.
76. In conclusion…
Situation
Competence
3 R’s
On Ramps
1. Platform & ecosystem competition for data and AI workloads
2. However, AI is hard; many capabilities 2-4 decades away
3. Industry in open source collaboration-competition mode
1. Read: Learn state-of-art
2. Redo: Apply and infuse in use cases/workloads
3. Report: Share back, others may improve
1. LF AI Landscape: Community projects
2. IBM CODAIT: Cloud Pak for Data (CPD), etc. – Enterprise workloads with Trusted AI
3. Red Hat ODH: OpenShift – Hybrid cloud platform and ecosystem
78. IBM’s Service Journey: A Summary Sketch
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Spohrer J (2017 ) IBM's service journey: A summary sketch. Industrial Marketing Management. 60:167-172.
79. Trust: Two Communities
1/29/2021 IBM Code #OpenTechAI 79
Service
Science
Artificial
Intelligence
Trust:
Value Co-Creation
Responsible Entity Collaborators
Transdisciplinary Community
Trust:
Secure, Fair, Explainable
Machine Collaborators
Open Source Communities
Special Issue
AI Magazine?
Handbook of
OpenTech AI?
80. Today’s Talk:
• Title: Future of AI and Post-Pandemic Society: A
Service Science Perspective
Abstract: The 2020 pandemic is accelerating the
digital (information technologies)
transformation of society, including online
working, learning, playing and belonging. The
future of AI will bring even greater acceleration
and transformations. Service science predicts
that in this transformation of business and
society that competing for collaborators will
increasingly shape value co-creation interactions
and capability co-elevation outcomes between
entities in the coming decades. A decade-based
(2020-2080) view of IT, AI, society, and service
science is provided.
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Consumers and society at large are expecting
more from business. Embracing those
responsibilities can be good for shareholders, too.
81. Outline
1. The pandemic is accelerating digital transformation – platform society and T-shaped (l)earners.
2. Service science perspective – transformation (collaborate with people/responsible entities)
3. Artificial intelligence perspective – automation (collaborate with machines)
4. Philosophical question: What do we do ourselves and what can we safely delegate in win-win games? Build vs buy.
82. Accelerating shift - from employees to earners in
platform society
Farrrel D, Grieg F (2014)
Online Platform
Economy.
83. Upskilling…
T-shapes (l)earners…
on multiple platforms
Rodgers S (2016) Jeremiah
Owyang on the Collaborative
Economy.
Kenny M, Zysman J (2016) The
Rise of the Platform Economy.
85. 1/29/2021 (c) IBM MAP COG .| 85
T-shaped Adaptive Innovator: Deep Problem-Solving and Broad Communication/Collaboration
Advanced Tech: AI to IoT to Quantum, GreenTech, RegTech, etc.
Work Practices: Agile, Service Design, Open Source
Mindset: Growth Mindset, Positive Mindset, Entrepreneurial
Many disciplines
Many sectors
Many regions/cultures
(understanding & communications)
Deep
in
one
sector
Deep
in
one
region/culture
Deep
in
one
discipline
86. References – Post-pandemic world
• Autor D, Mindell D, Reynolds E (2020). The Work of the Future: Building Better Jobs in an Age of Intelligent Machines. MIT Work of the Future Task Force. URL:
https://workofthefuture.mit.edu/wp-content/uploads/2020/11/2020-Final-Report.pdf
• Farrel D, Grieg F (2014) Online Platform Economy. JP Morgan Chase. URL: https://www.jpmorganchase.com/institute/research/labor-markets/jpmc-institute-
online-platform-econ-brief
• Gardner P, Maietta HN (2020) Advancing Talent Development: Steps Toward a T-Model Infused Undergraduate Education. Business Expert Press. URL:
https://www.amazon.com/Advancing-Talent-Development-Undergraduate-Education/dp/1951527062
• Hunt V, Simpson B, Yamada Y (2020) The case for stakeholder capitalism. McKinsey Report. URL: https://www.mckinsey.com/business-functions/strategy-and-
corporate-finance/our-insights/the-case-for-stakeholder-capitalism
• ILO (2017) Helping the gig economy work better for gig workers. URL: https://www.ilo.org/washington/WCMS_642303/lang--en/index.htm
• Kenny M, Zysman J (2016) The Rise of the Platform Economy. Issues in Science and Technology. Vol. XXXII, No. 3, Spring 2016. URL: https://issues.org/the-rise-of-
the-platform-economy
• Moghaddam Y, Demirkan H, Spohrer J (2018) T-Shaped Professionals: Adaptive Innovators. Business Expert Press. URL: https://www.amazon.com/T-Shaped-
Professionals-Innovators-Yassi-Moghaddam/dp/194784315X
• Rodgers S (2016) Jeremiah Owyang on the Collaborative Economy. Dassault Systemes – Navigate the Future. URL: https://blogs.3ds.com/northamerica/jeremiah-
owyang-on-the-collaborative-economy/
• Sapjic DJ (2019) The Future of Employment –30 Telling Gig Economy Statistics. Small Business by the Numbers. URL: https://www.smallbizgenius.net/by-the-
numbers/gig-economy-statistics/#gref
• Spohrer JC (2011) On looking into Vargo and Lusch's concept of generic actors in markets, or “It's all B2B… and beyond!”. Industrial Marketing Management.
2011;2(40):199-201.
• Spohrer J (2017) IBM's service journey: A summary sketch. Industrial Marketing Management. 2017 Jan 1;60:167-72.
• Spohrer J, Kwan SK, Fisk RP. (2014) ”Marketing: A Service Science and Arts Perspective”. In Roland T. Rust and Ming-Hui Huang Handbook of Service Marketing
Research (489-526). [Competing for collaborators is the constant across time]
• Torpey E, Hogan A (2016) Working in a gig economy. USA Bureau of Labor Statistics. URL: https://www.bls.gov/careeroutlook/2016/article/mobile/what-is-the-
gig-economy.htm
• Van Dijck J, Poell T, De Waal M (2018) The platform society: Public values in a connective world. Oxford University Press. [book review]
• WEF (2017) Towards a reskilling revolution - a future of jobs for all. URL: http://www3.weforum.org/docs/WEF_FOW_Reskilling_Revolution.pdf
87. 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.
26-30 July 2015 3rd International Conference on The Human Side of Service Engineering
87
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)
88. Future of Service Science
Smarter and Wiser Service Systems:
Entities transform to better future versions of
themselves by inventing win-win games and competing
for collaborators
Past Present Future
Organizational
Units
Family
Local Clan
Family
Business/Nation
Family
Platform Society
Change Individual
Generalist
(Breadth)
Individual
Specialist
(Depth)
Individual
T-shaped
(L)earners
Constant Competing for
collaborators:
win-win games
Competing for
collaborators:
win-win games
Competing for
collaborators:
win-win games
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90. (c) IBM MAP COG .| 90
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)