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Hicss52 20190108 v3

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HICSS52 Workshop on AI and Skills for Future. Hawaiian International Conference on Systems Sciences

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Hicss52 20190108 v3

  1. 1. HICSS-52 Workshops Jim from IBM (Jim Spohrer) Director, IBM DBG/DEG, Measuring AI Progress Cognitive Opentech Group (MAP COG) See also: IBM Developer and Center for Opensource Data and AI Technologies (CODAIT) HICSS-52 Workshops, Maui, HI, USA, January 8, 2019 https://www.slideshare.net/spohrer/hicss52-20190108-v2 1/8/2019 (c) IBM MAP COG .| 1
  2. 2. 1/8/2019 (c) IBM MAP COG .| 2 Microsoft acquiring GitHub $7.5B 2018 John Marks on Open Source Models will run the world Why SW is eating the world Mega-Trend: Open Source AI
  3. 3. Trust: Two Communities 1/8/2019 IBM Code #OpenTechAI 3 Service Science OpenTech AI Trust: Value Co-Creation, Transdisciplinary Trust: Ethical, Safe, Explainable, Open Communities Special Issue AI Magazine? Handbook of OpenTech AI?
  4. 4. Smartphones pass entrance exams? When? 1/8/2019 (c) IBM 2017, Cognitive Opentech Group 4 … when will your smartphone be able to take and pass any online course? And then be your coach, so you can pass too?
  5. 5. 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 51/8/2019 (c) IBM 2017, Cognitive Opentech Group 2080204020001960 $1K $1M $1B $1T 206020201980 +/- 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 Rouse WB & Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 1-21.
  6. 6. Timeline: GDP/Employee 1/8/2019 (c) IBM 2017, Cognitive Opentech Group 6 (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 Rouse WB & Spohrer JC (2018) Automating versus augmenting intelligence. Journal of Enterprise Transformation, 1-21.
  7. 7. Timeline: Leaderboards FrameworkAI 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) 2015 2018 2021 2024 2027 2030 2033 2036 1/8/2019 (c) IBM 2017, Cognitive Opentech Group 7 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level ->
  8. 8. Courses • 2015 • “How to build a cognitive system for Q&A task.” • 9 months to 40% question answering accuracy • 1-2 years for 90% accuracy, which questions to reject • 2025 • “How to use a cognitive system to be a better professional X.” • Tools to build a student level Q&A from textbook in 1 week • 2035 • “How to use your cognitive mediator to build a startup.” • Tools to build faculty level Q&A for textbook in one day • Cognitive mediator knows a person better than they know themselves • 2055 • “How to manage your workforce of digital workers.” • Most people have 100 digital workers. 1/8/2019 8 Take free online cognitive classes today at cognitiveclass.ai
  9. 9. “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
  10. 10. Resilience: Rapidly Rebuilding From Scratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. 1/8/2019 IBM Code #OpenTechAI 10
  11. 11. 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. 1/8/2019 IBM Code #OpenTechAI 11
  12. 12. 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. 1/8/2019 IBM Code #OpenTechAI 12
  13. 13. 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." 1/8/2019 IBM Code #OpenTechAI 13
  14. 14. 10 million minutes of experience 1/8/2019 Understanding Cognitive Systems 14
  15. 15. 2 million minutes of experience 1/8/2019 Understanding Cognitive Systems 15
  16. 16. 1/8/2019 16 1955 1975 1995 2015 2035 2055 Better Building Blocks
  17. 17. Future-Ready T-Shapes 1/8/2019 © IBM UPWard 2016 17
  18. 18. 1/8/2019 (c) IBM MAP COG .| 18
  19. 19. Who is winning 1/8/2019 (c) IBM 2017, Cognitive Opentech Group 19 https://www.technologyreview.com/s/608112/who-is-winning-the-ai-race/
  20. 20. 1/8/2019 (c) IBM MAP COG .| 20
  21. 21. Questions • What is the timeline for solving AI and IA? • 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? 1/8/2019 (c) IBM 2017, Cognitive Opentech Group 21
  22. 22. Hardware < Software < Data < Experience < Transformation 1/8/2019 Understanding Cognitive Systems 22 Value migrates to transformation – becoming our future selves; people, businesses, nations = service system entities Pine & Gilmore (1999) Transformation Roy et al (2006) Data Osati (2014) Experience Life Log
  23. 23. 1/8/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 23 I have… Have you noticed how the building blocks just keep getting better?
  24. 24. AI Fairness 360 1/8/2019 (c) IBM MAP COG .| 24
  25. 25. 1/8/2019 IBM Code #OpenTechAI 25
  26. 26. Step Comment GitHub Get an account and read the guide Learn 3 R's - Read, Redo, Report Read (Medium/arXiv), Redo (GitHub), Report (Jupyter Notebook) Kaggle Compete in a Kaggle competition Leaderboards Compete to advance AI progress Figure Eight Generate a set of labeled data (also Mechanical Turk) Design New Challenges build an AI system that can take and pass any online course, then switch to tutor-mode and help you pass Open Source Guide Establish open source culture in your organization 1/8/2019 IBM Code #OpenTechAI 26
  27. 27. By 2035, T-Shaped Makers with great Building Blocks and Cognitive Mediators 1/8/2019 27 Empathy & Teamwork sector region/culture discipline Depth Breadth STEM Liberal Arts
  28. 28. 1/8/2019 (c) IBM MAP COG .| 28
  29. 29. 1/8/2019 (c) IBM MAP COG .| 29 Join the for free and get monthly newsletter from the International Society of Service Innovation Professionals. Membership based non-profit professional association promoting people-centered smart service systems Fostering professional thought leadership of members through joint conferences, workshops, publications, members mentorship, and awards globally Catalyzing and elevating industry-academia- government collaboration in cutting edge research, best industry practices, innovative educational models, and policy influencing Join us: www.issip.org Members: 1200 +  ~200 universities  50 + companies  42 + countries Founders:
  30. 30. 1/8/2019 (c) IBM MAP COG .| 30
  31. 31. In Summary 1/8/2019 © IBM 2015, IBM Upward University Programs Worldwide accelerating regional development 31 “A service science perspective considers the evolving ecology of service system entities, their value co-creation and capability co-elevation interactions, and their capabilities, constraints, rights, and responsibilities.” Cognitive Systems Entities Service Systems Entities With Cognitive Mediators Add Rights & Responsibilities
  32. 32. Annual ISSIP Award 1/8/2019 (c) IBM MAP COG .| 32
  33. 33. Agenda: Go to HICSS.org 1/8/2019 (c) IBM MAP COG .| 33
  34. 34. Skills Partnership 1/8/2019 (c) IBM MAP COG .| 34
  35. 35. AI & Digital Service 1/8/2019 (c) IBM MAP COG .| 35
  36. 36. AI & Future of Work 1/8/2019 (c) IBM MAP COG .| 36
  37. 37. AI & Bias 1/8/2019 (c) IBM MAP COG .| 37
  38. 38. HICSS-52 Workshop: AI & Jobs/Skills • The Mega-Trend: Open source AI is a mega-trend, e.g., https://developer.ibm.com/blogs/2018/12/12/open-source-ibm-and-ai/ • Can everyone become an entrepreneur? Three laws of Robo-Economics - Freeman RB (2018) Ownership when AI robots do more of the work and earn more of the income. Journal of Participation and Employee Ownership. (2018 Jun 11). 1(1):74-95. . • See also Ng ICL (2018a) Mimicking firms: Future of work and theory of the firm in a digital age. See: https://warwick.academia.edu/IreneNg • Ng ICL (2018b) The market for person-controlled personal data with the Hub-of-allThings (HAT). Working Paper. Coventry: Warwick Manufacturing Group. WMG Service Systems Research Group Working Paper Series (01/18) http://wrap.warwick.ac.uk/101708/ DOI 10.13140/ RG.2.2.20917.78561 • Probably not, but everyone can be part of an entrepreneurial household/family Are farmers entrepreneurs? Will biological abundance be replaced by digital abundance – seems likely that everyone will eventually have 100 digital workers. See http://service- science.info/archives/5021 • Why Important? The ”Working Hypothesis” by Oren Cass: e.g. https://www.amazon.com/Once-Future-Worker- Renewal-America-ebook/dp/B079617VFZ 1/8/2019 (c) IBM MAP COG .| 38
  39. 39. HICSS-52 Workshop: AI & Bias • The Mega-Trend: Open source AI is a mega-trend, including for ethics, e.g., https://developer.ibm.com/blogs/2018/12/12/open-source-ibm-and-ai/ • Your Help Needed: Your help – and your data are needed – please consider participating in open source communities working on the challenge of AI and Bias, e.g. https://github.com/IBM/AIF360 (also see Linux Foundation Deep Learning work in this area – https://github.com/LFDLFoundation/presentations/blob/master/LFDL-Overview-12132018.pdf) • Related Areas: Remember, there are many adjacent open source communities for adversarial attacks, explanation, etc., e.g, https://github.com/IBM/adversarial-robustness-toolbox and https://github.com/marcotcr/lime • Why Important? One of the biggest benefits of AI may be persuading us all to be more ethical beings as we understand the historic origins and source of our biases in complex decision-making that work against us and our species in the world of today, read Harari’s “Sapiens” https://www.amazon.com/Sapiens-Humankind-Yuval-Noah-Harari/dp/0062316095 1/8/2019 (c) IBM MAP COG .| 39
  40. 40. AI & Skills 1/8/2019 (c) IBM MAP COG .| 40
  41. 41. 1/8/2019 (c) IBM MAP COG .| 41
  42. 42. Computer Science as Empirical Inquiry: Symbols and Search • "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… A physical symbol system is a machine that produces through time an evolving collection of symbol structures. Such a system exists in a world of objects wider than just these symbolic expressions themselves. ” • 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 1/8/2019 (c) IBM MAP COG .| 42
  43. 43. 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.1/8/2019 (c) IBM MAP COG .| 43
  44. 44. 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).1/8/2019 (c) IBM MAP COG .| 44
  45. 45. Service Science the study of service system entities 1/8/2019 (c) IBM MAP COG .| 45 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
  46. 46. Service Science the study of service system entities 1/8/2019 (c) IBM MAP COG .| 46 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.
  47. 47. Service Science the study of service system entities 1/8/2019 (c) IBM MAP COG .| 47 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.
  48. 48. Service Science the study of service system entities 1/8/2019 (c) IBM MAP COG .| 48 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.
  49. 49. Service Science: Conceptual Framework 1/8/2019 (c) IBM MAP COG .| 49
  50. 50. 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. 1/8/2019 IBM #OpenTechAI 50
  51. 51. Disciplines and some of the key entities they study 1/8/2019 (c) IBM MAP COG .| 51 Computer Science: Physical Symbol System Entities AI: Digital Cognitive System Entities Chemistry: Auto-Catalytic Molecular System Entities Biology: Biological Cognitive System Entities Service science: 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.
  52. 52. 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. 1/8/2019 (c) IBM MAP COG .| 52
  53. 53. 1/8/2019 IBM Code #OpenTechAI 53

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