Human and Machine Intelligence: Implications for the future of education

Transcription

1 Human and Machine Intelligence: Implications for the future of education

2 Gallman & Weiss, 1969 Kendrick, 1961 BEA, 2010

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5 Knowledge is a pattern of connections New knowledge builds on (relates to) what is already known Innovation requires openness for new connection forming, new creations, new mashups

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7 a thousand threads that lead from the locomotive to the very beginning of the modern world Rosen, 2010

8 Wheels Steam Motion Viability Transportation need Scientific progress Entrepreneurship Metal workers: cylinders

9 The process may be more like stitching together known parts than pioneering a complete route from scratch W. Bryan Arthur, 2006

10 in order for us to truly create and contribute to the world, we have to be able to connect countless dots, to cross-pollinate ideas from a wealth of disciplines, to combine and recombine these pieces and build new castles. Maria Popova

11 Humanity in transition Digital, networked, never-forget knowledge Blurring lines between systems and roles created in physical space Separation from what matters Economic churn: Elites, North South, West East, UBI Rise of attention to ancient wisdom/contemplative literature

12 Humanity s largest (last?) creation A global data skin, an exoskeleton, an ecology

13 IoT Mobiles Ocean sensors Environmental monitoring Satellites Social media

14 AI/ML/DL AI: the science and engineering of making intelligent machines (McCarthy, 1956) - General (human) - Narrow (specific to a task such as chess) ML: the ability to learn without being explicitly programmed (Samual, 1959) NN/DL: layers in a neural network, shares attributes of human brain

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16 However, for some problems this human knowledge may be too expensive, too unreliable or simply unavailable. As a result, a long-standing ambition of AI research is to bypass this step, creating algorithms that achieve superhuman performance in the most challenging domains with no human input. AlphaGo Zero

17 China s social credit system Rewards and punishment for behavior Access to hotels, jobs, schools, even dating sites

18 "I feel like in the past six months, people s behaviour has gotten better and better. For example, when we drive, now we always stop in front of crosswalks. If you don t stop, you will lose your points. At first, we just worried about losing points, but now we got used to it. (BI, 2018)

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20 Infant humans didn t only regurgitate; they created, made new meaning, shared feelings He had discovered that human learning was communal and interactive. For a robot, the acquisition of language was abstract and formulaic. For us, it was embodied, emotive, subjective, quivering with life. Guardian, 2018

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22 What will AI do for education? Automate mundane activities Tutors/chatbots/student support Improve communication Higher quality contextual feedback Personalized and adaptive learning Learner profiles (personal learning graphs) Social network expansion Content and resource exploration

23 What does it mean to be human in a digital age?

24 The adjacent possible Co-evolution with the environment Everything is moving faster pick faster, push harder

25 We are disconnected from what matters We are teaching an increasingly in conflict with new technological capability part of ourselves.

26 Ages of Humanity Physical Mental Being: this is our new research domain. This is the future of socio-technical and wellbeing research,

27 We face a knowing problem The challenge of the ephemeral and the impact of ambiguity on human psyche Render our world sensible and our actions within it meaningful

28 AI/HI integration Distributed technological cognition: human and technological agents. Society s techno-social systems are becoming ever fasters and more computer-oriented can generate a new behavioral regime as humans lose the ability to intervene in real time Johnson et al., 2013 (Nature)

29 Now facing a world of human/machine distributed cognition The algorithms and robots are part of our cognitive system

30 Shift to being attributes

31 Technology creates problems that only more technology can solve

32 There is a growing cry for help from graduate students across the globe who struggle with significant mental health concerns Graduate students are more than six times as likely to experience depression and anxiety as compared to general population Evans et. Al, 2018 (Nature)

33 We are teaching an increasingly in conflict with new technological capability part of ourselves.

34 Eudaimonia

35 Positive psychology scientific study of what goes right in life, from birth to death and all stops in between Peterson, 2006

36 Happiness index OECD Empathic schools

37 "The traditional scientific method, which is based on analysis, isolation, and the gathering of complete information about a phenomenon, is incapable to deal with such complex interdependencies. Heylighen et al, 2007

38 Two cultures: An intellectual or a scientific lens on the emerging focus on wellbeing C.P. Snow, 1959

39 The atom of learning?

40 Quine web of belief

41 Observations Inferred Beliefs Deepseated Beliefs Source: Jklagg, VT

42 Traditional science is iterative See by looking back

43 Science as usual is fine, it s needed But it s not going to embrace the opportunity before us

44 Networks rather than science as usual

45 Why? Speed of change Stable systems aren t accommodating of new approaches Need for impact on social systems Criticality of wellbeing in cycles of dramatic transition Integrative nature of being

46 Knowledge generation: moving to networks Then Now Self-contained monolith Networked (Boeing 787) Centralized Built for stability Efficiency as goal Globally networked Agility Flexibility $$ profit Multiple-bottom lines focus Employ for life Employ for need

47 Time for a new approach Need to urgently explore the human-artificial intelligence nexus Interest in new attributes for business success (multiple bottom lines) Computational advances that require humans to shift contributions Development of PS as a field and revival of contemplative/being practices through a scientific lens

48 Holistic change is possible Merging science with vision/architecting a future HAI: a distributed cognitive system

49 Change Systems of systems Granularity of integration and granularity of impact Learn from traditional systems of meaning and contemplative practices

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52 Need for sensemaking It s not access to information that defines our needs today. It is more complex making sense and acting sensibly

53 Knowledge development, learning, is (should be) concerned with learners understanding relationships, not simply memorizing facts. i.e. naming nodes is low level knowledge activity, understanding node connectivity, and implications of changes in network structure, consists of deeper, coherent, learning

54 Exploration Learning is the exploration of the unknown not just mastery of what is already known.

55 Compelling Questions Habitable Worlds: Are We Alone? Contagion: Can We Survive?

56 Geology Astronomy Physics Chemistry Biology Transdisciplinary The questions we care about don t fit in silos

57 Smart Courses

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