In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
From artificially intelligent systems towards real thinking tools and human s...Jorn Bettin
Ā
From artificially intelligent systems towards real thinking tools and human scale models that improve both human and machine learning
--
In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
--------------------------------------
Jorn Bettin is a Partner at S23M and loves building and working with high-performance teams. Jorn works with top-level subject matter experts and transdisciplinary teams to uncover and activate deep domain knowledge.
Jorn has a background in mathematics and his experience covers the following industries: logistics, industrial automation, healthcare, insurance, banking, legal and accounting, telecommunications, electricity, and government.
S23Mās MODA + MODE thinking tools complement Kaizen and agile techniques, enabling people and software systems to interact in the simplest possible way. MODA + MODE techniques create bridges of understanding between disciplines and organisational silos.
Jorn is passionate about open innovation and about addressing challenges that go beyond the established framework of research in industry, government and academia via the quarterly CIIC unconference. He is a co-author of a number of books on model driven product line engineering, is an expert on semantic interoperability, and has worked in methodology leadership roles at IBM in the 1990s.
Jorn is also part of Autistic Collaboration ā a mutual support hub for neurodivergent individuals and ventures, and advises clients on the creation of inclusive cultures of innovation and knowledge sharing.
Some critics may have you believe that computer game studies lack theoretical rigor, that games cannot afford meaningful experiences. I agree with them, sometimes, but I also believe that a richer understanding of computer games is possible, and that this understanding can shed some light on related issues in the wider field of Digital Humanities.
My main area of research has been designing and evaluating how contextually appropriate interaction can aid the understanding of cultures distant in time, space, and in understanding to our own. This field is sometimes called Virtual Heritage. In Virtual Heritage, tools of choice are typically virtual reality environments, and the projects are very large in scale, complexity, and cost, while my projects are often prototypes and experimental designs. I have many challenges, for example, morphing technological constraints into cultural affordances, and avoiding possible confusion between artistic artifice and historical accuracy, all the while evaluating intangible concepts in a systematic way without disturbing the participantsā sense of immersion. To help me judge the success or failure of these projects I have shaped some working definitions of games, culture, cultural understanding, cultural inhabitation, and place. However, these concepts and definitions are not enough. I also have to now tackle the issues of simulated violence, artificial āotherā people, the temptation of entertainment masquerading as education, and the difficulties inherent in virtually evoking a sense of ritual.
My lecture, then, is a discussion into how game-based learning, and the study of culture, heritage and history, might meaningfully intersect.
Micah Allen: Zombies or Cyborgs: Is Facebook eating your brain?Seismonaut
Ā
Micah Allen er hjerneforsker og PhD studerende pĆ„ Ć rhus Universitet. Her fortƦller han om sociale mediers indflydelse pĆ„ hjernen til Headstart Morgenseminar d. 17. marts 2010.
This lecture uncovers a hidden literacy in the way we think about nature in cyberspace. Why are there so many nature metaphors ā clouds, rivers, streams, viruses, and bugs ā in the language of the internet? Why do we adorn our screens with exotic images of forests, waterfalls, animals and beaches? In her new book āTechnobiophilia: Nature and Cyberspaceā, Sue Thomas interrogates the prevalence online of nature-derived metaphors and imagery and come to a surprising conclusion. The root of this trend, she believes, lies in biophilia, defined by biologist E.O. Wilson as āthe innate attraction to life and lifelike processesā. In this lecture, which marks the US launch of the book, she explores the strong thread of biophilia which runs through our online lives, a phenomenon she calls ātechnobiophiliaā, or, the āinnate attraction to life and lifelike processes as they appear in technologyā. The restorative qualities of biophilia can alleviate mental fatigue and enhance our capacity for directed attention, soothing our connected minds and easing our relationship with computers. More information at www.suethomas.net
This lecture was part of a series of Fall guest lectures exploring the intriguing new concept of metaliteracy developed by Tom Mackey and Trudi Jacobson, and it was presented live in the new Metaliteracy MOOC. The MOOC is open to students at the University at Albany and Empire State College for credit as well as to all global participants as a free and open learning experience. http://metaliteracy.cdlprojects.com/index.html
From artificially intelligent systems towards real thinking tools and human s...Jorn Bettin
Ā
From artificially intelligent systems towards real thinking tools and human scale models that improve both human and machine learning
--
In an increasingly software and data-intensive human world, the objective of human-scale computing is to improve filtering, collaboration, thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This objective is another way of stating the goal of developing a 'language and interaction style' that is better than any formal or informal language reliant on linear syntax.
--------------------------------------
Jorn Bettin is a Partner at S23M and loves building and working with high-performance teams. Jorn works with top-level subject matter experts and transdisciplinary teams to uncover and activate deep domain knowledge.
Jorn has a background in mathematics and his experience covers the following industries: logistics, industrial automation, healthcare, insurance, banking, legal and accounting, telecommunications, electricity, and government.
S23Mās MODA + MODE thinking tools complement Kaizen and agile techniques, enabling people and software systems to interact in the simplest possible way. MODA + MODE techniques create bridges of understanding between disciplines and organisational silos.
Jorn is passionate about open innovation and about addressing challenges that go beyond the established framework of research in industry, government and academia via the quarterly CIIC unconference. He is a co-author of a number of books on model driven product line engineering, is an expert on semantic interoperability, and has worked in methodology leadership roles at IBM in the 1990s.
Jorn is also part of Autistic Collaboration ā a mutual support hub for neurodivergent individuals and ventures, and advises clients on the creation of inclusive cultures of innovation and knowledge sharing.
Some critics may have you believe that computer game studies lack theoretical rigor, that games cannot afford meaningful experiences. I agree with them, sometimes, but I also believe that a richer understanding of computer games is possible, and that this understanding can shed some light on related issues in the wider field of Digital Humanities.
My main area of research has been designing and evaluating how contextually appropriate interaction can aid the understanding of cultures distant in time, space, and in understanding to our own. This field is sometimes called Virtual Heritage. In Virtual Heritage, tools of choice are typically virtual reality environments, and the projects are very large in scale, complexity, and cost, while my projects are often prototypes and experimental designs. I have many challenges, for example, morphing technological constraints into cultural affordances, and avoiding possible confusion between artistic artifice and historical accuracy, all the while evaluating intangible concepts in a systematic way without disturbing the participantsā sense of immersion. To help me judge the success or failure of these projects I have shaped some working definitions of games, culture, cultural understanding, cultural inhabitation, and place. However, these concepts and definitions are not enough. I also have to now tackle the issues of simulated violence, artificial āotherā people, the temptation of entertainment masquerading as education, and the difficulties inherent in virtually evoking a sense of ritual.
My lecture, then, is a discussion into how game-based learning, and the study of culture, heritage and history, might meaningfully intersect.
Micah Allen: Zombies or Cyborgs: Is Facebook eating your brain?Seismonaut
Ā
Micah Allen er hjerneforsker og PhD studerende pĆ„ Ć rhus Universitet. Her fortƦller han om sociale mediers indflydelse pĆ„ hjernen til Headstart Morgenseminar d. 17. marts 2010.
This lecture uncovers a hidden literacy in the way we think about nature in cyberspace. Why are there so many nature metaphors ā clouds, rivers, streams, viruses, and bugs ā in the language of the internet? Why do we adorn our screens with exotic images of forests, waterfalls, animals and beaches? In her new book āTechnobiophilia: Nature and Cyberspaceā, Sue Thomas interrogates the prevalence online of nature-derived metaphors and imagery and come to a surprising conclusion. The root of this trend, she believes, lies in biophilia, defined by biologist E.O. Wilson as āthe innate attraction to life and lifelike processesā. In this lecture, which marks the US launch of the book, she explores the strong thread of biophilia which runs through our online lives, a phenomenon she calls ātechnobiophiliaā, or, the āinnate attraction to life and lifelike processes as they appear in technologyā. The restorative qualities of biophilia can alleviate mental fatigue and enhance our capacity for directed attention, soothing our connected minds and easing our relationship with computers. More information at www.suethomas.net
This lecture was part of a series of Fall guest lectures exploring the intriguing new concept of metaliteracy developed by Tom Mackey and Trudi Jacobson, and it was presented live in the new Metaliteracy MOOC. The MOOC is open to students at the University at Albany and Empire State College for credit as well as to all global participants as a free and open learning experience. http://metaliteracy.cdlprojects.com/index.html
Pamela Rutledge: The Wired Child - Impact of Social TechnologiesPamela Rutledge
Ā
Lecture given at the American Museum of Natural History as part of their series on "The Wired Child: The Impact of Technology on the Brain."
The focus was on the positive psychology of social technologies and how that influences the sense of individual and collective agency and self-efficacy.
"What got us here, wont get us there!" Pirelli july 2014 Mebs Loghdey
Ā
I have developed and delivered two fresh and interesting sessions for Hyper Island, Unilever, Mercer and Pirelli. These sessions were developed as a response the Innovation and Sustainability imperatives faced by most managers.
Entitled "What got us here won't get us there!", this sessions teach managers about
1. Language, metaphor and reframing
2. Q-storming - designing powerful questions
3. Systems thinking
Managers leave these sessions better equipped to engage a future that is at once digital, mobile, social, green and data rich.
it describes ethnomethodology as a method as well as a theory. This very concise and precise presentation helps one to understand the real meaning of ethnomethodology.
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Ā
In this special issue, we present a synthesis of work that consolidates what is currently known and provides a platform for
future research. Consequently, we include both new empirical
studies and novel theoretical proposals describing work with both human children and adults and a range of nonhuman animals. In this introduction, we describe the background of this special issue and provide a context for each of the eight articles it contains. We hope such introduction will not only help the reader synthesize the interdisciplinary views that characterize this broad field, but also stimulate development of new methods, concepts, and data.
Ignoring Nature No More: The New Work of Social Sciences in Collaboration Res...Global Risk Forum GRFDavos
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Plenary V: Social Challenges and Opportunities for Effective One Health Governance
Philip TEDESCHI, Professor, Executive Director, Institute for Human-Animal Connection, University of Denver, Denver, USA
Do Intelligent Machines, Natural or Artificial, Really Need Emotions?Aaron Sloman
Ā
(Updated on 14 Jan 2014 -- with substantial revisions.)
Many people believe that emotions are required for intelligence. I argue that this is mostly based on (a) wishful thinking and (b) a failure adequately to analyse the variety of types of affective states and processes that can arise in different sorts of architectures produced by biological evolution or required for artificial systems. This work is a development of ideas presented by Herbert Simon in the 1960s in his 'Motivational and emotional controls of cognition'.
Religious Tolerance In India Essays ā Telegraph. Write a paragraph on āNeed of Religious tolerance in Indiaā in 150 .... Religious Tolerance in India; A Data analysis - YouTube. (PDF) The Impact of Social Media on Religious Tolerance in India A Case .... Religious Toleration in Mughal India - Owlcation. (PDF) Theory and praxis of religious tolerance. Religion In India Tolerance And Segregation Universal News - kulturaupice. Pin on Are You Ready For "CHANGE". Hinduism and Religious Tolerance. How India thinks about religious tolerance and diversity | IDR. Bestessayservices.com: Sample Anthropology Essay on Religious Tolerance. Religious Tolerance ā keefbook. Religious Tolerance | Teaching Resources. Religious Tolerance and Intolerance in India. India: Growing Intolerance and Hate Toward Religious Minorities .... Religion & Tolerance: India Pluralistic, But Divided ā The Dispatch. Religious Violence in india Essay Example | Topics and Well Written .... Essay Writing on RELIGIOUS TOLERANCE-New Speech Essay Topic. Religious Tolerance: Living In Peace To Avoid Living In Pieces, By .... Religious Tolerance in Islam | Al-Islam.org. Tolerance and Other Religions. Religious tolerance in India deteriorating: US lawmakers told. ļø Essay on tolerance in hindi. Essay about Religious Tolerance. 2019-02-28. Religious tolerance in India deteriorated in 2015: US report | Latest .... A Historical Analysis of Religious Tolerance | NewsClick. (DOC) Religious tolerance, the news media and respect for the theist .... (PDF) Cultural and Religious Tolerance in Islam. Pin on sociology in india. ā« Religious Tolerance in Guyana Free Essay Sample on Samploon.com. Ontario Consultants On Religious Tolerance Free Essay Example. 'In India, religious tolerance is deteriorating' - Rediff.com India News. Interfaith Religious Tolerance isnāt good enough in India | Vedic Tribe. Religious Tolerance and Hindu Rituals Assignment. A lesson in religious tolerance from ancient India | Letters | The Guardian. Religious Tolerance in Ancient India Religious Tolerance In India Essays
We gathered community leaders and a remarkable diversity of storytellers, to use the "collective story harvest" method as a way to practice listening across differences. Part of the 2018 Pittsburgh Inclusive Innovation Week. A blog post describing the workshop in more detail is here: http://www.fitassociates.com/blog/listening-to-difference
From collective insanity to organisational learning 2019 03 11 brisbane bus...Jorn Bettin
Ā
From collective insanity to organisational learning, by caring about the health of feedback loops at all levels of scale and all the places where they are needed. The talk will address the question of how, when, and why feedback loops may fail or get corrupted, and will explore how feedback loops relate to the creation of learning organisations and the design of better products and services.
From collective insanity to organisational learningJorn Bettin
Ā
āØFrom collective insanity to organisational learning, by caring about the health of feedback loops at all levels of scale
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From artificially intelligent systems towards real thinking tools and human scale models that improve both human and machine learning 2018 06 20
1. Collaboration for Life
From artificially intelligent systems towards āØ
Real Thinking Tools and Human Scale Models āØ
that improve both human and machine learning
Jorn Bettin
Auckland AI and Machine Learning Meetup, June 2018
2. Collaboration for Life
What is learning?
to learn : Gain or acquire knowledge of or skill in something by study, experience,
or being taught. Commit to memory. Become aware of something by
information or from observation.
Learning takes place at different levels of spatial and temporal scale:
ā¢ Individual bacteria, species of bacteria
ā¢ Individual plants, species of plants,
ā¢ Individual animals including humans, species of animals
ā¢ Social groups of animals from one species āØ
(in particular social insects and humans)
ā¢ Mixed groups of living creatures āØ
(from microbiomes to ecosystems and the planet)
ā¢ Individual software agents created by humans
ā¢ Social groups of software agents created by humans
ā¢ Mixed groups of human and software agents
expressed genes
genome
genetic diversity
chemical gradients
neural networks
cultural knowledge
experimental data
models
competency networks
3. Collaboration for Life
Individual contributions to the creation of learning systems
kin āØ
group
ecosystem
planet
individual āØ
agent
resources, knowledge, offspring
maintenance,āØ
resources
physical forces, āØ
physical resources
changes in physical, chemical, āØ
and biological processes
resources and learning opportunities
resources, knowledge, mates
social group
maintenance,āØ
resources
resources, knowledge
maintenance, āØ
resources
resources, āØ
knowledge
changes in āØ
ecosystem function
interactions
& flows
4. Collaboration for Life
Human contributions to the creation of learning systems
categoryāØ
of agent
techno-socialāØ
ecosystem
planet
human orāØ
software āØ
agent
resources, knowledge, evolution
maintenance,āØ
resources
physical forces, āØ
physical resources
changes in physical, chemical, āØ
and biological processes
resources and learning opportunities
resources, knowledge, collaborators
organisation
maintenance,āØ
resources
resources, knowledge
maintenance, āØ
resources
resources, āØ
knowledge
changes in āØ
system function
value
creation
activities
interactions
& flows
6. Collaboration for Life
Imitation, understanding, creativity
Useful working definitions:
ā¢ Imitation : Ability to replicate behaviour. āØ
Probabilistic reasoning, resulting in know how. (billions of years ago)
ā¢ Basic understanding : Ability to answer why questions. āØ
Causal reasoning, resulting in know why. (180,000 years ago)
ā¢ Creativity : Ability to ask new questions. āØ
Counterfactual semantic reasoning, āØ
pushing the boundaries of understanding. (50,000 years ago)
culturalāØ
evolution
genetic
evolution
8. Collaboration for Life
The atoms of the ālanguageā of thought
Human mental models have been around for much longer than human language.
Here is a synopsis of the thinking tools that predate human language:
ā¢ Shared attention (awareness that another animal is looking at the same thing)
ā¢ Pointing (based on having limbs)
ā¢ Mental representations ( = models) of the things we interact with
ā¢ Categories ( = mental models of groups of similar things)
ā¢ Containment and connectors (spatial relationships between things = graphs)
ā¢ Operations (mental models of patterns of movements and changes over time)
ā¢ Simulations (to predict events and arrive at decisions)
9. Collaboration for Life
Achieving shared understanding
Prior to spoken or written language communication via shared attention and pointing was the
was way of establishing shared understanding, and such shared understanding related to very
down-to-earth representations. Pre-language humans communicated within a highly local
context in space and time. The things being referenced were āclose at handā. It was reasonable
for people to assume that others understood what they referred to. The risks for
misunderstandings were limited.
Spoken language entered our world as a serialisation format for communicating simple
references to things within our local context. We started to reference abstract things,
references to references, and experiences that occurred many years ago. The number of
misunderstandings in communication grew exponentially. Since people could not visit the past
of other people, this lead humans down the path of extensive social delusion, where they
started to assume that they understood each other much better than they actually did. The
seeds for storytelling had been sowed. The first human hive minds emerged.
Written language made things worse in terms of the scope of social delusion. People had
opportunities to āreadā large volumes of information out of context in space and time. People
started importing many thousands of references to very unfamiliar abstractions into their
mental models on top of their first hand experiences. The human tendency to believe in the
validity of our imagination after hearing or reading a story allowed storytelling and belief systems
to rise to new heights. A few people started scratching their heads about weird human
behaviours and the beliefs that underpinned the observed behaviours.
10. Collaboration for Life
Exponential change in communication
- 1,800,000 years: Cumulative cultural transmission, teaching, imitation, experimentation
- 200,000 years : Spoken human languages ā local communication of tacit knowledge
- 5,400 years : Written human languages ā communication across time, explicit knowledge
- 600 years : Printing press ā 1-to-many communication across space, scale
- 180 years : Electrical telegraph & telephone ā global peer-to-peer communication, on demand
- 15 years : Internet ā global 1-to-many communication, zero marginal cost, dirt cheap
- Now : Internet of things ā machine-to-machine communication, new technologies every monthāØ
apps
time
2 million years of gene culture co-evolution
11. Collaboration for Life
The case for science and reason as forcesāØ
for steady and measurable human progress
Steven Pinker
ā¢ The Better Angels of Our Nature: Why Violence Has Declined, 2011
ā¢ Enlightenment Now, 2018
12. Collaboration for Life
And yet: Dysfunctional feedback loops
family
capitalised busynesslocal environment
government
local community
planet
individual
demands
busyness & āØ
consumption
lack of attention
capitalised bank
demands
busyness & āØ
consumption
does not meet
human needs
impaired ecosystem
functions
climate
change
lack of attention
waste
sells need
for busyness
demands
attention
legitimises
generates the debtāØ
that fuels busyness
waste
lack of attention
does not meet
human needs
stressed
primary externalities
secondary externalities
13. Collaboration for Life
Gamification of society
ā¢ Paul Babiak and Robert Hare, Snakes in
suits: When psychopaths go to work, 2006
ā¢ Susan Long, The perverse organisation
and its deadly sins, 2008
ā¢ Susan Long, Socioanalytic methods ā
Discovering the hidden in organisations
and social systems, 2013
ā¢ The Milgram experiment https://
www.youtube.com/watch?v=8g1MJeHYlE0
ā¢ The Stanford prison experiment https://
www.youtube.com/watch?v=sZwfNs1pqG0
ā¢ The Asch conformity experiment https://
www.youtube.com/watch?v=TYIh4MkcfJA
psychopathic traits are common in the upper echelons of the corporate world, with a prevalence of between 3% and 21%
Nathan Brooks, http://www.psychology.org.au/news/media_releases/13September2016/Brooks, 2016
neurotypical
copying
social games
innovation
psychopathic
lack of empathy
weak
neurological traits
derived/aggregate behaviours
selfish intent
collaborative intent
14. Collaboration for Life
Bullshit jobs make up a big part of the Big Data āeconomyā
Working Definition: a bullshit job is a form of paid
employment that is so completely pointless,
unnecessary, or pernicious that even the employee
cannot justify its existence even though, as part of
the conditions of employment, the employee feels
obliged to pretend that this is not the case.
Those who work bullshit jobs are often surrounded by
honor and prestige; they are respected as
professionals, well paid, and treated as high achievers
āas the sort of people who can be justly proud of what
they do. Yet secretly they are aware that they have
achieved nothing; they feel they have done nothing to
earn the consumer toys with which they fill their lives;
they feel itās all based on a lieāas, indeed, it is.
David Graeber, Bullshit Jobs: A Theory, 2018
80%
BS
40%
BS
15. Collaboration for Life
Popularity = The economy of ālikesā (Douglas Rushkoff)
https://youtu.be/6_n1Dro0Uec
narcissistic
behaviour
cultural
rituals
neurotypical
copying
social games
hierarchies
psychopathic
lack of empathy
neurological traits
derived/aggregate behaviours
selfish intent
collaborative intent
You gonna travel
anywhere this summer?
16. Collaboration for Life
The future of management
A good assessment of the speed of progress over the last 50 years by a colleague in the UK: āØ
Old Is the New New https://youtu.be/AbgsfeGvg3E
17. Collaboration for Life
Technology
All human artefacts are technology. But beware of anybody who uses this term. āØ
Like āmaturityā and ārealityā and āprogressā, the word ātechnologyā āØ
has an agenda for your behaviour: usually what is being referred to as āØ
ātechnologyā is something that somebody wants you to submit to.
āTechnologyā often implicitly refers to something you are expected to turn over to
āthe guys who understand it.ā This is actually almost always a political move.
Somebody wants you to give certain things to them to design and decide. āØ
Perhaps you should, but perhaps not.āØ
āØ
ā Ted Nelson,āØ
Pioneer of information technology, āØ
philosopher, and sociologist. āØ
He coined the terms hypertext āØ
and hypermedia in 1963.
18. Collaboration for Life
We have perverted the definition of intelligent behaviourāØ
ability to deceive others = āintelligent behaviourā
George Soros developed the theory of reflexivity based on the ideas of Karl Popper. Reflexivity
posited that market values are often driven by the fallible ideas of participants, not only by
the economic fundamentals of the situation. Reflexive feedback loops are created where ideas
influence events and events influence ideas. Soros further argued that this leads to markets
having procyclical "virtuous or vicious" cycles of boom and bust, in contrast to the
equilibrium predictions of more standard neoclassical economics."āØ
āØ
http://www.tandfonline.com/doi/abs/10.1080/1350178X.2013.859415
ideas
events psychopathic
lack of empathy
(social games)
19. Collaboration for Life
The resulting spurious cultural complexity is also known as guard labour
Guard labor is wage labor and other activities that are said to maintain (hence "guard") a capitalist system. Things that
are generally characterised as guard labor include: management, guards, military personnel, and prisoners. āØ
āØ
Guard labor is noteworthy because it captures expenditures based on mistrust and does not produce future value.
Guard labour is an increasingly common form of busyness, the term was coined by āØ
Arjun Jayadev and Samuel Bowles https://en.wikipedia.org/wiki/Guard_labor
fear busyness
21. Collaboration for Life
Intelligent behaviour : finding and operating a niche in the living world
dead alive
sick at āworkā chores
the arts and other autistic pursuits
collaborative play and learning
sports
How about a better definition of intelligence?
24. Collaboration for Life
Human scale cognition and sense making
We argue that conceptual blending is responsible for the origins of
language, art, religion, science, and other singular human feats, and that it
is indispensable for basic everyday thought as it is for artistic and scientific
abilitiesā¦
People pretend, imitate, lie, fantasise, deceive, delude, consider
alternatives, simulate, make models, and pose hypotheses. Our
species has an extraordinary ability to operate mentally on the unreal
ā¦
Because linguistic expressions prompt for meanings rather than represent
meanings, linguistic systems do not have to be, and in fact cannot be,
analogues of conceptual systems. Prompting for meaning construction is a
job they can do; representing meanings is notā¦
Vital relations, which include Cause-Effect, Change, Time, Identity,
Intentionality, Representation, and Part-Whole, not only apply across
mental spaces, but also define essential topology within mental spaces.
One of the overarching goals of compression through conceptual
blending is to achieve āhuman scaleā in the blended spaceā¦
2002
A brilliant book on the cognitive foundations of human scale conceptual semantic modelling
26. Collaboration for Life
Creativity = Having a āless well functioning mental bureaucratā (*)
Neurodivergent people:
ā¢ Adhere to idiosyncratic moral value
systems rather than social norms
ā¢ Are okay with exploring ideas that upset
the āsocial orderā
ā¢ Spend much more time experimenting
and implementing ideas that others
would consider crazy or a waste of time
ā¢ Have untypical life goals: new forms of
understanding, making a positive impact,
translating ideas into artistic expression
Autists in particular tend to:
ā¢ Easily suffer from sensory and social
overload
ā¢ Have unusually developed pattern
recognition abilities
ā¢ Have an unusual ability to persevere
(*) Jeffrey Baumgartner
autistic
perseverance
autistic
hypersensitivity
autistic pattern
recognition
neurodivergent
creativity
autistic
authenticity
individual
autistic rituals
invention
innovation
neurological traits
derived/aggregate behaviours
27. Collaboration for Life
The Two Traits of the Best Problem-Solving Teams:
Cognitive Diversity and Psychological Safety
HBR
autisticāØ
collaboration
absence
of
neurodiversity
29. Collaboration for Life
Imitation, basic understanding, creativity
Most animals, as well as present-day learning machines,
are on the first rung, learn to imitate via associative /
probabilistic reasoning.
Tool users, such as early humans, are on the second rung if
they act by scenario planning / causal reasoning and not
merely by imitation. They use experiments to gain a basic
understanding of the effects of interventions.
Counterfactual learners, on the top rung, can imagine and
understand worlds that do not exist and infer reasons for
observed phenomena via blending of semantic / vital
relationships.
Pearl, Judea; Mackenzie, Dana. The Book of Why: The New
Science of Cause and Effect
30. Collaboration for Life
The state of machine learning
The state of the art in artificial intelligence today is merely a souped-up
version of what machines could already do a generation ago: find hidden
regularities in a large set of data.
Deep learning works for certain tasks. But it is the antithesis of
transparency. ā¦
Yes, we forgive our meager understanding of how human brains work, but
we can still communicate with other humans, learn from them, instruct
them, and motivate them in our own native language of cause and effect.
We can do that because our brains work the same way.
If our robots will all be as opaque as AlphaGo, we will not be able to
hold a meaningful conversation with them, and that would be quite
unfortunate. ā¦
Transparency enables effective communication.
Pearl, Judea; Mackenzie, Dana. The Book of Why: The New Science of
Cause and Effect
31. Collaboration for Life
Neglecting human scale
We have used linear syntax programming languages to cobble together many thousands of software
systems by trial and error that no one understands anymore.
ā¦ and now we are in the process of cobbling together machine learning systems by trial and error
that produce correlation maps that are devoid of explanatory power.
On the implications:
1. Are you a model builder or a storyteller?āØ
https://jornbettin.com/2017/08/22/are-you-a-model-builder-or-a-story-teller/
2. Designing filtering, collaboration, thinking, and learning tools for the next 200 yearsāØ
https://ciic.s23m.com/2017/04/25/designing-filtering-collaboration-thinking-and-learning-tools-
for-the-next-200-years/
3. The antidote to misuse of mathematics and junk dataāØ
https://jornbettin.com/2015/04/
4. Ending the curse of software maintenanceāØ
https://the-software-artefact.blogspot.com/2011/05/ending-curse-of-software-maintenance.html
5. Fatal software errorsāØ
https://jornbettin.com/2011/04/23/fatal-software-errors/
32. Collaboration for Life
Human scale machine learning
We have to equip machines with a model of the environment. If a machine does not
have a model of reality, you cannot expect the machine to behave intelligently in that reality. āØ
āØ
The first step, one that will take place in maybe 10 years, is that conceptual models
of reality will be programmed by humans. The next step will be that machines will
postulate such models on their own and will verify and refine them based on
empirical evidence.
That is what happened to science; we started with a geocentric model, with circles and
epicycles, and ended up with a heliocentric model with its ellipses.
https://www.quantamagazine.org/to-build-truly-intelligent-machines-teach-them-cause-and-
effect-20180515/
https://www.quantamagazine.org/the-math-of-causation-puzzle-20180530/
33. Collaboration for Life
The objective of human scale computing
ā¦ is to improve filtering, collaboration,
thinking, and learning:
1. between humans,
2. between humans and software systems,
3. and between software systems.
This will require equipping artificial human-
scale agents with our individual motivations /
value systems.
We will need to think about hard and soft wired
cognitive lenses and about hard wired and soft
wired values and norms.
35. Collaboration for Life
Modern mathematics is human scale
At all times throughout human history a few people would have realised that human
language has severe limitations in terms of ambiguity and precision.
Given the limitations of human languages, it is perhaps not entirely surprising that
modern foundations of mathematics take us back to core concepts that pre-date
human language ā to the atoms of the language of thought:
ā¢ Model theory expresses the biological foundations of human mental models in
a formal symbol system.
ā¢ Denotational semantics is based on the simple observation that we can
abstract human understandable symbol systems into corresponding machine
readable symbol systems.
ā¢ Category theory is a thinking tool for articulating large scale patterns and
establishing semantic equivalences between different domains, it does not
involve any concrete symbol systems. We perform such semantic calculations
in our minds all the time, mostly subconsciously.
36. Collaboration for Life
Abstract math is useful? What is category theory?
Applied category theory: https://forum.azimuthproject.org/discussion/2105/lecture-28-chapter-2-ignoring-externalities/p1
See also AI is harder than you think: https://www.nytimes.com/2018/05/18/opinion/artificial-intelligence-challenges.html
37. Collaboration for Life
Tapping into the visual processing capacity āØ
of the human brain
The brainās capacity for processing visual data is
around 20 times higher than the brainās capacity for
processing audio data.
Even with simple technologies such as whiteboards and
markers it is possible to design and use highly expressive
and unambiguous visual languages that are much easier
for humans to parse and understand than information in a
linear format (audio or text).
MODA+MODE therefore makes extensive use of visual
languages and provides guidance for developing
further domain specific visual languages.
38. Collaboration for Life
play, learn, observe, question, imagine
a language for
describing
value creation
a language for
describingāØ
motivations
a language for
describing
interactions
The human lens
to make sense of the world and the natural environment from a human perspective,āØ
to evolve our value systems, and to structure and optimise human activities
Thinking Tools for Interdisciplinary Research, Design, and EngineeringāØ
https://coininco.files.wordpress.com/2017/08/moda-and-mode-lenses-and-principles.pdf
system
lens
semantic
lens
logistic
lens
39. Collaboration for Life
design / engineering
transportation /
communication
quality / maintenance
energy / foodāØ
production
culture
value creation
human artefactshuman symbols
critical self-reļ¬ection
nature
human societies
motivations
resourcesevents
agents
interactions
The human lens definesāØ
categories that are invariant across cultures, space, and time
learn
play
observe
question
imagine
system
lens
semantic
lens
logistic
lens
40. Collaboration for Life
Human scale computing can be understood as the
elaboration of the role of cognitive characteristics of
humans within ergonomics.
Systems, models and technologies are only
understandable as long as they do not generate
cognitive loads that exceed human cognitive
limits.
This observation can only be put to good use if human
cognitive limits become a primary concern in the
design of human institutions and technologies, in much
the same way that human scale physical dimensions
and characteristics have shaped the discipline of
ergonomics.
Developing visual languages and interaction styles āØ
that are better than English or any other linear language
41. Collaboration for Life
Designing tools for the next 200 years
It is time for creating a visual language and interaction style that is better than English or any
other linear language:
1. for validating and representing knowledge
ā¢ in a way that is intuitive and easily understandable for humans
ā¢ in a way that is easy for processing by software tools
2. for validating and representing knowledge flows
ā¢ between individual agents/teams/organisations/communities
ā¢ in a way that facilities collaborative validation of knowledge and beliefs
ā¢ as a substrate for interdisciplinary innovation and the creation of context specific variants
3. for filtering, validating, and representing economic flows
ā¢ supports domain specific accounting of all kinds of knowledge flows
ā¢ using Culture, Engineering, Maintenance, Energy, and Transportation as the basic sectors
for modelling economic value cycles
ā¢ with explicit tools that assist with the detection of deception
1. https://ciic.s23m.com/2017/04/25/designing-filtering-collaboration-thinking-and-learning-tools-for-the-next-200-years/
2. https://ciic.s23m.com/2017/08/30/addiction-and-story-withdrawal/
3. http://s23m.com/about/index.html ā Contact jorn.bettin@s23m.com for related PhD research opportunities
42. Collaboration for Life
Language is a very powerful thinking tool
Language frames people's thoughts and emotional response. āØ
Time to start consistently talking about concepts that can improve our lives:
1. Niche construction and symbiosis rather than competition āØ
ā to create organisations and products that are fit for purpose and valued by
the wider community
2. Company rather than business ā to focus on the people and things we care
about rather than what is simply keeping us busy
3. Values rather than value ā to avoid continuously discounting what is priceless
4. Physical waste rather than wealth ā to focus us on the metrics that do matter
5. Human scale and progress rather than large scale and growth ā to create
structures and systems that are understandable and relatable
6. Competency networks rather than leadership ā to get things done and
distribute decision making to where the knowledge resides
7. Coordination rather than management āØ
ā to address all the stuff that can increasingly be automated, management is
often the biggest obstacle to automation
8. Creativity and divergent thinking rather than best practices āØ
ā when facing the need to innovate and improve
46. Collaboration for Life
Validation via instantiation (or āconcretisationā)
Golf
ABC 123
instantiate
abstract
Observation: We need less speculation and
much more validation via instantiation !
instantiate
47. Collaboration for Life
6 Questions
Investigating decision making processes that occur when applying knowledge:
ā¢ When and how often does a decision require revision? ā Events and frequency
ā¢ Who arrives at the decision? ā Agents
ā¢ Why is the decision made? ā Purpose (which agents benefit?)
ā¢ Where (or in which information artefact) is the decision made? ā Location
ā¢ What are the possible choices? ā Limits of understanding
ā¢ How is the decision made? ā Heuristics
to surface tacit knowledge about systems
48. Collaboration for Life
MODA + MODE backbone principles for āØ
creating learning organisations and understandable systems
26 principles that provide āØ
a meta paradigm to avoid āØ
getting entrapped in a paradigm
MODA + MODE thinking tools for interdisciplinary research, design, and engineering: āØ
https://coininco.files.wordpress.com/2017/08/moda-and-mode-lenses-and-principles.pdf
50. Collaboration for Life
The fundamental axiom of values for the knowledge age
A metric either
measures a physical quantity, āØ
and can serve as a measure of constraints that a group of people cares aboutāØ
XOR
is an abstract non-scalable approximation āØ
of values that a small group of people cares about
51. Collaboration for Life
Improvements and innovation
All effective approaches for continuous improvement (such as
Kaizen, Toyota Production System, Waigaya, ā¦) and innovation
(Open Space, collaborative design, ā¦) share one common principle.
In order to successfully identify and implement opportunities for improvement and innovation āØ
the belief in the existence and relevance of social hierarchies must be suspended
Why is this the case? What does this tell us about society?
52. Collaboration for Life
The effect of hierarchical structures on innovation
1. Any form of hierarchy indicates a dampened
feedback loop.
2. Power is the privilege of not needing to learn.
3. A hierarchical organisation is the anti-
thesis of a learning organisation.
54. Collaboration for Life
Competency networks
Definition: A competency network is the graph of experience-based pair-
wise trustworthiness ratings in relation to various domains between the
members of a group.
Trustworthiness ratings are tied to specific pairs of individuals; they are not
directly transferable and they can not easily be aggregated. This limitation
probably was one of the key reasons for the small size of pre-historic hunter-
gatherer societies.
The notion of competency networks is inspired by the correlation between
software system structures and the communication patterns between human
software developers observed by Mel Conway in 1967:
Any organization that designs a system (defined broadly) will produce a
design whose structure is a copy of the organization's communication
structure. http://melconway.com/Home/Conways_Law.html
55. Collaboration for Life
Prosocial core design principles @ S23M
āØ
āØ
Tailored Core Design Principles:
1. Trusted relationships within the group and strong understanding of purpose
2. Fair distribution of costs and benefits
3. Fair and inclusive decision-making
4. Fast and empathetic conflict resolution
5. Authority to self-govern
6. Appropriate relations with other groups
7. Tracking agreed upon behaviours
8. Graduated responses to transgressions āØ
to prevent a person or a subgroup from āØ
gaining power over others
A working advice process
minimises the need for tracking
Fair and inclusive distribution
of resources minimises the
need for coercion
Supports an open and inclusive
neurodiverse & creative team
Applying evolutionary science to coordinate action, avoid disruptive
behaviours among group members, and cultivate appropriate
relationships with other groups in a multi-group ecosystem āØ
(the work of Elinor Ostrom, Michael Cox and David Sloan Wilson)
56. Collaboration for Life
Thinking in systems, designs, patterns
the team the tools
We distil knowledge and enable knowledge to flow to all
the places where it can be put to good use for the world
57. Collaboration for Life
The MODA + MODE approach has a fractal characteristic that enables
it to operate at all levels of scale, with explicit support for feedback
loops between different levels of scale:
ā¢ Development of collaboration platforms that improve the resilience
and performance of economic ecosystems.
ā¢ Development of technology platforms that harness deep domain
expertise to streamline the development of new products.
ā¢ Improvements in quality, reliability, and productivity of specific
teams or technological systems.
ā¢ Integrating the knowledge of multiple domain experts in a cross-
disciplinary context to co-create innovative solution designs.
ā¢ Translating tacit knowledge into explicit knowledge that does not
decay over time.
Typical use cases in industry, academia, and government
58. Collaboration for Life
Organisational learning = Cultural evolution
Evolution is triggered by:
1. Formation of a new group
2. Merging of two or more groups of
3. Establishing patterns of regular interactions between two or more groups
4. Splitting a group into two or more groups
5. A new person joining a group
6. A person leaving a group
Future software systems and machine learning systems can evolve in a similar way
ā iff they are modular at human scale
See also https://ciic.s23m.com/2018/06/13/creating-human-scale-learning-organisations/
59. Collaboration for Life
Coordination across levels of scale
Definitions of living systems and cultural constructions from large to small:
1. Planet ā Biodiversity and level of resilience of the planetary ecosystem
2. Government and companies ā Coordination of human activities and
state of the environment at a macro / regional level
3. Local community ā Coordination of human activities and resource use at
a local level
4. Local environment ā State of the environment at a local level
5. Family ā Coordination of human activities and resource use between kin
6. Individual ā Individual activities and resource use
60. Collaboration for Life
Individual contributions to the creation of learning systems
family
local environment
planet
individualmental support
maintain ināØ
a healthy state
diversity => resilience
monitor andāØ
start to understand
resources and learning opportunities
economic coordination
local community
maintain ināØ
a healthy state
attention
attention
attention
we know what to
do and measure
value
creation
activities
61. Collaboration for Life
Thank you!
Jorn BettināØ
jorn.bettin@s23m.com
Nothing beats capturing the knowledge flow
of leading domain experts to co-create
organisations & systems that are
understandable by future generations of
humans & software tools.
63. Collaboration for Life
The MODA + MODE backbone ā principles 1 to 8
# MODA + MODE principle
motivations motivations motivations motivations motivations
critical self-
reļ¬ection
human
societies
human symbols
human
artefacts
nature
1
Understand that minorities and outsiders are well positioned
for uncovering attempts of deception
addressing
corruption
honesty
2
Give minorities and outsiders access to private means of
communication
development of
new theories
equality
3 Operate transparent governance access to evidence trust
4
Adapt the cognitive load generated by technology to human
cognitive limits
understandability
ease of
communication,
happiness
simplicity usability
5
Recognise neurological differences as authentic and valuable
sources of innovative potential
discovery of
externalities
resilience,
happiness
resilience
6
Value metrics from the physical and biological world more than
human opinions
minimise human
bias
minimise cultural
bias
7 Value local perspectives more than widely-held popular beliefs learning
collaboration
between groups,
happiness
8
Value the strength of shared beliefs and corresponding
evidence more than the number of shared beliefs
trust, happiness trust, happiness
64. Collaboration for Life
The MODA + MODE backbone ā principles 9 to 20
# MODA + MODE principle
motivations motivations motivations motivations motivations
critical self-
reļ¬ection
human societies human symbols human artefacts nature
9 Use information quality logic to minimise ambiguity
shared understanding,
precision
quantiļ¬cation of
knowledge
10 Use probabilistic reasoning to acknowledge uncertainty
honesty, risk
assessment
quantiļ¬cation of risk quality management
11 Conduct commonality and variability analysis
collaboration,
simplicity, agility
simplicity usability
12 Formalise the results of commonality and variability analysis
shared understanding,
resilience
sharing, automation automation
13
Develop visual domain speciļ¬c languages to describe familiar
domains in unambiguous terms
shared understanding,
precision
simplicity,
understandability
quality of design,
manufacturing, recycling
14
Understand that all information is dependent on perspective and
viewpoint
diversity usability, ļ¬tness for purpose
15 Understand that a multitude of perspectives generates new insights learning, resilience innovation
16
Validate shared understanding by sharing of models and
corresponding instances
shared understanding,
evidence
quality of design,
manufacturing, recycling
17 Understand that power gradients stand in the way of transformation
courage,
transformation
reduction of externalities
18 Aim for optimal conļ¬ict in a supportive and trusting team environment agility, learning
quality of design,
manufacturing, recycling
19
Use agile experiments when venturing into unfamiliar domains to
learn from mistakes
experiments, learning
quality of design,
manufacturing, recycling
20
Conduct an adequate number of experiments in different contexts to
minimise risk before global application of major changes
caution minimisation of externalities
65. Collaboration for Life
The MODA + MODE backbone ā principles 21 to 26
# MODA + MODE principle
motivations motivations motivations motivations motivations
critical self-
reļ¬ection
human
societies
human
symbols
human artefacts nature
21
Understand that collaboration occurs to the extent
that there is shared understanding
shared
expectations
design of value cycles evolution of ecosystems
22
Recognise paradoxes and disagreements as the
essence of continuous improvement
evolution
continuous improvement of
design, manufacturing,
recycling
evolution
23
Practice everyday improvement, everybody
improvement, everywhere improvement
continuous
parallel
evolution
continuous improvement of
design, manufacturing,
recycling
continuous parallel
evolution
24 Engage in niche construction
diversity,
resilience,
happiness
resilience in design,
manufacturing, recycling
biodiversity, resilience
25 Use feedback loops to create learning systems
learning
systems
speed of innovation
codes, cell chemistry,
recursion, neural networks
26
Use modular decentralised design to promote
reuse without compromising resilience
simplicity,
resilience
resilience in design,
manufacturing, recycling
cells, organs, organisms,
species, ecosystems
A culture may have further bones, but one or moreāØ
missing vertebrae severely compromise capability
66. Collaboration for Life
play, learn, observe, question, imagine
Scientists, Engineers, Entrepreneurs, Artists & Mathematicians
CIIC brings together academic researchers and practitioners every 3 months āØ
to tackle wicked problems that donāt have an obvious solution.
Challenges that Go Beyond the
Established Framework of Research in
Industry, Government and Academia
Conference on Interdisciplinary
Innovation and Collaboration
https://ciic.s23m.com/
67. Collaboration for Life
Conference on Interdisciplinary
Innovation and Collaboration
CIIC workshop results (https://ciic.s23m.com/expected-results/):
ā¢ March 2018 ā Topics at the intersection of agriculture and healthcare
ā¢ December 2017 ā Design of interaction patterns for knowledge validation and trust building
ā¢ September 2017 ā Interaction and collaboration of humans and intelligent machines
ā¢ June 2017 ā Human scale computing
ā¢ March 2017 ā Neurodiversity
ā¢ December 2016 ā Making information interactive
ā¢ September 2016 ā The potential and limits of clinical decision support systems
ā¢ March 2016 ā Design and development of tools for effective self-care
ā¢ December 2015 ā Is there a place for barter?
ā¢ September 2015 ā How do we need to redefine economic progress? What is value?
ā¢ June 2015 ā Growing New Zealandās contribution to a sustainable world
68. Collaboration for Life
ā¢ Allows knowledge to ļ¬ourish in the open creative spaces between disciplines and organisational silos
ā¢ Complements the typical yearly cycle of domain-speciļ¬c conferences
ā¢ Has a quarterly cycle and feedback loop between teams that supports āØ
on-going and longer-term collaborations more effectively than yearly events
ā¢ Captures knowledge ļ¬ows and transdisciplinary insights in reusable semantic models and patterns
ā¢ Currently runs in Auckland at AUT and in Melbourne at RMIT, āØ
and the CIIC community is available to assist with replicating the concept in other locations
ā¢ Can help coordinate collaboration between locations via the CIIC Web site and related online tools
ā¢ Invites further co-sponsors from industry, academia, and government
ā¢ Is an antidote to bureaucratic limitations; large organisation are now inquiring about establishing
regular in-house CIIC style events
ā¢ Provides a safe environment for neurodivergent / autistic people to connect and collaborate
CIIC invites communities and economic ecosystems āØ
to sharpen their collaborative edge by embracing open innovation.
Conference on Interdisciplinary
Innovation and Collaboration
https://ciic.s23m.com/about/
69. Collaboration for Life
AUT ā Auckland University of Technology
MODA + MODE is being integrated into the āØ
curriculum on entrepreneurial strategies, creative technologies, āØ
and methodologies for trans-disciplinary research and collaboration