“Conversation about Cybernetics” | Joi Ito, Paul Pangaro | MIT Media Lab | Mar 17, 2016 (web video)

Conversation at the MIT Media Lab about cybernetics with Paul Pangaro, Nathan Felde, Mike Bove, Iyad Rahwan, Edith Ackermann, Joi Ito and Lorrie LeJeune.

A few background posts:

jods.mitpress.mit.edu/pub/designandscience
dubberly.com/articles/cybernetics-and-counterculture.html

Chat posted live on Facebook Mentions at facebook.com/joiito/videos/961545600598042/

Conversation at the MIT Media Lab about cybernetics with Paul Pangaro | Joi Ito | March 18, 2016 at joi.ito.com/weblog/2016/03/18/conversation-at.html

[Warning: the audio recording level on Youtube is low. An audio amplifier will be helpful for listening]

[00:00 Introductions]

[….]

[09:45 As we started to think about the future of Media Lab … and the Media Lab has recently been getting into machine learning, synthetic biology, and other complex adaptive systems. If we go back to the roots of Media Lab, there were some roots of cybernetics there, but for a while a lot of our focus is on computer-human interface and things that were a little more objects. And then we started to get into networks, and systems. But now, we’re shifting into a lot of the hard sciences in self-adaptive complex systems.

[10:30] And then, as I looked at people like Kevin Esvelt who has been doing CRISPR gene drive, he thinks much more about how do we think about who should decide, and how should that enter the system, and less about what is the specific technology that is in the gene drive. And there he can see the design across scales, where at each scale you have a complex system that interacts with other systems across scales.

[10:55] As we start to put all of the science together, what we’re realizing is that the traditional disciplinary science rewards a very focused, single object, rather than systems connected. Now, there is systems thinking going on. But also multiple systems across scales. If you look at Ed Boyden’s lab, he’s got about 50 people working — at very interdisciplinary and antidisciplinary — we touch multiple systems, we create tools that look at multiple systems, and we perturb multiple systems.

[11:30] And then we’ve got people like Kevin Slavin who have come in, sort of talking about participatory design. You’re not stuck in traffic, you are traffic. You put that together. We had a conference last year called Knotty Objects, which is about design. We brought Paolo Antonelli and they talked about critical design. One of the things I realized is that there’s critical design, which was a lot about people not doing it, but critiquing it. And then we had the Media Lab kids who tend to do things, but not being as self-critical as you might want. And they thought more in objects, than systems.

[12:05] So, we were grappling with how do we think about what we were all doing, and how could science be more responsible. We launched this Journal of Design Science, which was to try to break design into science, which means thinking about all of the systems, thinking about things as iterative interventions in an unpredictable complex system, rather than how do I make those predictable things more efficient. Then, how can we change design so it’s less focused on the customer, and more on nature, or the system, across scales.

[12:35] So, as I was searching for the right word to describe what we were doing, I found I was repeating on second order cybernetics.

[12:50] We were having a discussion at the faculty meeting about being interdisciplinary / antidisciplinary. The Media Lab was where all disciplines were brought to work together. Well, there actually was a thing called cybernetics where all of the discipline had come together in the Macy Conference, where was this wonderful moment where it felt like we were going to go transdisciplinary. But, sort of in retrospect, somehow it disappeared.

[13:12] So, how did it disappear, where did it go? Stewart Brand would say “it got bored to death”. Some people said it got too academic, some people said the Macy Conferences ended and disappeared. Some people said the applications got so compelling that it ended up being applied. Theoretical. So there were a lot of reasons why it disappeared.

[13:40] So, I traced someone holding a torch. So now, what I want to explore is a couple things. One is, is there a way to connect cybernetics into what we’re doing in research? Now that I’m turning 50 this year, as an old-timer, I hear the crypto-currency people saying the same things that I was saying back in the 90’s, and making the same mistakes we made when we were building the Internet. I don’t like to repeat mistakes. I don’t like to rehash stuff that’s already been done. So, what can we can learn from cybernetics’ successes? But there are also learning from its failures. What could you or we have done better?

[14:15] We can look at the met-catalyst(?) movement in architecture, which was about bringing biology and architecture together. It was Tungay in Japan that did it. But it kind of died. I think it was because we didn’t have the tools to bring biology into architecture. Today, we do. There are a lot of things, like machine learning, and other things, where the technology has caught up to the theory, so we can apply it.

[14:40] So is it possible that maybe some of the things that we thought about in second-order cybernetics are more relevant and more possible now? [….]

[15:05] So one thing right now that is an argument — a disagreement — at the faculty level is about whether we should grab cybernetics, or not. Shouldn’t we just use the word “design”? Cybernetics comes with a lot of baggage. There a lot of people who are practitioners of cybernetics. When I wrote a little bit about cybernetics, I found some very enlightening comments coming in. But some people who had done stacks of work that seemed a little bit too … like the tools they were using to think about it, they weren’t using the new tools. I didn’t want to diminish what they were doing, and get on their turf, but I didn’t think I could grab the whole lot. [….]

[15:50] Since all of you are in touch with where we are with the Media Lab, or at least you know the DNA of the Media Lab, and you also know the history of cybernetics, I’d love to find — talk about the history of cybernetics, and talk about the forensics of it, and where it is today, and then maybe talk with about how you think it might apply to the future. [….]

[19:00 Paul Pangaro starts the discussion with “what does cybernetics offer”?]

[….]

[59:25] So where is this discussion, now, around, what is the terminology?

[59:30] This has been a useful conversation. We’re launching this idea around — we’re using the words “extended intelligence”, to be what we’re using instead of AI, to talk about this environment. We’re also going to be doing this meeting around AI and governance. And we’ll be launching what it means to put society into the loop.

[1:00:00] In terms of doing, we’re doing. I think a lot of the idea and the words you’re talking about resonate with what we’re thinking. We launched this Journal of Design Science, and are now working on how we describe it. We’re trying very hard — and Stewart has been helpful in thinking about this — to keep it a conversation, rather than be a series of peer-reviewed papers. The way we’re trying to do it is to have a conversation; have the online — we’re using a platform called PubPub that allows versioning and commenting — for the output to also be a reflection of the conversation. […]

[1:00:55] So, we’re moving forward. What would be interesting — talking about cybernetics — would be to learn from cybernetics, and also to see, if you and other people working in cybernetics can take some of the things that we’re working on — like say, machine learning, or evolutionary biology [….]

[1:01:50] The tricky part for me is, how do we have this conversation? I do think that kids don’t read books any more. It’s an ongoing conversation. The words are very fluid. Some of them mean different things to different people. [….]

[1:02:25] The world is much more global, now. Macy was kind of confined, in the cultural context. You talked about the influence of the Austrians. But now we have the impact of everyone. How do we have this conversation across languages?

[1:02:40] To me, that may be the harder thing.

[….]

[1:10:35] So that’s my personal meta place. What is the institution? I look at Bauhaus, I look at Black Mountain, I look at RLE, and all of the other institutions. And for some reason, the Media Lab has sustained over 30 years. I think a lot of it is the approach. [….]

[1:11:00] That could be what we learn about the forensics of cybernetics. [….] Some people had a tremendous amount of impact, but not sustainability. The Media Lab has a weird thing. We like orthogonality and disagreement, we build tools, we’re not obsessed about theory, although we have it, not as a primary output. And then, we’re happy to move along, as new tools come, and new technologies come.

[….]

[1:14:00] I feel like the best designer designs themselves, as the intervention. And, so, it’s me personally, and then the institution. The journal is for us, but I don’t want to create the church. So you have to make the membrane permeable, but humble in that I want to affect myself. In affecting myself, I may affect the environment, in a responsible way … but not to be evangelical about it.

[….]

Tagged with: ,
Posted in Talk Video Streaming

Ian Mitroff | “Dirty Rotten Strategies: How We Trick Ourselves and Others into Solving the Wrong Problems Precisely” | Feb. 24, 2010 | Commonwealth Club (web video, MP3 audio)

Don’t solve the wrong problems precisely.  Type 3 Errors and Type 4 Errors, by Ian Mitroff, extending the Design of Inquiring Systems.

Abstract, from http://www.commonwealthclub.org/events/2010-02-24/dirty-rotten-strategies-how-we-trick-ourselves-and-others-solving-wrong-problems-p

How can people or groups tell whether others are deliberately steering us down faulty paths? Mitroff delves into how organizations and interest groups lure us into solving the “wrong problems” with intricate but inaccurate solutions that are based on faulty and erroneous assumptions – and offers strategies and solutions.

Video of 9m57s (with slides) on “Book TV: Ian Mitroff & Abraham Silvers, Dirty Rotten Strategies” at https://www.youtube.com/watch?v=CjgJVp9f_1k

Video of 59m47s (with slides) on “Book Discussion on Dirty Rotten Strategies” at http://www.c-span.org/video/?292366-1/book-discussion-dirty-rotten-strategies

Audio podcast 1h41s downloadable at http://www.commonwealthclub.org/events/archive/podcast/ian-mitroff-dirty-rotten-strategies-how-we-trick-ourselves-and-others-solving

Preview of book at books.google.com/books?id=9Iol_cctGHkC&printsec=frontcover#v=onepage&q&f=false


[This digest started with the Youtube transcript, and therefore initially uses that time code to 09m57s.  The version on c-span.org has a 14 second header and then runs to 59m47s.]

[00:00] If I had to sum up the the book in a single statement, it would be:  don’t solve the wrong problems precisely, because if you do, it not only a waste of precious resources, time and energy, but it leads to cynicism and despair and puts off the true problem such that they build up into a crisis.

[00:19] Also, if I had to summarize in a in a single saying, it would be from the celebrated author Thomas Pynchon:   if they can get you asking the wrong questions, then they don’t have to worry about the answers.

[….]

[00:40] What’s worse, the wrong solution to the right problem, or, the right solution to the wrong problem?

[00:50] Well, the right solution to the wrong problem is worse, because if you get the “right solution to the wrong problem” you convince yourself that you’ve solved the right problem, and you don’t go back up to the start of the tunnel coming into all of the different branches where you can branch off.

[01:07] You say, I’ve gone down the right path.  But if you keep getting the wrong solution to the right problem you say ok, I’ve made an error and hopefully the error will be self-correcting or I will eventually come to the right solution.

[01:20] Why solve the wrong problem precisely, as I said, a waste of time?

[01:25] In every case, whether you solve the right or wrong problem, it’s due to a set of assumptions.   Solving the wrong problem precisely is due to faulty assumptions, which leads to having to know your assumptions.

[Ally Bank, “Pony”, see http://www.adweek.com/video/ally-bank-pony-121402]

[….]

[03:16] Let me give you an overview of the talk and what’s in the book.   So, we’re gonna talk about something called E3 and E4: Error of the Third Kind, Error of the Fourth Kind.  They’re central to solving the right or the wrong problem.

E3: Trick ourselves; E4: Trick Others

[slide:

E3: Trick Ourselves

E4: Trick Others

]

[….]

[03:54] Let me start with E3 and E4.

[03:56] If you take a course in statistics, just about every courses talks about two types of error, type 1 and type 2 error. Everybody whose taken a course knows about that.

[04:07] And the easiest way to understand it is: you’re a drugmaker.   You have a new drug, and an old drug.   And what you you do you is to go out and test on a sample and hopefully the new drug is better than your old drug.

[04:17] But there are two types of errors you can make.

[04:19] One error is to say the new drug is better than the old drug when it really isn’t.

[04:24] And vice versa, the old drug is better the new drug when it really isn’t.

[04:27] And those are type 1 and type 2 errors.

[04:29] And those have to do with the bell-shaped curve and when you got the right samples.

[04:36] E3 is very different.  Have I tested the right hypothesis to begin with?  Am I asking the right question?

[04:43] So whether it’s the cost or the efficacy of a drug or of health care, it’s how E3 has to do with how we define a problem in the first place.

[04:52] And so E3 is when we trick ourselves.  Not necessarily anybody else, but, we tricked ourselves.  Okay, we fall in love with your pet hypothesis.

[05:00] E4 is more deceptive and potentially more harmful

[05:04]  It’s when I try to convince you, that the formulation that I and my company, my organization or industry has come up [with] is the right formulation of the problem.  And that you ought to accept it.  And there is no other way to formulate the problem.

[05:18] So it’s large fundamentally with miseducation.

[05:22] … in the book …

[slide:

Starts with Mis-education

X + 6 = 11 is an exercise.

Exercises ≠ Problems

Problems ≠ Messes

]

[05:25]  I’m not a proponent of textbooks.  Most of us start learning things from textbooks.  So the first thing we learned was X + 6, for example, equals 11.  What’s X?  That’s not a problem.  It’s an exercise.  The reason why it’s not a problem:  it’s already preformulated  There’s one and only one right answer, but you can usually convert it into a problem.

[05:46] Billy has six dollars and needs eleven dollars to buy a video game.   But Billy is in a poor family.  He has to give his money to help his mother and father.  Then it becomes a problem.

[05:55] Because the context is all-important.  Exercises remove all the context, descriptions.

[06:01] Now the problem with exercises, you give students, you know, 20 or 12 years, whatever it is, and education with exercises.  You turn them into certainty junkies and they balk like mad if you give them a real problem where they have to formulate the problem.

[06:15] In real problems, they have more than one way to formulate.   There’s not just one formulation.

[06:19] So you get into problem negotiation.  But you don’t get that, as you go through typical education.  Exercises don’t equal problems.  And problems don’t equal messes.

[06:30] A mess is a whole system.  A set of problems that are dynamically interconnected and change all the time. This is Russ Ackoff, who died recently, one of my mentors.

[06:40] But managers don’t solve problems, they manage messes.

[06:44] And that’s what President Obama certainly has to do.  It’s not a single well-defined problem, but how all these things are interconnected so the health care problem is not separate from the financial recovery and jobs recovery and all the rest.

[06:57] In fact, if you have a mess, and I’ll show you an example, and you take any the elements or problems out of the mass that constitute it, you distort the problem.   You distort the mess, because you have to look at the interactions.  Problems are not separable.

[07:13]  Health care.  Let me give an example of how we get off and solve the wrong problem.

[slide:

Health Care

Technically, the US has the best Medical System.

But, Technology ≠ Best Health Care System.

US has a poor Sick Care System.

Solves which problem?

]

[07:17] Technically, the U.S. has the best medical system in the world.  No question about that, from a technical standpoint.

[07:24] But technology does not actually equal the best delivery of health care as we want it.

[07:29] They’re not the same.  So solving the medical problem is not the same as solving the health care problem.

[07:36] In fact, the U.S. has a poor sick care system …

[….]

[08:04]  The health care system — and we’ll talk about the current health care bill — is founded on three primary assumptions.  (1) Government is the problem.  (2) Healthcare is a business like any other business.  And (3) cost-cutting is the primary aim.

[slide:

Three Wrong Assumptions

1. Government is the problem

2. Health care is a business

3. Cost-cutting is the primary aim]

[….]

[09:29] Now, it’s not that you have to accept my formulation or my statements.  That’s not the point. But I put my new things, my assertions, strongly as possible, so you know what I’m saying.  If if you disagree, therefore you have hopefully a better clarity on what you agree.

[….]

[Switch to c-span.org timecode]

[10:40 slide] The Critical Role of Critical Assumptions

[10:42] Everything is dependent upon assumptions.

[….]

[10:55] What happens in a crisis in principally this:  It’s not, yteah, that people die, which they do, it costs a lot of money, the organization loses money.

[11:06] One the primary things that happens that most people aren’t aware of:  a crisis literally demolishes all, or nearly all, of the principal assumptions that we use to give meaning to our life, to our reality.  That’s why I give an existential definition to a crisis.

[….]

[11:40 slide

Fort Hood.

1. Enemy

1. Location

1. Mental health professionals

1. One of our own

]

[….]

[11:50] When I listen to crises, I take them in a different way, because I’ve been so tuned to crises for 25 years.  In virtually every case, a crisis  undermines a primary set of beliefs that we use to make sense of reality.  And that’s why they’re existential crises.

[….]

[13:00 slide

Unreality

What's real?

Infotainment

Twittering in Operations

Normalization of the bizarre

]

[…]

[14:40 slide

Knowledge

How can we determine if we are committing an E3 or E4 error?

Inquiry systems]

[….]

[14:50 slide

Way Out

1. Expert Consensus Most Common
2. Scientific Modeling Most Common
3. Multiple Models E3 Assessed
4. Conflict E3 Assessed
5. Systemic E3 Rare

]

[16:40] You can’t really determine whether you’re committing a Type 3 or Type 4 Error, if you’re only using models 1 and 2, the first two ways.  Because they typically only produce one view of a problem, what they take as a “correct one”.

[16:55] It’s only when you get to multiple ways of defining the problem that you can begin to get an handle on “what is truth” or “what is false”.  Otherwise you can’t do it.  Not that it’s perfect.  I’m not saying that.  It’s only when you get to, then, 4 or 5.

[17:10] When you get down to 5, it’s the rarest type of knowledge system of all.  We don’t train people how to think systemically.  And that’s really the only way out of these horrific problems we face.  They can’t be defined by one discipline, one profession.  In fact, when I hear people come up with — boom — one definition of any problem, I want to run like mad, because I know you’ll have to accept their assumption.  It’s very rarely that people make their assumptions clear.

[17:50 Slide

Religion

Solutions to the social problems of 2000-5000 years ago

Rational reasons for God

Not he wrong solution to the wrong problem

]

[….]

[Karen Armstrong, The Case for God; contrary to Richard Dawkins]

[….]

[18:50] In fact, one of the first books I did was, The Subjective Side of Science.  I studied the Apollo moon scientists, not the astronauts.  And if you think a scientist worth his or her salt is going to give up his or her pet hypothesis, particularly for the origin of the moon, just because the first round of rocks are  returned from the moon, you’ve got to be crazy.  They’re going to do everything they can in the world to defend it.  Ultimately, they’re going to give it up.  But only after they’ve defended it to the death.  When I interviewed 42 of the most prestigious scientists, they said that was rational, that a scientist shouldn’t give up his or her pet hypothesis, too soon, lest they give up something worth exploring.

[….]

[20:20 Slide

Way Out?

Messes cannot be managed by the mindsets that created them.

]

[A paraphrase of Albert Einstein]

[….]

[20:50] The fundamental purpose of a university, to me, is to teach critical thinking. Yes, teach technology, and theories, and all the rest of that.  Knowledge.  Of course, all of that is important. But the fundamental job is critical thinking.  And critical thinking involves knowledge of assumptions, to be able to criticize your assumptions, to be able to replace them, to think about alternate assumptions, and to be able to appreciate complex messes, not simple-minded problems, in their entirety.  And to bring to bear on them, multiple ways of looking at them, from multiple disciplines, from multiple points of view.  To say, by looking at the mess, maybe now I have a better idea of which parts of mess I want to concentrate on for the time being.  But in order to know that, I have to see the entire mess.

[21:40] Is there any way to definitely say that you understand the mess fully?  Of course not, it’s a starter.  [….]

[22:10 Slide modified from George Patton

In conclusion:

If everybody is thinking alike, then NOBODY IS thinking"

Mitroff & Silvers

]

[23:25 Questions]

[….]

[24:25 Los Angeles Police Department]

[25:20 Ford Firestone]

[26:10 Toyota]

[26:45 Bill Clinton]

[27:10] What I’ve said to my clients, the people I’ve consulted with, is that if you have only one thing to do in a crisis, my recommendation is: hire an ex-investigative reporter to dig around all of the dirt of the corporation, and make a mock newspaper or a mock tv interview, to show your corporation in the worst light.  Because I can guarantee you that’s what will happen.  Now why doesn’t that happen?  Denial is so powerful.

[28:00 Defence mechanisms]

[29:00 We don’t have learning organizations]

[30:00 Environmental organization.  False choices, that lead to false policies]

[31:00 Five inquiry methods are abstract.  Have turned them into planning methods.  An example: Myers-Briggs Type Indicator. Put all of the people of one personality type into the same group.  When you do that, it intensifies the way of looking.  Ask them to define the problem.  List the major stakeholders that affect or are affected by the solutions, and what assumptions they make.  A systematic way to get a constructive debate]

[32:30  If you can’t get a Myers-Briggs, here’s another way to do it.  One group to argue status quo, whether they believe it or not.  Put people who are in moderate opposition, then more, then radical.  Then list the major stakeholders.]

[33:20 The biggest problem on which I’ve worked.  The U.S. Census Bureau, 1980, 1990.  Undercount.  We set up a week-long debate.]

[34:30 If you have a small organization, could be hard.  Professional management.]

[35:10 More systemic methods.  Where are we cultivating?]

[35:45 Book, in chapter on religion.  Ken Wilbur.  The power of human development.  Once an idea is unleashed, it gains currency, and can take off]

[36:50]  That’s one of the Type 3 errors that I talk about on the chapter on religion.  Here it is: confusing one state of development for the lack thereof in another state.  And that’s one of our principles.  We try to solve problems at one level, by a level one or two steps down, and they can’t be solved.  That’s the whole point.  And that’s why I’m talking about systemic.  Because the problems that we have cannot really be solved, unless, there’s a systemic perspective.  [….]

[37:40] I have to thank my editor at Stanford University Press for taking a radical manuscript, like this, with this kind of a message, to say: the ability to challenge our assumptions, to rethink our assumptions, to think expansively, to think beyond the confines of a single narrow discipline or profession.  That’s the way out.  If we’re mired in one set of assumptions, or one organization, we can’t do it.  [….]

[38:20 15% of organizations can thing proactively, systemically.  85% can’t.]

[38:50 Global warming]

[39:15 Comment. Set up 20% of the time up front, defining the problem.  Then we can work on solving the problem.]

[40.00 Agree.  John Dewey said problems don’t start in disinterest, they start in moral outrage. Wellpoint.]

[40:50 Four steps of scientific problem solving.  1.  Defining the problem.  Conceptual model of the problems.  Broad variables.  Single explanation, no!  Each profession will define differently.  Advanced medical students, psychological students.

[41:50 2.  Build a scientific model.  The first stage is semantic.  The second stage is syntactic].

[42:00 The third stage is to derive a solution, not to the solution, but to the model.]

[42:10 The fourth stage is pragmatic.  Take the solution and see if it solves the problem.]

[42:20 The Type 3, Type 4 errors primarily happen in the first stage, defining the problem wrongly.  If don’t see all of the stages, have defined the problem incorrectly.  Different people focus on different branches.  They don’t see the scientific problem systemically].

[43:20 Initially, doing dialectic doubles the time.  In reality, the more you do it, it doesn’t double the time.  You can’t define one, without the other].

[44:10 Government, messes everywhere.]

[44:25 Broader than that.  Type 3, Type 4 in many areas.  Governments.  Corporations.  Point of strategic planning is not thinking about isolated problems, and to anticipate problems.  Don’t see one as better than others.  General Motors bureaucracy rivals federal government.]

[46:30 Los Angeles Police Department]

[46:40 Salt Lake Winter Olympics.  Problem was Russian ice dancers downgraded.  Didn’t think of all of the crises that could hurt the Olympic committee.  Could show families and grouping of crises.  Not the case that there are not good organizations to learn from.]

[48:30 Ken Wilbur.  Ability to think more complexly.  Challenges are greater.  Hope.]

[49:00 International news 15 minutes every evening, now 24 hour news.  Exacerbates problems?]

[49:40 More is not better.  May not lead to more insightful.  PBS 6 or 10 minutes more insightful.  Facebook and social media hasn’t led to better coverage.  Can now manipulate and merge images.  People can’t tell the difference, don’t care about the difference.  Ally Bank commercial]

[51:10 Michael Vick, football player.  Moral devaluation.  Someone auctioned off notes.  Expect more from the human society.]

[52:30 Media, merging images, real and non-real.  Young people hooked on texting while driving, a problem.  Technologically advanced is not the same as socially advanced.  An engineer, but not solely an engineer.]

[53:50 Tiger Woods.  Got so big, the rules didn’t pertain to him.  The first billion dollar athlete.  Shows had rapidly an icon can crash.  No secrets.  Horrible stitched together videos.  That’s what will happen.  Who will hire someone who will put them in the worst light. Primary thing in crisis:  you don’t own the clock.  The only way to gain control is to fess up, and hopefully the American public will accept it.]

[56:40 Toyota.]

[57:00 Betrayal]

[57:20 Crisis.  You can’t solve the right problem.  Assumptions have a half life, and decay over time.  As circumstances change, your assumptions have to change.   As Ackoff said, plan or be planned for.  Have a real learning organization and a real learning society].

 

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Posted in Talk Audio Download, Talk Video Streaming

“Thank you for being late” | Thomas Friedman | Jan. 2016 | Stockholm Resilience Centre (web video)

Directly after the World Economic Forum, @tomfriedman described his upcoming book “Thank you for being late” in conversation with Johan Rockström at the Stockholm Resilience Centre.

[05:45]  I was deeply influenced a year and a half ago by a book I read called The Second Machine Age by Erik Brynjolfsson and Andy McAfee.  What they argued was that the first machine age was built on the steam engine which doubled in power every seventy years.   But we’re now in the second machine age.  And the second machine age is built on the microchip which, according to Moore’s Law, doubles in power every 24 months.

[7:10] So what I told them was, you guys, I  love your theory, but it’s incomplete as an explanation of the world, because there are two other forces that just entered the second half there of their chessboard at the same time.  They are the other two largest forces on the planet.

[7:26] One is the market — that’s my shorthand for globalization — and the other is mother nature — that’s climate and biodiversity loss.

[17:08] I have three chapters that are interrelated.  The first is about mother nature as mentors and model, which comes out out of biomimicry.   I believe that what we’ve created with our hands now is a system of systems, a network of networks and network of data telecommunications that is more interconnected — hyper-connected — interdependent and complex that it mirrors only one other thing in our experience.   And that’s the natural world.

[41:08] So we actually started the story about Egypt, in Salina, Kansas, in the heart of the wheat belt in America.   I did an interview with Wes Jackson, who is an amazing bioscientist trying to develop a perennial form — a sustainable form — of wheat. And he was explaining to me the prairie.  And said, Tom, you need to understand that the prairie was a natural permaculture.  It was a system that naturally fertilized and pollinated and created its own natural pesticide.  What we did is when we came out here — the white Europeans — we plowed up the prairie and we’ve planted monoculture crops: wheat, corn and sorghum.   And to be sustained they needed massive amounts of high-density fossil fuels in the form of tractors, pesticides and fertilizers.  When the dust bowl happened, all the monoculture crops died.  And all of the prairie survived — the main parts of the prairie — because they’re naturally polycultural resilient, a healthy and good dependent system.

[42:22] And when he said that, I said that’s really interesting, what do think Al Qaeda is doing?  Al Qaeda, in the Middle East, is trying to wipe out the polyculture of the Islamic world.    And the Islamic world was at its most economic and greatest political power, when?  When, Moorish Spain, between the 8th and 13th century, when it was the world’s greatest culture of good, ideas and trade. They’re trying to wipe out Islamist as polyculture and instead — and by the way they’re leveraging high-density fossil fuels from oil states — to wipe out the culture of the Muslim world and replace it with a monoculture that’s enormously susceptible to diseased ideas.

“A conversation with Thomas Friedman” | January 2016 | Stockholm Resilience Center Slow Talk at http://www.stockholmresilience.org/21/research/research-news/1-28-2016-a-conversation-with-thomas-friedman.html

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“Why Societies Collapse” | Joseph Tainter | 2010 | Local Future (web video)

Updating from The Collapse of Complex Societies (1988), Joseph Tainter describes sociopolitical complexity, and “what it means for us”.

The talk mentions colleague Timothy F. H. Allen, but doesn’t surface the idea of complicatedness that appears in their joint publications.

“Why Societies Collapse — and What It Means for Us” | Joseph A. Tainter | November 2010 | Local Future 2010 International Conference on Sustainability (Prince Conference Center, Grand Rapids, Michigan), described at http://localfuture.org/conferences.htm .

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“I hate Karl Marx” | Rainer Ganahl | 2010 (web video)

I laughed out loud @KiasmaMuseum at @rainerganahl 2010 video “I hate Karl Marx”, but the humour didn’t seem to be appreciated by others.

Here’s a description from the artist:

For this video playing in the year 2045 Karl Marx has reincarnated as Chinese. He controls the world and the entire world is Chinese, speaks Chinese, dresses and eats Chinese (the same way it is today English/American). Marx’s specter to haunt the world could not be stopped by any capitalist alliance. The young German lady speaking and screaming entirely in Chinese suffers a melt down in front of Marx’ statue on Karl Marx Allee expressing her discontent and opposition.

The appreciation of Karl Marx is described by Rainer Ganahl more fully at http://www.ganahl.info/karlmarx.html:

I see Marx as an socio-economic thinker who came up with the best analysis of his generation. He was the first one to properly grasp the full impact of industrialization and its consequences on people in relationship to the entire economic system.

He did do that with an ethical eye, a drive for social and economic justice and a good portion of wishful teleological thinking one can share or not

This work of art could be described by Stuart Candy as “Journalism from the Future“.

I hate Karl Marx

“I hate Karl Marx” | Rainer Ganahl | 2010 (web video) at http://www.ganahl.info/Ihatekarlmarx.html

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John E. Kelly III | “The Future of Cognitive Computing” | Oct. 13, 2015 | IBM (web video)

From the 2015 Cognitive_ColloquiumSF, at http://research.ibm.com/cognitive-computing/#sf, there’s a video:

  • Kelly, John E., III. 2015. The Future of Cognitive Computing. Web Video. Third Annual IBM Research Cognitive Colloquium: Augmenting Human Intelligence. Mission Bay Conference Center at USCF. research.ibm.com/cognitive-computing/#sf.

Watching the video, here are some personal notes, with timecodes:

[10:35] The first era of computing:  1900-1940s Tabulating Systems Era; second 1950s Programmable Systems Era (but will run out of programmers); 2011 — ? Cognitive Computing Era, will be as different as Programmable from Tabulating

[16:20] Man and machine will beat man or machine

[16:25] Human capabilities: Compassion, intuition, design, value judgments (moral value), common sense (unless they can ever be quantified)

[16:55] Machine capabilities:  Deep learning (instant recall of everything, source to all knowledge), discovery (capability to start to reason), large-scale math, fact checking

[17:20] Human + machine: human beings have a normal distribution of capabilities, but with human + machine, can move the distribution

[18:30] How do we get the synergy between man and machine?

[18:40] Since Jeopardy, this field has lit up: image processing, optimizing buying behavior, signal processing of voice.  But they’re all point solutions

[19:25] IBM trying to build a while toolkit, like the System/360 in 1964.

[20:10] Watson capability, put into cloud (so could scale), decomposed the Question & Answering system into five technologies:  machine learning, question analysis, natural language processing, feature engineering, ontology analysis

[20:40] Build out a suite of services on the Watson cloud that are composable assets.

[22:50] Essence of cognitive capability: first is learning at scale, reasoning or developing insights with the data, with a goal, interacting with humans.

For the video, there’s a slide-by-slide breakdown as “The Future of Cognitive Computing” | Andrew Trice | November 23, 2015 | IBM Bluemix Dev at https://developer.ibm.com/bluemix/2015/11/23/future-of-cognitive-computing/

The dawn of the Cognitive Era

The Future of Cognitive Computing (transcript by Andrew Trice)

 

The associated white paper is at:

On “The technical path forward and the science of what’s possible”:

Programmable systems are based on rules that shepherd data through a series of predetermined processes to arrive at outcomes. While they are powerful and complex, they are deterministic — ­ thriving on structured data, but incapable of processing qualitative or unpredictable input. This rigidity limits their usefulness in addressing many aspects of a complex, emergent world, where ambiguity and uncertainty abound.

Cognitive systems are probabilistic, meaning they are designed to adapt and make sense of the complexity and unpredictability of unstructured information. They can “read” text, “see” images and “hear” natural speech. And they interpret that information, organize it and offer explanations of what it means, along with the rationale for their conclusions. They do not offer definitive answers. In fact, they do not “know” the answer. Rather, they are designed to weigh information and ideas from multiple sources, to reason, and then offer hypotheses for consideration. A cognitive system assigns a confidence level to each potential insight or answer.  [p. 6]

A comparison to AI:

… a critical distinction between the technical approach to cognitive computing and other current approaches to Artificial Intelligence. Cognitive computing is not a single discipline of computer science. It is the combination of multiple academic fields, from hardware architecture to algorithmic strategy to process design to industry expertise.  [p. 7]

As compared to purpose-built, narrowly-focused applications:

Cognitive systems, in contrast, combine five core capabilities:

1. They create deeper human engagement: [….] They reason through the sum total of all this structured and unstructured data to find what reallymatters in engaging a person [….]

2. They scale and elevate expertise:  […]  these systems are taught by leading practitioners — whether in customer service, oncology diagnosis, case law or any other field — they make available to broad populations the know-how of the best.

3. They infuse products and services with cognition:  Cognition enables new classes of products and services to sense, reason and learn about their users and the world around them. This allows for continuous improvement and adaptation, and for augmentation of their capabilities to deliver uses not previously imagined. [….]

4. They enable cognitive processes and operations:  [….]  Business processes infused with cognitive capabilities capitalize on the phenomenon of data, from internal and external sources. This gives them heightened awareness of workflows, context and environment, leading to continuous learning, better forecasting and increased operational effectiveness — along with decision-making at the speed of today’s data.  [….]

5. They enhance exploration and discovery:  [….]  far better “headlights” into an increasingly volatile and complex future.  [….]  By applying cognitive technologies to vast amounts of data, leaders can uncover patterns, opportunities and actionable hypotheses that would be virtually impossible to discover using traditional research or programmable systems alone.  [p. 8]

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Jim Spohrer | “Empowering Makers in the Cognitive Era” |Aug. 10 2015 |ICER (web video + slides)

Keynote August 2015 @JimSpohrer ACM International Computing Education Research (ICER) Conference, Omaha, Nebraska

Slides available at http://www.slideshare.net/spohrer/spohrer-icer-20150810-v1.

[00:00 slide 1] Doug Englebart, Augmentation theory

[12:35 slide 10] Albert Einstein: I fear the day that technology will surpass our human interaction.  We will have a generation of idiots.

[13:55 slide 11] Intelligent Personal Assistant (in wikipedia)

[27:30 slide 26] Intelligence Augmentation (Englebart’s Vision)

[31:20 slide 28] T-Shaped Makers

[33:00 slide 30] By 2035, no one drives.  Cars drive themselves.

[38:00 slide 31]  Responsibility:  Can people drive today without getting a driver’s license?  Shouldn’t they understand some of the science behind it?

[38:45 slides 32-35] Natural systems (explain external phenomena), cognitive systems (explain internal phenomena), service systems (describe people interacting in win-win ways — value co-creation phenomena)

[40:15 slide 37] Cognitive Mediators, Smart Service System

“The difference between a service system and a cognitive system?  My dog is a cognitive system, by the way.  I love my dog.  But my dog has no rights and responsibilities.  Young children, elderly people with dementia, they’re cognitive systems, but they don’t have as many rights and responsibilities, as us mature and responsible people.  The way a cognitive system becomes a service system is when it sets up the rights and responsibilities that go along with being a member of a very productive society”.

Here’s the original abstract from http://icer.hosting.acm.org/icer-2015/icer-2015-keynote/.

After briefly surveying the history of knowledge, computing, programming, and software engineering, computing education will be reframed as empowering makers in the cognitive era. The makers’ movement is about the democratization of the tools of self-expression and production. From global cloud-based deployment of apps on smart phones to nano-manipulation of advanced materials in custom jewelry and clothing with open designs downloadable for 3D printers, software empowers makers to co-create value in smart service systems. Smart service systems are based on provider platforms that enable customer to interact and co-create value together. In addition, cognitive assistants for all business occupations and societal roles are beginning to appear democratizing access to knowledge and expertise in smart service systems.

Teaching about the elegance, not just correctness, of solutions and how they serve customers wants, needs, and aspiration will be of increasing importance. The implications for a next generation of students who “make a job, not just take a job” even before graduation will be explored. Also, issues of sustainability and resilience of smart service systems with empowered makers in the cognitive era will be explored. Rethinking the rights and responsibilities of empowered makers at all ages will require an especially close examination of the way teamwork is encouraged and rewarded in families, neighborhoods, and educational institutions.

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