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Capitalism 4.0 & Neuroplasticity of the Collective Brain

Capitalism 4.0 & Neuroplasticity of the Collective Brain | Decision Intelligence | Scoop.it
I have just returned from an interesting experience in Washington. D.C.: a panel discussion with His Holiness the Dalai Lama. The event was sponsored by the American Enterprise Institute (AEI), a leading neo-conservative think tank responsible for m...
Lorien Pratt's insight:

What a wonderful article, chock-full of insights.  My favorite: "there are two sources of learning: learning from reflecting on the past, and learning from sensing and actualizing emerging future possibilities." .  Yes!  Learning from the past is fundamentally limited.  As things move faster, we must also learn from the future.

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Decision Intelligence
Decision intelligence is an interdisciplinary field with a mission to solve the world's most complex problems It is based on the premise that "the decision"; is the atomic unit of complex problem-solving.   Closely related to Decision Engineering, Decision intelligence draws upon  technology such as visual decision modeling, complex systems modeling, big data, predictive analytics, machine learning. UX design, statistical analysis, business intelligence, business process management, causal reasoning, evidence-based analysis, and more. For an overview, see the webinar at http://youtu.be/XRTJt3bVCaEand more videos at http://www.youtube.com/quantellia. Many of these topics are vigorously discussed in the Decision Intelligence discussion group: http://www.linkedin.com/groups?gid=205078.  See http://www.lorienpratt.com/the-decision-intelligence-and-decision-engineering-ecosystem/ to learn about the emerging ecosystem of decision intelligence companies, influencers, and problems solved.  I also invite Decision Intelligence pioneers to subscribe to my blog and receive my free eBook: http://forms.aweber.com/form/90/568343590.htm .
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Beyond interactive data visualizations to the causal flow at the NYT!

Beyond interactive data visualizations to the causal flow at the NYT! | Decision Intelligence | Scoop.it
Draw your guess for every income level, then compare it with the actual data on college enrollment and the drawings of other readers.
Lorien Pratt's insight:

I really can't express in words how important this is.  In a world where "interactive data visualization" is *only* about drill-down into static data, the NYT earlier this week showed the roots of an interactive, collaborative cause-and-effect link. 


This is the CORE BUILDING BLOCK of forward models, and is the most important element for the future models we're starting to see more and more, where human expertise, machine learning, complex systems, collaboration, and causal visualization combine to bring us to an ENTIRELY NEW LEVEL in how computers support cognition.  Whether you call it Intelligence Augmentation, Cybernetics, Causal Flow Modeling, or Decision Intelligence, the NYT has nailed it. 


Congratulations to Gregor Aisch, Amanda Cox, and Kevin Quealy.  I don't know you guys, but you've nailed it.

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World Makers: Simulation and models will save the world

World Makers: Simulation and models will save the world | Decision Intelligence | Scoop.it

"The goal of World Makers is to encourage people to build computer simulations of the world. This includes simulating water, weather, crops, land use policy or anything else. Models can be regional or global, simple sketches or full blown simulations.

 

The classic game ‘Sim City’ by Will Wright is perhaps the best known example of a computer simulation. It lets people build their own imaginary city from the ground up, placing roads, homes and services and measuring their success against the happiness of the population. The goal here is similar - but real - with real data, real stakeholders and real outcomes.

 

Simulations are a powerful holistic way of understanding and communicating the complexity of the challenges we are facing. The fact is that we are all stakeholders in a complex natural planetary ecosystem. It defines us, our lives, our values. Without nature humanity as we know it will quickly cease to exist.

 

At the same time we are making poor decisions that are undermining our diverse heritage. We risk runaway effects that may be beyond our ability to control. We are playing a high stakes game of planetary Jenga.

 

This is a crisis of organization. We routinely spend trillions of dollars of value to make millions of dollars in profit. Consider even just dredging the Louisiana swamplands or cutting the mangrove trees and the impact on New Orleans. Nature simply doesn’t care about our rhetoric or our aspirations. We cannot predict or model outcomes in such a way as to reach consensus. Almost universally the side-effects of our actions dominate over intended consequences. Private interests can pursue short term gains and externalize true costs onto the rest of us. In sum the world has become too complex to understand with current tools.

 

We simply do not know the outcomes of our decisions. We don’t even have trustworthy predictions of those outcomes. Will the world as we know it even exist after 2100? Or will we see massive ecosystem collapse, human migration, war and other disruptive effects? Or will everything be fine? There is no consensus.

 

The one phenomena moving as fast as the environmental crisis is the Internet and computing power. The hybrid synthesis of human intuition and brute force computation lets us explore more complex situations in more depth. The simulations we are starting to build will eventually allow the most vulnerable and concerned stakeholders predict outcomes at the intersection of policy, law and land-use in a rigorous manner. By doing so we’re shifting the civic debate from “rhetoric” to “model based” reasoning.

 

In the future there will be nobody who is not an environmentalist. There will be nobody who isn’t a direct participant in helping save this planet. We will find ourselves needing to get the participation and buy in from millions of voices that are currently disempowered. We will need to find a way to foster diversity. We need to find a way to stop private interests from eating the public good.

 

Ultimately we’re going to need new models of governance and decision making. It’s clear we’re going to have to hack the systems around us. The structures that got us into this mess are not the same as the structures that are going to get us out. This is how we’re going to save the world."

Lorien Pratt's insight:

This is so important that I'm reproducing it in its entirety here.  Please read and share.

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Beyond Data (part 1): J. K. Rowling, Shakespeare, and the Sorcerer’s Decision

Beyond Data (part 1):  J. K. Rowling, Shakespeare, and the Sorcerer’s Decision | Decision Intelligence | Scoop.it

'The decision is only as good as the data that supports it'.  It was bound to be said"

Lorien Pratt's insight:

Why data matters less than you think.  Me on one of my soapboxes :-)

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Decision lever visualization: an animated review

Decision lever visualization: an animated review | Decision Intelligence | Scoop.it
Since thinking so much about levers in the last two posts, I've also been pondering the variety of levers I've built and seen, and the different purposes they serve in a decision model.   In particular, given that our goal is for models to be as easy to understand as possible to facilitate collaborative team…
Lorien Pratt's insight:

Enjoy this tour of decision lever animations.

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The Odds, Continually Updated - NYTimes.com

The Odds, Continually Updated - NYTimes.com | Decision Intelligence | Scoop.it

Now Bayesian statistics are rippling through everything from physics to cancer research, ecology to psychology. Enthusiasts say they are allowing scientists to solve problems that would have been considered impossible just 20 years ago.

Lorien Pratt's insight:

Bayesian statistics are increasingly important, and this article is an accessible introduction.  The basic idea: calculate statistics as conditional on something else: the probability of cancer *given that* you're a woman over 50; the likelihood of revenue growing more than 50% *given that* your competitors don't launch a new marketing campaign. 

 

Relevant to DI because there's a close relationship between propagating causation in the world and propagating probability (indeed, we might think of the observed probability as the epiphenomenon of the underlying causative link, modulo causation/correlation).  So a Bayesian model can be implemented in a decision model, in those circumstances when probability analysis is the right formalism to solve a particular problem.

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Vusamazulu Credo Mutwa speaks to the importance of awakening nonlinear thinking

"Our people believe that every human being, male or female has two minds: the mother mind, and the warrior mind. The warrior mind looks at things logically. The warrior mind says "two plus two is four". But the mother mind says nothing like that. The mother mind…does not think in a line way as warriors do. The mother mind things sideways, sideways, and upwards and downwards.  We must awaken the mother mind within us.  We must feel what is going on in the world, we mustn't just listen. "

Lorien Pratt's insight:

So the Zulu have an innate understanding of decision intelligence / nonlinear systems thinking / auditory/sequential versus motor/spatial/visual thinking. Who'd have guessed!

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Decision: I do not think it means what you think it means

Decision: I do not think it means what you think it means | Decision Intelligence | Scoop.it
We use the word "decision" to mean two very different things.  If I say "I've decided that the moon is made of green cheese", or "I've decided that the economy will deteriorate next year", these statements aren't necessarily about actions I'm going to take.  If, instead, I say, "I've decided to go to go to…
Lorien Pratt's insight:

Distinguishing "deciding that..." from "deciding what to do".  There's an important difference!

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Decision Engineering: A New Paradigm for Delivering Analytics

Decision Engineering: A New Paradigm for Delivering Analytics | Decision Intelligence | Scoop.it
I just learned that there is a very interesting analytics company in Alameda, California. Alameda is just across San Francisco Bay from Baker Street Publishing. The company is AbsolutData. I can almost see their office from my rooftop.The AbsolutData website reads, "Introducing Decision Engineering -- Turning the traditional delivery model on its head, start with decisions and not data and tools." What a refreshing idea!  Start with decisions and not with data.I have been promoting dec
Lorien Pratt's insight:

A nice post from my friend Steve Barrager about my friends at AbsolutData.  And if you scooched this map down a bit, you'd see me there too, here in Mountain View.  Small world :-)

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luc taesch's curator insight, July 3, 4:06 AM
(Big) Data is focused on the past, not the future. Decision making is about the future.
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Are You a Good Decision Maker? Consider This Emerging Field

Are You a Good Decision Maker? Consider This Emerging Field | Decision Intelligence | Scoop.it
Decision engineering (which also goes by the name decision intelligence) is a field that designs decisions themselves as if they were tangible projects, such as building robots or computer systems, using the same engineering methodologies and techniques.
Lorien Pratt's insight:

Delighted that the DE/DI field was covered today on IEEE Roundup!  Congrats to @timvangelder, @SteveBarrager for mentions in this important article. 


This is the week, guys, the inflection point in the hockey stick.  Hold on tight.

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Baby steps: introducing decision intelligence to clients

Baby steps: introducing decision intelligence to clients | Decision Intelligence | Scoop.it
It's not easy selling into an emerging market, no matter how important it is.  We won two projects in the last week or so.  In both cases, the customer hadn't heard  of decision intelligence before talking with us.  In one, they were looking for data analysis to guide a marketing investment; in the other, the question was to determine the…
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In Search Of The True Value In The Internet Of Things

In Search Of The True Value In The Internet Of Things | Decision Intelligence | Scoop.it

The real value lies in being able to capture and analyze the data that comes from the sensors at the endpoints of IoT — and that needs to be the few nuggets of data that are of material value to the business

Lorien Pratt's insight:

More data from IOT devices doesn't necessarily translate into more business value; some data is more useful than others

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A grand tour of decision architecture tools for leaders

A grand tour of decision architecture tools for leaders | Decision Intelligence | Scoop.it
Structure your organization’s work to encourage wise choices.
Lorien Pratt's insight:

A must-read grand tour of tools & techniques for decision leadership, from two Harvard professors  / consultants. My summary:

Leaders can architect decisions through a five-step process:

  1. Understand biases
    1. Kahneman, thinking fast and slow, system 1 and system 2
  1. Understand behavioral issues at the heart of poor decisions
    1. Burnout?
    2. Technology / knowledge issues?
    3. Narrow down the problem
  1. Determine causes
    1. Insufficient motivation?
      1. e.g. an onboarding process that failed to create an emotional connection
    1. Cognitive bias?
      1. Action-oriented
      2. Bias from perception and judgment of alternatives
      3. Biases from framing of alternatives
      4. Stability bias: prefer the status quo
    1. Seek to shift from System 1 to System 2
  1. Redesign the decision-making context
    1. Use choice architectures and nudges e.g. Thaler
      1. e.g. sign near big plates at google about portion size
      1. e.g. opt-in vs. opt-out retirement planning
    1. Trigger system 1: tap into emotions
    2. Harness biases, e.g. loss aversion: "pay your tax or lose your car"
    3. Simplify processes
    4. Engage system 2
      1. Reflection, broaden thinking, increase accountability, use reminders, and more
    1. Skirt systems 1 and 2 altogether using default and automatic systems
  1. Rigorously test
    1. Identify outcome
    1. Focus on one solution at a time
    1. Think in terms of treatment and control groups
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Learning to See Data

Learning to See Data | Decision Intelligence | Scoop.it

Scientists working in a little-known branch of psychology called perceptual learning have shown that it is possible to fast-forward a person’s gut instincts both in physical fields, like flying an airplane, and more academic ones, like deciphering advanced chemical notation. The idea is to train specific visual skills, usually with computer-game-like modules that require split-second decisions. Over time, a person develops a “good eye” for the material, and with it an ability to extract meaningful patterns instantaneously.

Lorien Pratt's insight:

This is probably the most important Decision Intelligence-related article I've read in a while; apparently there is a new field called Perceptual Learning that studies how we can train specific visual skills, much like my co-founder Mark's STATPLAY research. 

 

Summary:

 

  • A Brooklyn-based painter and conceptual artist is helping genetic scientists to visualize data
  • The goal: reduce big data overload
  • "perceptual  learning" is the little-known field that fast-forwards gut instincts by training specific visual skills, often with computer game modules
  • Eleanor J. Gibson founded  this field in 1969
  • UCLA medical school has adopted perceptual learning modules as part of its standard curriculum, to train on skills like reading electrocardiograms, identifying rashes, and      interpreting biopsy samples
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Decision engineering a subdiscipline of engineering management

Engineering management - Wikipedia, the free encyclopedia

Outside the USA, in Germany the first department concentrating on Engineering Management was established 1927 in Berlin. In Turkey the Istanbul Technical University has a Management Engineering Department established in 1982, offering a number of graduate and undergraduate programs in Management Engineering.

Decision engineering

Decision engineering seeks to use engineering principles in the creation of a decision, which it views as an engineering artifact in its own right. From this point of view, the creation of a decision includes agreeing to objectives, developing a detailed specification, and then creating a decision model, which captures the key cause-and-effect elements of the decision environment (a systems thinking approach) with a focus on the particular decision, instead of the entire system (which can be otherwise intractable). Like other engineered artifacts, a decision model can be subject to Quality assurance review, and-since it is documented-is amenable to Process improvement over time. Decision engineering models draw from the information technologies described above for data supporting the decision, but are distinguished from IT in that they model the decision, not just the data supporting it.

Lorien Pratt's insight:

It's great to see decision engineering recognized as a subdiscipline of engineering management.

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Dance Dance Brainy: Can we get smarter through whole-body interfaces instead of just sitting all the time?

"I'd rather come home with a sore shoulder from having to move all that data around than with Diabetes [from sitting too much]"

Lorien Pratt's insight:

I love this prescient talk from my friend Anselm about whole-body gestural interfaces to computers.  We'll be smarter if we do this, too (http://bit.ly/1LevmNg).

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Why machine learning needs humans

Why machine learning needs humans | Decision Intelligence | Scoop.it

As soon as the situation becomes dynamic, when something unexpected happens and basic assumptions change, the machine-only approach fails mightily

Lorien Pratt's insight:

What a terrific argument for the importance of human-in-the-loop machine learning!  Great job Forbes, Dan, and  Arnab!

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Hand gestures / "situated cognition" a back-channel to our verbal intelligence

Hand gestures / "situated cognition" a back-channel to our verbal intelligence | Decision Intelligence | Scoop.it

"Physical gestures ...constitute a kind of back-channel way of expressing and even working out our thoughts. Research demonstrates that the movements we make with our hands when we talk constitute a kind of second language, adding information that’s absent from our words."

 
Lorien Pratt's insight:

This is why decision models live in visual, motor, even 3D navigation space: to get at all of the smart brains within us.

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Kashif Zia's curator insight, August 10, 5:09 AM

This is why decision models live in visual, motor, even 3D navigation space: to get at all of the smart brains within us.

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Top-ten decision lever best practices

Top-ten decision lever best practices | Decision Intelligence | Scoop.it
"We need to win more work," says the CEO.  "Can you think through how we could lower our prices to become more attractive to our customers?" A good decision engineer can't help but ask "the lever question" at this point: "Ma'am, are we only to consider pricing, or would you be open to other approaches…
Lorien Pratt's insight:

A deeper dive for decision models about how to get your levers right.

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The dirty dozen: twelve ways to fail at effective decision making

The dirty dozen: twelve ways to fail at effective decision making | Decision Intelligence | Scoop.it
In the course of my decision analysis, analytics, and intelligence work for businesses and industry, I have identified a set of common points of failure in a typical decision engineering initiative.  These characterize the "hidden traps", where decision makers often struggle to preserve the integrity of the Decision Engineering life cycle. Below is the chain…
Lorien Pratt's insight:

A great article by @TANGENT Arc about how to avoid decision making pitfalls.

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The Decision Intelligence and Decision Engineering Ecosystem interactive map

The Decision Intelligence and Decision Engineering Ecosystem interactive map | Decision Intelligence | Scoop.it
It's been an incredible last few weeks in the Decision Intelligence world, as we're seeing an ecosystem emerging with new vendors, articles in IEEE, the New York Times, at HBR, and much more. I've taken a first shot, in the graphic below, of mapping the ecosystem. It's not at all complete, so please send me…
Lorien Pratt's insight:

The ecosystem is really taking off. Thanks to you for being a part of this exciting new discipline!

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Experfy Secures Seed Round to Scale Data Scientist Marketplace

Experfy Secures Seed Round to Scale Data Scientist Marketplace | Decision Intelligence | Scoop.it
Founded last year, Experfy Inc. has built a marketplace for data scientists who, like designers using 99Designs Inc. or business consultants using HourlyNerd Inc., respond to requests from individuals and businesses for help with specific projects.
Lorien Pratt's insight:

Experfy provides world-class, expert resources for data science.  Including decision intelligence / decision engineering, I'm delighted to say :-)  (see https://www.experfy.com/practice-areas/visualizations ). Yup, this is the week.

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Gongos: a Decision Intelligence company

Gongos: a Decision Intelligence company | Decision Intelligence | Scoop.it

Gongos is a decision intelligence company.  We partner with outcome-driven, visionary organizations exposing them to the future as seen through consumers' eyes.

Lorien Pratt's insight:

It's tremendously exciting to see decision intelligence taking off.  Here's yet another company in this space! Based in Michigan, Gongos offers solutions to multiple verticals. Clients include Whole Foods, Chase, Fiat Chrysler, and more.  Beyond dashboards, the company offers "infographical journeys, video documentaries, insight portals, animated vignettes, and insight integration initiatives".   Looking forward to getting to know you, @_Gongos!

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Decision Intelligence building blocks: about levers

Decision Intelligence building blocks: about levers | Decision Intelligence | Scoop.it
I'm going to write a series of posts about the core elements of a decision model.  This one's about Levers: simulations of things you can change as you make the decision.   We might also have called levers choices. It can be confusing: you'd think that a decision model would produce the choices as output, not as input.  Because…
Lorien Pratt's insight:

Every complex decision is made of just a few kinds of building blocks.  Levers represent the choices you can make,

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Counterfactual blindness and the invisible things

Counterfactual blindness and the invisible things | Decision Intelligence | Scoop.it

This is an article about invisible things that matter.  Because these things are invisible, it's going to be harder going than usual.   Because they matter, it's worth it. There's a story a friend told me last week about a plumber.  A women calls him in an emergency; there's water everywhere. ..."

Lorien Pratt's insight:

There are a lot of invisible things that need to be made visible.  The "but for" reality is one of them.

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Mark Zangari speaks on Agency and Machine Learning: from data to actions

Mark Zangari speaks on Agency and Machine Learning: from data to actions | Decision Intelligence | Scoop.it
Once upon a time there were programmers, but not software engineers.  As businesses and other organizations learned the value of this new technology, software engineering emerged as a discipline to derive maximum business value from it. There is a similar need emerging in data science today.  This means that machine learning is underutilized compared to…
Lorien Pratt's insight:

Great talk by Quantellia CEO Mark Zangari in Seattle a couple of weeks ago.

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