Decision Intelligence
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Random things make beautiful patterns when they are bumped around in systematic ways

Random things make beautiful patterns when they are bumped around in systematic ways | Decision Intelligence | Scoop.it

This video shows salt scattered on a surface, which is made to vibrate at different frequencies.  The salt creates beautiful different patterns depending on the frequency.

Lorien Pratt's insight:

If a) we live inside systems that have structure (economic, cultural, political, etc.) and b) these systems are subjected to noise, then c) this video shows how systems create emergent patterns.  So d) if we can learn to model that emergence, we can e) do a much better job of achieving the goals that we want and avoiding unintended consequences.


h/t @Linda Larson Kemp

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Decision Intelligence
Decision intelligence (DI) is an interdisciplinary field that solves the world's most complex problems.   DI connects human decision makers to technologies like machine learning, AI, deep learning, visual decision modeling, complex systems modeling, big data, predictive analytics, 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/XRTJt3bVCaE, and more videos at http://www.youtube.com/quantellia. Many of these topics are vigorously discussed in the Decision Intelligence LinkedIn 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. Also, I offer DI and machine learning consulting services.  See http://bit.ly/1X8O2zF to learn more. Would you like to receive the DI News in email? Click here to sign up: http://bit.ly/29wYd1u
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What If It’s All Connected? Humanity and the Global Crisis

What If It’s All Connected? Humanity and the Global Crisis | Decision Intelligence | Scoop.it

We could easily let this massive clockwork of complexity overwhelm us. If it’s all connected, where and how shall I intervene? Isn’t it all too big for me to do anything about? Again, this is the beauty of interdependence. Tug at the right piece of frayed string and the whole rug will unravel before you....Humanity needs to think systemically. We need to act from a place of holistic insight.

Lorien Pratt's insight:

The latest explanation of the critical importance of systems thinking from the incomparable Joe Brewer.

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Prospect Identified: Now What?

Prospect Identified: Now What? | Decision Intelligence | Scoop.it

There is more to selling than knowing who will buy. Knowing when to contact a prospect and what to say can be just as important.

Lorien Pratt's insight:

Absolutdata is one of a handful of companies selling solutions under the decision engineering (which we now call DI) banner.   Marketing and sales tend to be the early adopters of advanced tech (e.g. google, Amazon), so here's another data point in this pattern: AI/decision engineering for sales analysis.  Looks like a great new offering.

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Empathy: The Core of Complex Decisions | Lorien Pratt | TEDxLivermore

Making decisions based on invisible inputs is like building a sky scraper without a blue-print. Yet that is the norm, even for very complex problems
Lorien Pratt's insight:

Please enjoy my TEDx Livermore talk. This is the core of the decision intelligence vision.  Please share.

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Buckminster Fuller’s Manifesto for the Genius of Generalists

Buckminster Fuller’s Manifesto for the Genius of Generalists | Decision Intelligence | Scoop.it
"Only mind can discover how to do so much with so little as forever to be able to sustain and physically satisfy all humanity."
Via Steve Wilhite, luc taesch
Lorien Pratt's insight:

So much is moving today from analysis to synthesis.

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luc taesch's curator insight, August 9, 4:30 AM
vital distinction between money-work and purpose, debunking the myth of the zero-sum game of prosperity
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One link think

One link think | Decision Intelligence | Scoop.it

In the swirl of events, I'm often left wondering if there's something deeper going on.  Our leaders seem to be increasingly missing the bigger picture.  A glimpse, here and there, into the underlying cause of dead ends we've reached: problems with capitalism, the media, politics, climate, conflict, health care.   Is there a common cause? ..."

Lorien Pratt's insight:

When I ran across George Lakoff's article on direct versus systemic causation this morning, it crystallized the "one link think" theme that keeps crossing my mind as I observe world events and think about what's missing.   New to me: the empirical evidence regarding a correlation between one- versus multi-link thinking and political preference. 

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Business School Students Are Taught to Extract Resources and Make a Quick Buck Instead of Creating Value

Business School Students Are Taught to Extract Resources and Make a Quick Buck Instead of Creating Value | Decision Intelligence | Scoop.it

"...executives started to base all of their business decisions on the goal of boosting their firms’ stock prices. When corporations become financialized, executives turn their attention away from investing in the productive capabilities of employees, which is the basic building block for rising American living standards. They also tend to allocate fewer resources to research and development, which is where innovation happens. Instead, executives watch the stock market — in large part because their own compensation was increasingly based on the value of the company’s shares."

Lorien Pratt's insight:

1980s Wall Street->executive shift to focus on shareholder value rather than productive employees / less investment in R&D->Business schools adapted curriculum to appeal to MBAs looking for a "quick buck"->by 1990s shareholders viewed as only constituents-> today focus on Wall Street / quant / modeling rather than on focusing on how to run a business->many teachers don't understand negative impacts of shareholder value (despite Jack Welch calling it "the dumbest idea in the world".

 

My $0.02: this is also an example of an increasing focus on "hard" (e.g. financial) factors rather than "soft" (e.g. social utility) factors in the face of global complexity and competition.

 

DI relevance: look at the first line: it's about business decisions that don't include long-term and soft factors.  That's our mission, people.  Let's do this.

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Pulling Back the Curtain on #MachineLearning Apps in #Business

Pulling Back the Curtain on #MachineLearning Apps in #Business | Decision Intelligence | Scoop.it

"There is a big mistake that many companies are making, spending too much time on their data."

Lorien Pratt's insight:

Please enjoy this techemergence interview with me.  I touch on intelligence augmentation (IA), machine learning in vision, text, and other domains, the emerging decision intelligence ecosystem, the limits of data, and how to hire a machine learning consultant.

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Confessions of a former covert CIA agent - Amaryllis Fox

"Because if your enemy is a policy, no matter how complicated...that we can work with."

Lorien Pratt's insight:

Believe it or not, this compelling video of a former covert CIA agent is about decision intelligence.

 

Our adversaries are humans too, with children they care about, and people they love.

 

By moving from "us vs. them" and seeking a shared vision and working towards shared synergistic outcomes through getting complex situations under control, we have a chance.  It's about policies being too complicated, and working together to fix them.

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squarebeef's comment, June 15, 3:20 AM
Helpful...!!
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Companies struggling to operationalize big data

Companies struggling to operationalize big data | Decision Intelligence | Scoop.it

There is a “growing gulf” between companies’ desire to embrace big data and their ability to operationalize it..."

Lorien Pratt's insight:

The explosion of big data has created an adjacent "desert": knowledge and best practices about how to translate that data into value.   This is especially true in large organizations, in areas like telecom (as shown here), health care, and government.  This article is one of many showing that this resource is vastly underutilized. 

 

Indeed, there isn't even a widely-followed practice of how to write a specification/requirement/objectives document for a project that uses big data.  Indeed, most companies begin with the data, and only later get to the use case / machine learning spec / decision modeling that will translate that data into their business objectives. 

 

This is what we do for our clients (http://bit.ly/1Ukqi98).

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How the Profound Changes in Economics Make Left Versus Right Debates Irrelevant - Evonomics

How the Profound Changes in Economics Make Left Versus Right Debates Irrelevant - Evonomics | Decision Intelligence | Scoop.it

...new economic thinking provides something altogether different: a new way of seeing and understanding the economic world. When viewed through the eyeglasses of new economics, the old right–left debates don’t just look wrong, they look irrelevant. New economic thinking will not end economic or political debates; there will always be issues to argue over. But it has the promise to reframe those debates in new and hopefully more productive directions....

 

New economics seeks explanations of how the economy works that have empirical validity. Thus behavioural economists run painstakingly crafted experiments to explain actual human economic behaviour. Institutional economists conduct detailed field investigations into the functions and dysfunctions of real institutions. Complexity theorists seek to understand the dynamic behaviour of the economy with computer models validated against data."

Lorien Pratt's insight:

In multiple arenas, including economics and more, an older approach - which we might call "linear" for lack of a better term - is giving way to a way of thinking that better reflects the world.

 

This article gives a good summary of what's going on from the point of view of economics.

 

For instance, the Federal Reserve did an analysis in  2006 that predicted "not much" of an impact on the economy if housing prices dropped by 20%.  This was, of course, wildly wrong.  As have been many other predictions that don't take networks, virtuous and vicious cycles, and emergence into account.

 

This is, in essence, the core of what we do in Decision Intelligence: bringing the same next level of nonlinear systems thinking to organizational decision making that this article says is starting to creep into economics. 

 

There is every reason to believe that both approaches have tremendous promise.

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A global artificial intelligence tournament to solve the stock market

A global artificial intelligence tournament to solve the stock market | Decision Intelligence | Scoop.it
Numerai is a global artificial intelligence tournament to predict the stock market. You download our data, build a model, and upload your predictions.
Lorien Pratt's insight:

Exciting! Take expensive-to-obtain stock market data, encrypt it, then allow anyone to download it and make predictions.  Run a tournament, create a hedge fund, and share earnings with the winners.

 

One question: if the data is encrypted, it's going to preclude one of the most powerful techniques for maximizing performance: feature engineering. 

 

otoh, unlike Kaggle, you don't have to disclose your intellectual property when done.   That's a very good thing.

 

See more discussion here: https://www.reddit.com/r/MachineLearning/comments/3wdr9e/numerai_a_global_ai_tournament_to_predict_the/

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Imagine a dog. Got it? I don’t. Here’s what it’s like to be unable to visualize anything.

Imagine a dog. Got it? I don’t. Here’s what it’s like to be unable to visualize anything. | Decision Intelligence | Scoop.it
I have never visualized anything in my entire life. I can't "see" my father's face or a bouncing blue ball, my childhood bedroom or the run I went on 10 minutes ago. I'm 30 years old, and I never knew a human could do any of this.
Lorien Pratt's insight:

Written by Firefox founder Blake Ross, this is a fascinating story about a condition I'd never heard of before: "aphantasia".  It means the lack of an ability to form pictures in your head.

 

For me, it's a cautionary tale of decision making diversity: just because decision mental models are *often* visual, they are not so for everyone. So this is reinforcement to a number of conversations I've been having (one just today with Ruth Fisher and John Kelly) that emphasize the importance of story (text) as an adjunct to a good decision visualization.

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Big data is worthless without AI

Big data is worthless without AI | Decision Intelligence | Scoop.it

What is big data?  Where did big data come from?  Big Data analytics 1.0.  Big Data analytics 2.0.

Lorien Pratt's insight:

Slides from a great talk from H2o's Erin LeDell at Oscon last week.  Good view of how machine learning and AI help organizations to extract value from big data investments.

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Physicists have discovered what makes neural networks and deep learning so extraordinarily powerful

Physicists have discovered what makes neural networks and deep learning so extraordinarily powerful | Decision Intelligence | Scoop.it
Nobody understands why deep neural networks are so good at solving complex problems. Now physicists say the secret is buried in the laws of physics.
Lorien Pratt's insight:

I've been getting off-the-charts successful results with deep learning lately, and this article explains a bit of why.  It seems that, although there are an infinite number of models that could possibly be built, the universe is constrained and so reality only follows a subset of them.  And deep learning models a similar subset.  So by choosing a structure that emulates the hierarchical structure of the human brain, which also evolved to model that same subset of functions, deep learning doesn't have to search an infinity of mathematical functions, rather a much smaller space.  And that's how it can be tractable.  How cool is that?

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Humanity, Star Trek, Buckminster Fuller, and the Kobayashi Maru

Humanity, Star Trek, Buckminster Fuller, and the Kobayashi Maru | Decision Intelligence | Scoop.it

"I reprogrammed the simulation so it was possible to rescue the ship"

Lorien Pratt's insight:

Please read this terrific article by my friend @stevebrant.  A rich fictional world is essential for the kind of systems change that we need for DI to be widespread. And Star Trek: Discovery may well be the right vehicle.

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Integrated reporting as a sustainability tool

Integrated reporting as a sustainability tool | Decision Intelligence | Scoop.it
It's time for integrated thinking — or the development of business models, strategies and decision-making that integrate concerns for society and the environment into the pursuit of profitability — in integrated reporting.

Via Acquisti & Sostenibilità not-for-profit
Lorien Pratt's insight:

We can talk about new things like decision intelligence all we want, but we need to meet organizations where they are at today: and reporting is done by everyone.

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Dr. Sheila Ronis: The Center for Complex and Strategic Decisions - Past, Present and Future

Dr. Sheila Ronis: The Center for Complex and Strategic Decisions - Past, Present and Future | Decision Intelligence | Scoop.it

Hosts: Quantellia; SV SIMCenter; One Island, Ford Innovation presents Dr. Sheila Ronis: The Center for Complex and Strategic Decisions - Past, Present and Future - Wednesday, August 24, 2016 at The Ford Research and Innovation Center, Palo Alto, CA.

Lorien Pratt's insight:

Join me August 24 in Palo Alto for this important speaker.

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Now is the Time to Be Rooted In Reality

Now is the Time to Be Rooted In Reality | Decision Intelligence | Scoop.it

"In this time of unprecedented global change, we need to be rooted in reality more than ever. Yet it is quite clear — by simply tracking all the ways people make an exodus from “the real” on a daily basis — that we are not doing this individually or as a collective humanity....there is a profound disconnect between what is needed and the outcomes we are getting....it is essential that we learn how to discern what is really going on. This means disconnecting from the endless streams of novelty on our social media feeds. It means studying the cultural logics of our political and economic systems. Deeply and thoroughly, it means understanding the history of what brought us to this period of mass turbulence that is now changing the very chemistry of our planet — and redefining our place in the world....What we aren’t doing is putting all the pieces together and acting on what we would see if we did so. As a knowledge synthesizer myself, I see where many of the patterns converge. But more watchful eyes are sorely needed. And better ways of coordinating ourselves toward collective action must follow from what we see together. This means we need a LOT more people connecting with reality.

Lorien Pratt's insight:

This is one of the best manifestos on the importance of decision intelligence I've seen.  And, like us, Joe Brewer realizes that Design is core to the solution to the problems we face.  Any friends know Joe?  Yet another tribe member to connect to the hive.... :-)

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Solving All the Wrong Problems

Solving All the Wrong Problems | Decision Intelligence | Scoop.it

"A service that sends someone to fill your car with gas.

A service that sends a valet on a scooter to you, wherever you are, to park your car.

A service that will film anything you desire with a drone.

A service that will pack your suitcase — virtually."

Lorien Pratt's insight:

A very important article, reflecting a growing sentiment in technology circles that we need to focus on the grand challenges.  DI is a road map for bridging the two worlds: hooking in the the big data / machine learning folks complex decisions.

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Empathy Theme of TEDx Livermore

Empathy Theme of TEDx Livermore | Decision Intelligence | Scoop.it
TEDxLivermore team has chosen empathy as the theme for its 2016 meeting.
Lorien Pratt's insight:

Join us tomorrow in Livermore

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The Economy Isn't A Machine. It's Organic and Constantly Evolving. - Evonomics

The Economy Isn't A Machine. It's Organic and Constantly Evolving. - Evonomics | Decision Intelligence | Scoop.it

The standard, equilibrium approach has been highly successful. It sees the economy as perfect, rational, and machine-like, and many economists – I’m certainly one – admire its power and elegance. But these qualities come at a price. By its very definition, equilibrium filters out exploration, creation, transitory phenomena: anything in the economy that takes adjustment – adaptation, innovation, structural change, history itself. These must be bypassed or dropped from the theory.

 

By the mid 1980s, many economists were ready for a change.

Lorien Pratt's insight:

Core DI reading: W. Brian Arthur's overview of the history of complexity economics.  Complexity economics is very closely related to DI: the difference is DI's tighter connection to machine learning, and our emphasis on visual models that make complex models accessible to the masses.  Also, DI has a tighter focus: on the decision - than economics, which seeks to model larger systems. We share identical roots however: the core themes of emergence, systems, and complexity are essential for solving complex problems, and complexity economics is way ahead of the pack in terms of fields that understand this.

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The Real Secret of Youth Is Complexity

The Real Secret of Youth Is Complexity | Decision Intelligence | Scoop.it
Simplicity, simplicity, simplicity!” Henry David Thoreau exhorted in his 1854 memoir Walden, in which he extolled the virtues of…
Lorien Pratt's insight:

A great illustration of antifragile principles.  And a hope for the future: the complexity we face everywhere will make us stronger.

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Emerging trends in digital marketing: 6 takeaways from Gartner Digital Marketing Conference

Emerging trends in digital marketing: 6 takeaways from Gartner Digital Marketing Conference | Decision Intelligence | Scoop.it
CMOs, take note: From omnichannel challenges to IoT developments, digital marketing's future looks bright ... and a little scary.
Lorien Pratt's insight:

Different verticals are adopting data, analytics, and machine learning at different rates.  Digital marketing is near the start of the pack, so other industries like healthcare and telecom can learn a lot by watching its progression.  Here's a great article from my friend Karsten on the state of the art.

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Why do you make bad decisions?

Why do you make bad decisions? | Decision Intelligence | Scoop.it
From cognitive bias to groupthink - this chart shows what could be clouding your thinking

Via Philippe Vallat
Lorien Pratt's insight:

A nice chart with the classic biases

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Gary Bamford's curator insight, December 27, 2015 5:28 AM

Something to consider in the New Year.

Paulo Amendoeira's curator insight, February 1, 6:11 AM

Why do you make bad decisions?

LuizQuaglia's curator insight, September 16, 11:18 AM
Decisões ruins! Aqui 20 viés cognitivos que estragam nossas decisões. 
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The Science of Intuition: How to Measure 'Hunches' and 'Gut Feelings'

The Science of Intuition: How to Measure 'Hunches' and 'Gut Feelings' | Decision Intelligence | Scoop.it

"The results showed that when the participants were shown the positive subliminal images, they did better on the task: They were more accurate in determining which way the dots were moving. But they also responded more quickly and reported feeling more confident in their choice.

The experiments also suggested that the participants became better at using their intuition over time, Pearson said. "It's all about learning to use unconscious information in your brain," he said. Just as people can become more comfortable making decisions when they apply logic and reasoning, they may also become more adept at trusting their intuition when they use it more frequently over time, the study revealed. "

Lorien Pratt's insight:

Unlike previous studies, which relied primarily on questionnaires, this study used a clever subliminal design to present information to only the subconscious - and not the conscious - mind.

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