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Decision Intelligence
Decision intelligence is a framework to apply an interdisciplinary set of technologies to solve the world's most complex problems in an increasingly nonlinear and rapidly changing world. Technology includes predictive intelligence, 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 LinkedIn group Effective Decision Making in the Midst of Complexity: http://www.linkedin.com/groups?gid=205078.  Also see http://www.quantellia.com
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Teaching computers to think like Decision Makers: Quantellia CEO Mark Zangari to speak on May 23 in SF

Teaching Computers to Think Like Decision Makers

Friday, May 23, 2014, 12:30 PM

USF
101 Howard St

10 Data Scientists Attending

Speaker: Mark Zangari, Quantellia Teaching Computers to Think Like Decision Makers: The Next Revolution in the Data Sciences. “Big Data” and analytics have revolutionized "micro-decisions", those myriads of tiny decisions that follow a similar pattern, are made frequently, but each of which has relatively low risk and low value (e.g. the cross-sell...

Check out this Meetup →

We tend to focus on "micro-decisions".  This talk covers how analytics and more can help with "macro" decisions, which are typically less frequent but represent higher stakes.  This talk should be of interest to the SF Bay Area Decision Analysis community, and more.  I'll be flying in to attend as well; it would be great to meet you!

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Generalists to the Rescue: The Emergence of the Sustainability Professional | The Buckminster Fuller Institute

Generalists to the Rescue: The Emergence of the Sustainability Professional | The Buckminster Fuller Institute | Decision Intelligence | Scoop.it
Lorien Pratt's insight:

I think that sustainability is one of the most promising arenas for Decision Intelligence to be of value.


From the article: "The emergence of professional sustainability managers is a product of individual initiative, belief in human agency and responsibility to ensure Earth's appropriate stewardship. This is the new frontier and it is laden with opportunity."

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The backlash against big data

The backlash against big data | Decision Intelligence | Scoop.it
“BOLLOCKS”, says a Cambridge professor. “Hubris,” write researchers at Harvard. “Big data is bullshit,” proclaims Obama’s reelection chief...
Lorien Pratt's insight:

This article summarizes some recent big data backlash, and cites three weaknesses of data: 1) bias problems; 2) "theory is obsolete"; 3) spurious correlations.


Um, well, sort of.  The real problem with data is that it's just one ingredient in the decision-making cake, and yet most pundits treat it as the entire thing.  The rest of the cake includes a causal model (often a complex systems model) that says how today's decision impacts tomorrow, and which captures the emergent characteristics of the situation, intended (and unintended consequences), and the difference between levers and externals.  Just sayin'

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Why doesn't all this data produce better decisions?

Why doesn't all this data produce better decisions? | Decision Intelligence | Scoop.it

..Because one thing is missing: an understanding of how those decisions flow through time to produce results.

Lorien Pratt's insight:

Download the solution for free.

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Dr. Lorien Pratt speaks on Decision Intelligence, CMU Silicon Valley, April 16

Dr. Lorien Pratt speaks on Decision Intelligence, CMU Silicon Valley, April 16 | Decision Intelligence | Scoop.it
  • What is the one question that, more than any other, organizations want technology to answer, but that it does not? 
  • How can machine learning / analytics / optimization technologies be expanded from fully automated use cases to new ones that require some human interaction? 
  • As big data hype normalizes, what comes next? 
  • How can we extend beyond "what do I know?" to "what can I do to impact my goals?" 
  • What problems do emerging democracies and multinational companies share in common, which can be solved with AI/neural network/machine learning technology? 
  • How can data and analytics technologies help to solve the Millennium Global Challenges (poverty, clean water, energy, and more)?
Lorien Pratt's insight:

Hoping to see you there!

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A beautiful video about Patient Decision Assistants: embracing complex medical decisions

NHS Shared Decision Making, patient decision aid, Dec12 low resolution (RT @emjohnston1: "@acpatient: Nice little video about NHS patient decision aids.

Via Informed Medical Decisions Foundation
Lorien Pratt's insight:

How wonderful it is that the NHS has moved beyond simplistic decision support, and embraced the complexities of the behavioral context, including life stage and lifestyle choices, in the medical decision-making process.  There are also complex interactions between the doctor, patient, and information resources that seem to be well-understood here.


Personally, I've had to make some of these same complex medical decisions for myself over the last few years.  I could have used a PDA, for sure!

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Amazon.com: Learning to Learn eBook: Sebastian Thrun, Lorien Pratt: Kindle Store

Learning to Learn - Kindle edition by Sebastian Thrun, Lorien Pratt.

Lorien Pratt's insight:

About taking neural networks from single-purpose machines to multiple tasks.  Includes the best description of my PhD  out there, where I use Shannon's Information Metric (IM) as a secret weapon to assess (and modify) the hyperplanes created by one neural network to be used in another, even if the new task is not quite the same.

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A beautiful film series about complex systems

A short film looking at complex systems theory from http://www.fotonlabs.com "

Lorien Pratt's insight:

This is my favorite short introduction to the complex systems underpinnings of decision intelligence.  Well worth a watch, if only for the beautiful photography.


This is a series in four parts. The following ones are at these links:


Some quotes from the film:

 

"At some point the box does not fit any more...you need a paradigm shift."

"[Complex systems] are the conceptual boxes into which the scientists, by a rather strenuous and devoted attempt, put nature into."

 

"We need to change our view from the component-oriented to the transaction-oriented."

 

"These systems are critically fragile, and small perturbations can trigger larger systemic effects."

 

"Beyond [data] we must come up with new tools, new concepts, to face the problems today."

"This coupling of complex systems with science involves a paradigmatic shift...it emphasizes process over structure, it emphasizes holistic contextualization over reduction"

"We are now living in what we call "the big system". The global system...has many interconnected subsystems, and many, what we call feedback loops."

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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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Optimized Decision Making (a short history of the future)

Doing to data what the browser did to the internet: reducing cognitive friction to realize a multi-trillion dollar opportunity, and more.

Lorien Pratt's insight:

This is the most important presentation I've ever given.  I hope you can take the time to listen, and please share.

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Decision Intelligence for complex optimization: the road ahead

Decision Intelligence for complex optimization: the road ahead | Decision Intelligence | Scoop.it

What's the best price to charge?  Where should I build my new equipment?  Who should receive a loan, to minimize risk?  Which of my people should I train for what program?  Where will my philanthropic donation have the greatest impact.  These and hundreds of other decisions are informed by data, but we usually only go part of the way towards a full optimization solution.  Join this live webinar on Wednesday to find out how to go the distance.

Lorien Pratt's insight:

We've found that computers are better at some things than people are.  So there's a bit of a revolution going on in using them to bring hard evidence to complex decisions.


But we can do more. There are many problems that involve a web of interacting factors, big data, unintended consequences, virtuous and vicious cycles.  Yet for most business problems, computers take us part of the way.


We've put a lot of time and effort into getting great data visualizations , great predictions, great slices and dices of data into the brains of decision makers.


But, in many situations,  the rest is up to us.  We have to assemble the pieces in our heads.  We have to read the map, ponder over the dashboard, study the visualization.  And then make the decision, without further help.


We can do much, much better.  Just as graphical browsers removed the "cognitive friction" for the masses to use the internet, the combination of decision intelligence and optimization removes the friction for everyone to formulate, and then solve, complex problems.

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How Wolves Change Rivers

How Wolves Change Rivers | Decision Intelligence | Scoop.it
Lorien Pratt's insight:

This is a beautiful video showing the unintuitive *positive* consequences that we can understand through a cause-and-effect whole-systems model of an ecosystem.  The substantial cascading ripple effects of the re-introduction of wolves to Yellowstone is quite unexpected and wonderful.


I wonder if there were feedback effects here, too, where the improvements to the river and other wildlife, in turn, helped the wolves.

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A tribute to thinking, fast and slow

A tribute to thinking, fast and slow | Decision Intelligence | Scoop.it
Thinking, Fast and Slow was a global bestseller, and had a profound impact on psychology and economics, as these tributes from other leading figures show
Lorien Pratt's insight:

What a lovely tribute to Daniel Kahneman from some of the great thinkers of our time: Steve Pinker, Richard Thaler, Nassim Taleb, and more.


Kahneman's work is also deeply important to Decision Intelligence, because we'll never automate / systematize the thousands of decisions we make every day, so they're subject to cognitive bias.  Understanding those biases, deeply, is therefore important. 


In addition, arguably the "slow" part of thinking (System 2) is what decision intelligence is trying to do more rigorously for many use cases, because these use cases are being handled today  suboptimally, by the "fast" part (System 1).


Kahneman is the master of this space.  I highly recommend Thinking, Fast, and Slow: http://amzn.to/1bbdQs7 .

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Is the Big Data Backlash Real?

Is the Big Data Backlash Real? | Decision Intelligence | Scoop.it
Earth be still.  Big data has lost its luster. Could it be that analyzing terabytes, exabytes and zettabytes of information won’t make us smarter … or, even worse, could it make us wrong? We’re beginning to see headlines like “Google and the flu: how big data will help us make gigantic mistakes” in the Guardian, “Eight (No, Nine!) Problems With Big Data” in the New York Times and “Big Data: Are we making a big mistake?” on author and F Topic: Big Data.
Lorien Pratt's insight:

A nice roundup of the current status of the question: "Where are we on the disillusionment / enlightenment train with big data". 

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AI / Machine Learning / Neural Networks: what's missing? Lorien Pratt speaks at CMU Silicon Valley

Lorien Pratt's insight:

I've spent the last 18 years since I left my career as a college professor answering a single question: "Why is this incredibly powerful AI/ML/neural network technology not more widely used?"  It's been restricted to just a few use cases, and we're still not using data and objective evidence in thousands of situations across countries and companies around the world.


This talk is the result.  My life's work.  I hope you enjoy it.


(Hint: think complexity)

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Google and the flu: how big data will help us make gigantic mistakes

Google and the flu: how big data will help us make gigantic mistakes | Decision Intelligence | Scoop.it
As Google's attempt to predict the spread of flu by using search terms shows, lots of data can cause plenty of confusion, writes John Naughton
Lorien Pratt's insight:

Good analysis of big data, where it sits on the hype cycle, and why the "evidence-based policy-making" thing has yet to work out.

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The Missing Link: Decision Intelligence for automating the OSS decision-making process

The Missing Link: Decision Intelligence for automating the OSS decision-making process | Decision Intelligence | Scoop.it

In a typical telecom environment, data to support systematic decision making can feel like “feast or famine”. On the one hand, the amount of information available, when combined with the expertise of strategic planners with different backgrounds and experience, can be overwhelming. On the other hand, when launching new products into new markets, where the past is an unreliable guide to the future, data that provides guidance for critical decision-making elements such as pricing demand functions, demand for the product in particular geographies, or the cost of OSS/BSS implementation, may be missing or misleading.”

Lorien Pratt's insight:

Telecom expert Ryan Jeffery writes about decision intelligence and how it applies to telecom OSS.

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How to squeeze every drop of value from big data? Add a complex systems model / decision intelligence: landmark Stratecast report.

How to squeeze every drop of value from big data?  Add a complex systems model / decision intelligence: landmark Stratecast report. | Decision Intelligence | Scoop.it

"The myth that anything done in the data cloud is worth doing, because it makes one agnostic and able to make good decisions, might have been true in the past, but the landscape has shifted. Today, the data cloud is enormous, but most business decisions do not need this overwhelming amount of data."

Read more: http://www.digitaljournal.com/pr/1814044#ixzz2xBlYEsAf

Lorien Pratt's insight:

This is a significant report from a major market research firm about decision intelligence.   It validates the importance of the emerging discipline that is covered here on this Scoop.It page.  From Stratecast, a division of Frost and Sullivan. 

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New treasure trove of free international population data and maps is available

New treasure trove of free international population data and maps is available | Decision Intelligence | Scoop.it

New Release - U.S. Census Bureau International Population Data and Maps


The Census Bureau has added to and updated the online collection of subnational population data linked to maps (shapefiles) that are available at the Spatial Data Repository.  The Repository contains a variety of data and maps primarily for countries that receive assistance via the President's Emergency Plan for AIDS Relief (PEPFAR).

http://spatialdata.measuredhs.com/

 

To access the maps, start at the web page above and:

1. Click on Data in the ribbon below the title

2. Under the Select Countries tab at the left, click on Single Country

3. Choose a country in the dropdown menu immediately below the Single Country tab to see available data sets.  Census Bureau population data and maps are available for the countries listed below.

   - Africa: Botswana, Ethiopia, Ghana, Kenya, Lesotho, Malawi, Mozambique, Namibia, Nigeria, Rwanda, South Africa, Tanzania, Zambia, Zimbabwe

   - Americas: Dominican Republic, Guyana, Haiti

   - Asia/Europe: Cambodia, India, Indonesia, Russia, Thailand

 

In the near future, the Census Bureau will release a seamless global map containing population estimates for tens of thousands of subnational administrative areas globally.  

 

The website below contains links to other Census Bureau international data and map products, including gridded data sets containing population estimates for 100-meter cells for several countries.  These are ideal for obtaining neighborhood-level population estimates.

 

http://www.census.gov/population/international/data/mapping/

 

Please forward these links to anyone who may have use for detailed international population data and maps.  All information on both websites is freely available to the public. We would appreciate hearing about how the data and maps are used, and any other feedback.

from:
Joshua Comenetz, Ph.D.
Chief, Geographic Studies Branch
Population Division
U.S. Census Bureau

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In the next half hour, you can have access to millions of datasets, right from inside Excel

In the next half hour, you can have access to millions of datasets, right from inside Excel | Decision Intelligence | Scoop.it
              I found a great tool for integrating Quandl free, public data into Excel PowerBI. I made a quick screencast too.  There are over 8,000,000 datasets ...
Lorien Pratt's insight:

From my favorite data scientist, @lynnlangit, something amazing.  Be sure to watch the screencast. This is the future, folks. Now let's make some good use of all this data, ok?  It's a treasure trove.

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From trickle down to trickle up

A visual model demonstration showing how tax policy impacts economics.

Lorien Pratt's insight:

Shows how, under certain model assumptions, the middle class drives the economy, and how tax policy impacts this dynamic.

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Data needs to be used: over 10 petabytes of U.S. Climate and Weather data coming soon

Data needs to be used: over 10 petabytes of U.S. Climate and Weather data coming soon | Decision Intelligence | Scoop.it
The National Oceanic and Atmospheric Administration is seeking ways to release vast new troves of its data, a move that could be a boon for businesses.
Lorien Pratt's insight:

The NOAA (and other agencies) have huge repositories of data.  This is a treasure trove, waiting to be unlocked, but we need the right key.  It's not just about willy-nilly data mining.  Instead, the treasure will come from targeted, decision-focused analysis to find causative, not spurious, relationships.


As humans, we're not very good at "connecting the dots" from todays here-and-now actions to tomorrow's effects at a distance.  Visualizing these causal flows, informed by data like this set and more, is what's coming next.


From the article: "NOAA said it seeks to “unleash the potential” of its environmental data by working with entities outside of government. NOAA has 10s of petabytes of data stored in various ways, and produces more than 15 million products daily — from weather forecasts for New York City to tide-gauge observations in Seattle — which it said amounts to about 20 terabytes per day. This is twice the data of the entire printed collection of the U.S. Library of Congress, according to a press release."



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What is Democracy and how do you measure it?

Coppedge, a political science professor currently leading an international research team on the varieties of democracy, says democracy is difficult to break ...
Lorien Pratt's insight:

Yet another terrific data set now available, this one measuring one of the most important aspects of today's world: democracy.  This is not just a data set, but also an ontology: a conceptual map of the dimensions of democracy. Elements of this ontology represent important entities and attributes in many potential decision models. For instance, we might develop an analytic that relates two aspects of democracy: income disparity and access to media.  If these are correlated, then we can go further to try to determine if there is a cause-and-effect relationship.  If we can determine that nature of that relationship, then this becomes part of a decision model that helps us determine if our democracy improvement dollars are best spent on improving access to media, or rule of law, or some other element.  A data model like this one, along with data to populate it, has tremendous value in this setting.

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Lorien Pratt's comment, February 25, 10:52 PM
Also see http://kellogg.nd.edu/varieties.pdf for additional background
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From Artificial Intelligence to Compassionate Intelligence: Steve Omohundro

Steve Omohundro interviewed at the Royal Botanical Gardens in Melbourne Australia. He speaks about artificial intelligence and compassionate technology - app...
Lorien Pratt's insight:

Underneath Decision intelligence are a lot of cutting-edge technologies: big data, machine learning, deep learning, quantum computing, and more, which are also part of a re-emergence of AI.  But what are the greater implications of this increasingly powerful technology?  I lost track of Steve Omohundro a few years back and was delighted to make his re-acquaintance through this video, which covers "compassionate intelligence" (including the work of Marshall Rosenberg, who is one of the great ones imho), balancing multiple outcomes, avoiding unintended consequences, animal intelligence, and more.  A real treat, and worth a watch.


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Big Data, Trying to Build Better Workers - NYTimes.com

Big Data, Trying to Build Better Workers - NYTimes.com | Decision Intelligence | Scoop.it
Lorien Pratt's insight:

One of the most important benefits of big data analysis is when it corrects long-held beliefs: heuristics that we believe to be true, but the data says "not so much".


When we apply analytics to HR, this is often the case, as described in this article.  For instance, are workers who change jobs a lot likely to also leave quickly?  Many believe "yes", but the data doesn't support this pattern.


Another common myth: an outgoing personality is a good indicator of a good sales person.  Turns out that the most important characteristic for sales success is "a kind of emotional courage, a persistence to keep going even after initially being told no."


In Big Data HR, we see these and other conclusions about "soft" factors leading to hard-dollar opportunities for substantial cost savings and revenue growth.

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