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Complexity science meets bottom-up development

Complexity science meets bottom-up development | Decision Intelligence | Scoop.it
Systems models may offer realistic solutions for development, a workshop hears. But what about the building blocks?
Lorien Pratt's insight:

More "Systevism".  I intend to buy this book, right now.

"The last thing I expected to hear at this week’s workshop in London, United Kingdom, on complexity science was that this is an approach that can lead to realistic solutions to development challenges from the bottom up. But it is one of the messages that came through from freelance science writer Philip Ball, as well as Ben Ramalingam, author of the widely acclaimed book Aid on the Edge of Chaos, which draws on complexity research to argue for its role in rethinking development aid."

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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.   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 LinkedIn group Effective Decision Making in the Midst of Complexity: http://www.linkedin.com/groups?gid=205078.  Also see http://www.tdi3.org, http://www.quantellia.com, http://www.absolutdata.com/, and http://www.informeddecisions.se/.  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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Who is your Company’s Chief Decision Officer?

Who is your Company’s Chief Decision Officer? | Decision Intelligence | Scoop.it

Per a recent PWC report, “Big decisions have big impact on future profitability, with nearly 1 in 3 executives valuing those decisions at least at $1 billion”. Today’s organizations are dealing with complex situations that change “in flight”, technical silos, intellectual property locked in the minds of few, and more.

Lorien Pratt's insight:

Looking forward to this great keynote panel.  Join me!

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Artificial Intelligence Powered by Crowdsourcing: The Future of Big Data and Humanitarian Action

Artificial Intelligence Powered by Crowdsourcing: The Future of Big Data and Humanitarian Action | Decision Intelligence | Scoop.it
As far as we know, AIDR is the only Big Data solution out there that combines crowdsourcing with real-time machine learning for disaster response. Why do we use crowdsourcing to train the AI engine? Because speed is of the essence in disasters. You need a crowd of Digital Humanitarians to quickly tag as many tweets/messages as possible so that AIDR can learn as fast as possible. Incidentally, once you’ve created an algorithm that accurately detects tweets relaying urgent needs after a Typhoon in the Philippines, you can use that same algorithm again when the next Typhoon hits (no crowd needed).
Lorien Pratt's insight:

I'm excited to see this book announcement: another data point in the explosion of new use cases we're starting to see for AI/ML/DI.

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Welcome to the age of unintended consequences (and what to do about them)

Welcome to the age of unintended consequences (and what to do about them) | Decision Intelligence | Scoop.it
So one of my favorite things about decision intelligence is its promise to help to overcome unintended consequences. As a way to capture both mental models, as well as providing an ongoing infrastructure to gather evidence to support and refine what start out as mental models and end up as sophisticated systems models, I’m tremendously excited about the future of what we can do.
Lorien Pratt's insight:

Unintended consequence design patterns?  Yet another "reality engineering" post. 

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Google wants to rank websites based on facts not links

Google wants to rank websites based on facts not links | Decision Intelligence | Scoop.it
Being trustworthy and accurate could help a web page rise up Google rankings if the search engine giant starts to measure quality by facts, not just links
Lorien Pratt's insight:

When you do a google search, you can receive millions of results, so their order matters a lot.  Google's current approach orders the results based on the number of incoming links to a site.  It is looking at ranking, instead, by truthfulness. 


This article also describes a few other truth-detection initiatives.  Important work, and it's just getting started.

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Are Machine Learning and Big Data all about just advertising and marketing?

Are Machine Learning and Big Data all about just advertising and marketing? | Decision Intelligence | Scoop.it

"use cases seemed to have focused on just a few, very lucrative ones, and that many other applications of this great technology had been left by the wayside. In what appeared to be a bit of winner-take-all"

Lorien Pratt's insight:

Are we seeing impoverished ML use cases in recent years?  And if so, is the tide turning?

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Do Marketers Rely on Instinct Over ROI?

Do Marketers Rely on Instinct Over ROI? | Decision Intelligence | Scoop.it
While 87% of B2B marketers used social media, just 17% were able to prove its ROI—the lowest percentage among channels used.
Lorien Pratt's insight:

Interesting: though marketing and advertising seem to constitute the majority of Big Data use cases, many marketers still rely on "gut instinct" decision making.  My own $0.02 as to why: the future is not like the past, and we know it. So yet another good place for decision modeling, where we bring the best of the evidence-based world (based on past data) together with systems-based understanding (which helps us to understand the future).

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Agency Theory: Because what use is data, if it doesn't lead to actions?

Agency Theory: Because what use is data, if it doesn't lead to actions? | Decision Intelligence | Scoop.it

Agency Theory: The existence of massive data sets in many arenas is creating new challenges. Most people know about the issue of spurious correlations that do not represent true cause-and-effect. However a second challenge is more insidious and costly: this is the expense – which can run into the billions of dollars – of managing data that does not lead to actionable and valuable outcomes for an organization. For this reason, organizations that can identify the 20% of data that represents 80% of value realize a substantial advantage.


In this talk, I introduce Agency Theory, which is a mathematical framework for analyzing decision models to solve this problem. Agency theory borrows key ideas from machine learning, to solve a different purpose: rather than finding a set of parameters that best fits a data set, the objective is to find a set of decisions that leads to the most favorable set of outcomes, along with the data that is most valuable in supporting those decisions.

Lorien Pratt's insight:

Please join my Quantellia cofounder Mark Zangari in Seattle on May 1.  This is a landmark talk.  I'll be there too.

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James Dolan's curator insight, March 8, 12:30 PM

this is a more general problem affecting how we translate clinical research into practice and organize health systems that is too rarely discussed.

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The Science of Decision Making: Signup deadline is March 9

The Science of Decision Making: Signup deadline is March 9 | Decision Intelligence | Scoop.it

How does the latest research in neuroscience, psychology, and behavioral economics help us model, influence and improve decision making?

Lorien Pratt's insight:

  Looks like an amazing course!  Online starting soon, then at Stanford in April.  h/t @nmurphysf

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Developing the right big data strategy for your organization

"Having the most data seldom makes you the wisest, the fastest, or the most nimble. The champions of small data appreciate that big insights often come from simple events. "

Lorien Pratt's insight:

Be thoughtful with your data."

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7 Pricing Mistakes To Avoid: Data-Based Insights from Salesforce, Uber and Kraft

7 Pricing Mistakes To Avoid: Data-Based Insights from Salesforce, Uber and Kraft | Decision Intelligence | Scoop.it
“Pricing is one of those things that till you go and make the change you don’t know what will happen. You go in with a lot more confidence if you have data,” says Anil Kaul, the founder and CEO of Absolutdata, a San Francisco-based firm with offices in Singapore, the Middle East, India, and the United Kingdom. Founded in 2001, Absolutdata now has more than 450 employees.
The company, which has a $20 million investment from Fidelity, specializes in what it calls “decision engineering.” This is the discipline of applying data to your decision-making process in a structured fashion. Among other things, the company provides pricing scenarios based on analytics.
Lorien Pratt's insight:

Congratulations to my new friend Anil Kaul and Absolutdata for this great article about decision engineering in pricing decision making in Forbes!

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What is a decision engineer?

What is a decision engineer? | Decision Intelligence | Scoop.it
Engineers know how to exercise judgment when data is not available. (Early in my engineering career I was told that, “Engineering is the art of approximation.”) Decision engineers know how to help other people assign probabilities to uncertain events and overcome cognitive biases.
Lorien Pratt's insight:

An absolutely top-notch article from one of the world's first and best Decision Engineers, Steve Barrager.  Talk to this man, he really knows his stuff.

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The "secret sauce" at the center of complex decisions is in cause-and-effect links. Here's how to make them rock.

The "secret sauce" at the center of complex decisions is in cause-and-effect links.  Here's how to make them rock. | Decision Intelligence | Scoop.it

"...with a decision model, we can see how machine learning, AHP, and machine learning fit into an overall picture of how to make decisions more rigorous, transparent, and agile."

Lorien Pratt's insight:

Cause-and-effect links live at the heart of complex systems.  And understanding them means we can go beyond historical data to understand situations we haven't faced before, using piecewise causal links from the past to inform new situations.  This is incredible, because it breaks us from the tyranny of using only historical data in data science, machine learning, AI, and more..    Here's how three previously separate approaches can be used to help us get the links right.

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How to bridge from great data to great decisions?

How to bridge from great data to great decisions? | Decision Intelligence | Scoop.it

Unlike most data conferences solely geared toward technical aspects, Data4Decisions focuses on the needs of executives and decision makers, uniting the best minds in business and technology to uncover common––and powerful––opportunities to effectively deploy data, make smarter decisions and achieve lasting results.

 

While the conference tracks will present interactive panel discussions and case studies citing specific examples from targeted industries, attendees will be provided executable insights and actionable takeaways, regardless of their current sector.

 

The cross-cutting themes will assist decision makers in preparing or advancing their organizations to meet the common challenges associated with security, workforce, ownership, monetization and privacy. 


Lorien Pratt's insight:

Join me next week in Raleigh.  This will be a great conference!

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Time for big data and machine learning to take a bold step forward…into 1946

Time for big data and machine learning to take a bold step forward…into 1946 | Decision Intelligence | Scoop.it

We've been lost in data for half a century. Time to move on, friends. Robert McNamara, secretary of defense from 1961 through 1968, came to the post from Ford Motor company, where he was ultimately appointed president.  His success in both positions came from bringing the discipline of statistical control from the Air Force into Ford"

Lorien Pratt's insight:

This is a quick read (lots of pictures :-) ) and a link to Mark's talk at USF last year for a deeper dive.

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Qstride's curator insight, March 26, 1:35 PM

Technology

Mitchell Ryan's curator insight, March 26, 10:35 PM

A Really interesting take on how big data is useful

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Beautiful interconnection patterns in organizations mimic biology

my vision is a collective human intelligence assisted by a technology substrate like a membrane of technology that augments human capacity and ability to perceive, reason, think, act (experience collectively). I am interested to understand real human behaviours as evidenced by how we relate and communicate and provide an understanding of the individual vs group, the continuous spectrum and widening of the self-concept and the malleable and porous nature of human identity, the individual vs the collective, we are all one.
Lorien Pratt's insight:

I've seen this so may times, and it's lovely that we're now drawing pictures of new previously invisible things.

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Meat and Bones: Machine learning and DI working together for evidence-based management

Meat and Bones: Machine learning and DI working together for evidence-based management | Decision Intelligence | Scoop.it
I had a great call with the CEO of a possible partner company for Quantellia this week, where I found myself saying that Decision Intelligence is the “bones” to the “meat” of machine learning.
Lorien Pratt's insight:

This is one of the most tremendously exciting things in the world, to a geek like me.

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Data data everywhere, but hard to make it think.

Data data everywhere, but hard to make it think. | Decision Intelligence | Scoop.it

Our community of big data providers consists of people with wide range of professional and academic backgrounds: Data Engineers, Data Scientists, Data Mining Experts, Data Analyst/Modelers, Big Data Solutions Architects, Visualization Designers, Statisticians, Applied Physicists, Mathematicians, Econometricians and Bioinformaticians.

Lorien Pratt's insight:

Experfy is my hero.  And they're solving one of the most important issues in a world of galloping big data.  Watch the video at the top of their page, it's excellent.

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Google has developed a technology to tell whether ‘facts’ on the Internet are true

Google has developed a technology to tell whether ‘facts’ on the Internet are true | Decision Intelligence | Scoop.it
the fact that a search engine could effectively evaluate truth, and that Google is actively contemplating that technology, should boggle the brain. After all, truth is a slippery, malleable thing — and grappling with it has traditionally been an exclusively human domain.
Lorien Pratt's insight:

It's a method that's ingenious in its simplicity: spider for knowledge "triples", e.g. (Barack Obama, nationality, American).  In other words: (object, attribute, value).  Yet another example, imo, of taking the oo paradigm out of code and into reality.  A good idea.

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Gapminder's new initiative: overcoming ignorance - misconceptions about world population and more

Gapminder's new initiative: overcoming ignorance - misconceptions about world population and more | Decision Intelligence | Scoop.it
The world is spinning so fast that it can be hard to keep track of everything going on. And most of us aren't doing a good job of it, writes Hans Rosling.
Lorien Pratt's insight:

Ever wondered what happened to Hans and Ola Rosling, of Gapminder fame?  It's The Ignorance Project, to help us improve our collective knowledge (http://www.gapminder.org/ignorance/) This is at the foundation of good decision intelligence, and very exciting news.

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How big data and supercomputing can provide "anticipatory intelligence" to the IC

How big data and supercomputing can provide "anticipatory intelligence" to the IC | Decision Intelligence | Scoop.it
“We’re trying to bring the intelligence world into the 21st century,” he said. “Policymakers are still asking for stuff that equates to the TripTik, because that’s what they’ve always done.”
An outdated U.S. national security system yields a culture that is reactive rather than anticipatory, which is hardly a winning strategy, according to O’Connell.
Lorien Pratt's insight:

The US Intelligence Community is looking at predictive analytics to do a better job of anticipating the future.  h/t Linda Kemp.

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The Next Technology Revolution Will Drive Abundance And Income Disparity

The Next Technology Revolution Will Drive Abundance And Income Disparity | Decision Intelligence | Scoop.it

...researchers concluded that of the 702 job functions studied, 47-percent are at risk of being automated.

Lorien Pratt's insight:

Like any new technology, machine learning will have negative disruptive effects as well as positive ones.  Maybe we can solve this using itself: leveraging machine learning frameworks like World Modeler (http://www.quantellia.com) to find the sweet spot where we maximize the benefits while minimizing the disruption?

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What to do when complexity starts to eat you alive: in law, government, and organizations

What to do when complexity starts to eat you alive: in law, government, and organizations | Decision Intelligence | Scoop.it

"As a software engineer, I realize I’ve seen this situation before.   It’s what code looks like before it’s been refactored. Because our systems must work efficiently for our companies to survive, software engineers have developed a comprehensive architectural best practice, starting with the concept of code smell ..."

Lorien Pratt's insight:

Summary: things (governments, laws, organizations) get crazy complex, like giant balls of band-aids.  We can fix them.  We must.

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There are two kinds of software: It’s time to take world modeling seriously

There are two kinds of software: It’s time to take world modeling seriously | Decision Intelligence | Scoop.it
It's time to get serious about world modeling.  Here's why: There are two kinds of software in the world. (1) Tools (like Microsoft word) and (2) software that depends on a model of the world as its core capability Examples of the second category are...
Lorien Pratt's insight:

This crystallized for me earlier today.  I hope you find it useful.

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Teaching Your Kid to Read (or to navigate a complex world)? Let Her Play Minecraft 

Teaching Your Kid to Read (or to navigate a complex world)? Let Her Play Minecraft  | Decision Intelligence | Scoop.it
Successful games steer players through their complex systems incrementally, in a sort of feedback loop between player and game that’s as fun as it is difficult, encouraging success and growth instead of defeat.
Lorien Pratt's insight:

I've been reading about the Quest to Learn school for years, and they seem to have a great handle on how to use modern computer technology to teach critical thinking, complex system understanding, and more.  Yet another great development from this world-class institution.

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Quick Study: Modeling a basic decision in World Modeler

Quick Study: Modeling a basic decision in World Modeler | Decision Intelligence | Scoop.it
Hello and welcome to World Modeler! 
Quick Study 1 includes a step-by-step guide to the basics of model building, including time-based simulation.  You can download the PDF document, then use it t...
Lorien Pratt's insight:

Please enjoy this step-by-step video, the first in a series of World Modeler tutorials.

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