Decision Intelligence News
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Decision Intelligence News
AI/BI/CI/DI: Decision intelligence (DI) solves the world's most complex problems.   It 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. See https://en.wikipedia.org/wiki/Decision_Intelligence. For an overview, see the webinar at http://youtu.be/XRTJt3bVCaE, http://www.lorienpratt.com, and the Decision Intelligence group: http://www.linkedin.com/groups?gid=205078.   Also, my company offers DI and machine learning consulting services.  See http://bit.ly/1X8O2zF to learn more.  Don't miss the latest DI news!  Click here to sign up: http://bit.ly/29wYd1u.
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Decision Intelligence: a new discipline emerges

"Where will the value be in AI when the hype is gone? Decision Intelligence is what's next: it is to AI as software engineering was to coding: a bridge from important problems to AI solutions. But also much more: integrating complex systems analysis, agent-based modeling, and many other disciplines, and forming the seeds of a Solutions Renaissance, where people work together with smart machines to solve the hardest problems faced by humanity."

Lorien Pratt's insight:

I hope you find these slides from my prowler.io talk last week valuable.

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Digital twin

Digital twin - Wikipedia

Another example of digital twins is the use of 3D modeling to create digital companions for the physical objects. It can be used to view the status of the actual physical object, which provides a way to project physical objects into the digital world.

"Digital twins integrate artificial intelligence, machine learning and software analytics with data to create living digital simulation models that update and change as their physical counterparts change."

Lorien Pratt's insight:

ML and AI are core to the digital "twinning" of physical objects: yet more validation that these are the right technologies to twin our mental models that lead to decisions. 

One aspect of the future of DI: agents that "twin" your decision-making mental model and make recommendations on that basis. This leads to a number of future use cases for AI, such as the future of collaborative filtering: going beyond prediction into a causal model.  Or for elder patients in mental decline to help to understand how they might have made decisions in complex medical situations.  Well beyond the science fiction of "brain uploading", a mental model mapping (like Five Wishes on steroids) can go a long way. 

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A visual introduction to machine learning: r2d3

A visual introduction to machine learning: r2d3 | Decision Intelligence News | Scoop.it
What is machine learning? See how it works with our animated data visualization.
Lorien Pratt's insight:

This is hands-down the most beautiful and accessible introduction to the core concepts of machine learning I've seen. 

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Cassie Kozyrkov (Google) on Decision intelligence (ML++) | TNW Conference 2018

Cassie Kozyrkov (Google) on Decision intelligence (ML++) | TNW Conference 2018 | Decision Intelligence News | Scoop.it
We're teaching people to fix all these appliances, but we're not teaching them how to use them.
Lorien Pratt's insight:
exactly!
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Why we need DI to solve humanity's hardest problems: 2018 DI Summit visual journal

Why we need DI to solve humanity's hardest problems: 2018 DI Summit visual journal | Decision Intelligence News | Scoop.it
“Why aren’t we solving the world’s problems?” asked Pratt – a 30-year AI researcher. “Let’s make synergies happen.” With topics ranging from SETI’s work on the origin of the universe to the City of Palo Alto’s sustainability initiative, the assemblage included leaders in multiple disciplines including law, government, global economics, ecology, future workforce and higher education.
Lorien Pratt's insight:

This meeting was a surprise for me in a number of ways:

 

  1. DI has hit its tipping point.  Senior thought leaders consider it inevitable.
  2. DI is as much about reconciling human biology, emotions, and cognition and social systems as it is about technology
  3. This is a universal horizontal discipline, attracting experts from SETI to Algae biofuels, from democracy to banking.
  4. The vendor market is crystallizing.
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For all the hype, AI still hasn’t impacted the US economy

For all the hype, AI still hasn’t impacted the US economy | Decision Intelligence News | Scoop.it
There's a suspicious absence of what many economists have expected from the AI boom happening in the US: a lift in productivity, and maybe a catastrophic loss of jobs.
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How invisible things can solve the hardest problems

"We're nearing the bounds of complexity for the types of problems that humans can solve"  A quick look at the book Revealing The Invisible: How Our Hidden Behaviors Are Becoming The Most Valuable Commodity of the 21st Century, by Thomas Koulopoulos (Author) and George Achillias (Contributor)   https://amzn.to/2J8ZK1b

Lorien Pratt's insight:

Revealing the Invisible launches tomorrow!  Congratulations, Thomas!

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Artificial Intelligence: The Miracle and the Menace: G7 Summit Diplomatic Courier preview

Artificial Intelligence: The Miracle and the Menace: G7 Summit Diplomatic Courier preview | Decision Intelligence News | Scoop.it

Artificial Intelligence (AI) may well be the most powerful technology of the 21st century, helping to solve humanity’s most complex unsolved problems: environmental, social, and more.  Yet skeptics believe that AI’s risks are as large as its potential benefits. How can they be avoided? And why isn’t the most powerful technology being used more widely today to solve the world’s greatest “wicked” problems?

 

Great technological advances are often a double-edged sword. A backlash follows an initial “honeymoon period”. Unintended consequences that were not immediately obvious during the technology’s infancy become more apparent, and may even overwhelm the initial, benefits. A historical example is the cotton gin, which led indirectly to the U.S. Civil War.   The challenge is to iron out the rough edges while preserving the benefits."

Lorien Pratt's insight:

Artificial Intelligence is, like many technologies, a double-edged sword.  How can we deploy it to solve the most important problems we face as humanity, while minimizing unintended consequences and bias?  This article is from the Diplomatic Courier magazine being distributed at the G7 Summit that starts on Friday in Quebec. #G7Charlevoix

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When the AI hype is over, where will the substance be?  Prowler.io has the answer #aithinkagain

When the AI hype is over, where will the substance be?  Prowler.io has the answer #aithinkagain | Decision Intelligence News | Scoop.it

"There is an emerging movement of people who ... see the broader issues of the world, and they're sort of frustrated...they think AI isn't really solving these problems...machine learning is solving these single-link problems...What this conference is doing..it's lit a match to this kindling..our challenge here at this conference is to keep that fire going, and to have it build into a network of ecosystems that can solve these big problems."

Lorien Pratt's insight:

I was honored to join Prowler at this important DI conference, and to be featured in this video.

 

"There is an emerging movement of people who ... see the broader issues of the world, and they're sort of frustrated...they think AI isn't really solving these problems...machine learning is solving these single-link problems...What this conference is doing..it's lit a match to this kindling..our challenge here at this conference is to keep that fire going, and to have it build into a network of ecosystems that can solve these big problems."

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AI Can’t Reason Why

AI Can’t Reason Why | Decision Intelligence News | Scoop.it
The first rung is Association, the level for current machines and many animals; on that rung, Pavlov’s dogs learned to associate a bell with food. The next is Intervention: What will happen if I ring a bell, or raise the price of toothpaste? Intervention is different from observation; raising the price unilaterally is different from seeing what happened in the past. The top rung is Counterfactual, which means the ability to imagine results, reflect on one’s actions and assess other scenarios. This is the rung that machines need to reach to evaluate and communicate about responsibility, credit, blame and self-improvement. Imagine giving a self-driving car this ability. After an accident, its CPU would ask itself questions like: What would have happened if I had not honked at the drunken pedestrian?
Lorien Pratt's insight:
We are at a stage with #decisionintelligence where it is so rapidly crystallizing that every week a new facet to this field emerges. Judea's new book popularizing causal inference is this week's development. DI implements the intervention phase that has yet to be broadly achieved by machine learning. And counterfactual reasoning as I have covered in my blog is an important future direction for DI as well
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How Judea Pearl Became One of AI's Sharpest Critics

How Judea Pearl Became One of AI's Sharpest Critics | Decision Intelligence News | Scoop.it
In his new book, Pearl, now 81, elaborates a vision for how truly intelligent machines would think. The key, he argues, is to replace reasoning by association with causal reasoning. Instead of the mere ability to correlate fever and malaria, machines need the capacity to reason that malaria causes fever. Once this kind of causal framework is in place, it becomes possible for machines to ask counterfactual questions—to inquire how the causal relationships would change given some kind of intervention—which Pearl views as the cornerstone of scientific thought.
Lorien Pratt's insight:
Judea Pearl is right. At Quantellia, we build systems that unify bayesian and other casual structures into deep learning and other dependency semantics. What do you think?
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Alcidion announces acquisition of MKM Health and Patientrack to create international specialist health informatics company

Alcidion announces acquisition of MKM Health and Patientrack to create international specialist health informatics company | Decision Intelligence News | Scoop.it

We are very pleased to announce that Alcidion has entered into binding agreements to acquire health informatics software and services company MKM health in Australia and New Zealand, and Patientrack in the UK.

This transformative Acquisition creates a new and leading specialist health IT solution provider focused on “next generation” decision intelligence technology designed for hospital and allied healthcare customers globally. Patientrack and Alcidion’s existing Miya and Smartpage product sets will provide the expanded group with a strong foundation of complementary technologies.

Lorien Pratt's insight:

Yet another DI company emerges: in health informatics

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The Science Behind Lemonade

Lemonade co-founders Daniel Schreiber and Shai Wininger, together with Lemonade's Chief Behavioral Officer Professor Dan Ariely, explain the science behin
Lorien Pratt's insight:

Behavioral economist Dan Ariely uses AI, a B corp, and a completely new business model for insurance to turn the industry upside-down.   It actually looks fun.  Has anybody used Lemonade?  Drop me a line.

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Responsible AI/DI Summit 2018 Tickets, Wed, Sep 19, 2018 at 3:00 PM

Responsible AI/DI Summit 2018 Tickets, Wed, Sep 19, 2018 at 3:00 PM | Decision Intelligence News | Scoop.it
Please join us for the first-of-its-kind, invitation-only half-day event dedicated to crystallizing the extension of AI into DI, and working together to ensure that technology is deployed responsibly to solve the most challenging problems facing businesses, governments, and all organizations worldwide.
The event will consist of a mix of visionary and applied presentations and conversations, including plenty of time for Q and A. Joining us will be global thought leaders VR Ferose (SAP), Cassie Kozyrkov (Google’s Chief Decision Scientist), Steve Omohundro (Possibility Research), Lorien Pratt (Quantellia), Mark Zangari (The Risk Framework), Barney Pell (Decision Theory), John Furrier(SiliconANGLE/theCUBE), Gladys Kong (UberMedia), Kamesh Raghavendra (The Hive), Somik Raha (Ulu Ventures), Jon Swartz (Barron’s), Yuva Athur (SAP Labs), and Tim McElgunn (TMT Research and Advisory Services). Presenters will share their thoughts on DI as it exists today, its potential for the future, and their perspectives on how the journey will take shape. Attendees for this intimate gathering will be able to not only hear from innovators and tech titans, but will also be encouraged to ask questions and share their thoughts on the challenges and opportunities they face.
Learn more
Lorien Pratt's insight:

Responsible AI/DI Summit 2018: This is the beginning of a new community. As we've been syncing up with the conference speakers, I've learned that DI is even bigger than I'd thought: a multidisciplinary field of study that includes the social sciences as much as it does technology. Unifying dozens of disciplines to solve the hardest problems and make the hardest decisions in a responsible way is indeed the most important and challenging problem of our time. And *everyone* has a part to play: from elementary school kids to retirees, from Silicon Valley to rural Africa.

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A visual history lesson in the roots of Decision Intelligence

A visual history lesson in the roots of Decision Intelligence | Decision Intelligence News | Scoop.it

""It's challenging to make decisions based on big data." "We need an insight button." "How do you give people the right set of tools to understand big data?" "Decision makers do not have access." "How does visualization help?" Maybe the writing was on the wall....."

Lorien Pratt's insight:

Visual Insight has been tracking the threads that are today emerging as DI for many years.  And the only way to fully understand this complex field is visually.

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Joe Boutte's curator insight, June 21, 6:37 AM

I learn so much from visual note-taking or journalism.  I agree that there are still ample opportunities to visualize big data for insight and action.  We're closer than we were in 2008 with ample computing power, AI, massive data sets, and great visualization tools.  Moving from data to action is still a challenge, but I love the idea of an "insight button".  I see the first glimpses of it in some of the tools from IBM, Google, Microsoft, and others, but it's on the horizon and it will be more useful than the "easy button".  A lot of science, research, ideation, visualization, and collaboration will get us there.  Thanks for sharing the visual notes and reminding us of how to get further down this path of discovery, insight, and action.

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Our Place In the Cosmos and the Role of STEM in the Advance of Civilization –

Our Place In the Cosmos and the Role of STEM in the Advance of Civilization – | Decision Intelligence News | Scoop.it
(4) The Chaotic Age, characterized by the bewildering collapse of democratic society, which is inherently dysfunctional and therefore riddled with a panoply of hellish and baffleplexing problems: conflict, violence, oppression, injustice corruption, poverty, ignorance, alienation, suffering, and terrorism. The resolution of this nightmare age of unrelenting chaos is to evolve to the Fifth Age where we master the art of taming the ill-mannered recursion laws that define and characterize the Chaotic Age: (5) The Cybernetic Age, in which the otherwise mind-boggling math of recursive loops is tamed and tuned to gracefully converge to the long-dreamed of Omega Point. To emerge from the Chaotic Age and evolve into the Cybernetic Age, we are going to have to conscientiously educate ourselves in the STEM disciplines (Science, Technology, Engineering, and Mathematics) with a concentrated effort to master the fractious mathematics of recursive systems. The key to mastering the Fifth Age is to embrace the Fifth Discipline of Peter Senge. The key is to master Systems Thinking.
Lorien Pratt's insight:

I'm thrilled to read this, because I think it explains the cultural substrate that is driving the need for DI.

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Organizations are complex, loopy, and full of warm data

"...how we might engage more intentionally with emergence to shape adaptive outcomes for our organizations, the world, and ourselves."
Lorien Pratt's insight:

This is the best imagery I've seen about the nonlinear complexities that surround organizations, and how to engage with them.

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Is That Decision Intelligence - or Elvis on a Piece of Toast?

Is That Decision Intelligence - or Elvis on a Piece of Toast? | Decision Intelligence News | Scoop.it
As Kozyrkoz explained it, “We humans are really good at finding patterns; we’ll find Elvis in a piece of toast, and we shouldn’t take that seriously.” She continued, “We’re allowed to make decisions based on intuition as long as we’re really honest with ourselves about it, but if that’s a really important decision, then the decision maker might not want to run headlong into the wall based on Elvis found in a slice of toast.”
Lorien Pratt's insight:
more DI metaphors from Kozyrkoz!
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DI for Insurance Sales Lead Generation

DI for Insurance Sales Lead Generation | Decision Intelligence News | Scoop.it
By pairing publicly available data or their own customer interaction data with Decision Intelligence, insurance companies can identify people with intent, interest and relevant emotional affinity early in the process as they embark on an insurance-related decision.
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Decision Intelligence with Cassie Kozyrkov

Decision Intelligence with Cassie Kozyrkov | Decision Intelligence News | Scoop.it

Chief Decision Scientist, Cassie Kozyrkov joins Mark and Melanie to explain data science, analytics, machine learning and statistical inference, in relation to decision intelligence...."And the mistake that leaders make is they don't see that there is a difference between these two. And so, what they try to do is they try to build themselves a machine learning team-- an AI team-- and they staff that entirely with researchers. And that is exactly the same as you want to run an industrial scale kitchen, and the only people you hire are the folks who've built microwaves their whole lives. Those folks might not know anything about cooking, might have no empathy for restaurant customers. "

Lorien Pratt's insight:

#google has a Chief Decision Scientist, who is an expert in Decision Intelligence.  how awesome is that?

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The greater your value, the less you're paid

The greater your value,  the less you're paid | Decision Intelligence News | Scoop.it
Very few economists have actually attempted to measure the overallsocial value of different professions; most would probably take the veryidea as something of a fool’s errand; but those who have tried tend toconfirm that there is indeed an inverse relation between usefulness andpay. In a 2017 paper, US economists Benjamin B. Lockwood, Charles G.Nathanson, and E. Glen Weyl combed through the existing literature onthe “externalities” (social costs) and “spillover effects” (socialbenefits) associated with a variety of highly paid professions, to seeif it were possible to calculate how much each adds to or subtracts fromthe economy overall. They concluded that while in some cases—notablyanything associated with creative industries—the values involved werejust too subjective to measure, in other cases, a rough approximationwas possible. Their conclusion: the most socially valuable workers whosecontributions could be calculated are medical researchers, who add $9 ofoverall value to society for every $1 they are paid. The least valuablewere those who worked in the financial sector, who, on average, subtracta net $1.80 in value from society for every $1 of compensation.
Lorien Pratt's insight:
multi link DI models could help here
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It's Time to Stop Calling It 'Artificial' Intelligence

It's Time to Stop Calling It 'Artificial' Intelligence | Decision Intelligence News | Scoop.it
The fatal flaw in AI isn't the technology or its intelligence, it'ssomething far more difficult to change.
Lorien Pratt's insight:

this is completely right. most use cases need intelligence augmentation (IA), with humans in the loop. the tech is plenty good enough,so the bottleneck has shifted to this new (and also very old) question:trust, handoffs, mutual understanding, shared mental models, and much more

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Opinion | A.I. Is Harder Than You Think - The New York Times

Opinion | A.I. Is Harder Than You Think - The New York Times | Decision Intelligence News | Scoop.it
The limitations of Google Duplex are not just a result of its being announced prematurely and with too much fanfare; they are also a vivid reminder that genuine A.I. is far beyond the field’s current capabilities, even at a company with perhaps the largest collection of A.I. researchers in the world, vast amounts of computing power and enormous quantities of data..
Lorien Pratt's insight:
Gary Marcus and Ernest Davis are right:AI is much more limited than a lot of hype would have us think (although that being said, there area an amazing amount of single-link systems out there). DI gets us to the next level.
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Sign up for the Decision Intelligence News

Sign up for the Decision Intelligence News | Decision Intelligence News | Scoop.it

All you ever wanted to know about the emerging field of Decision Intelligence.

Lorien Pratt's insight:

A new discipline emerges! DI news now available delivered straight to your email.  Never miss the latest.

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Decision Intelligence Sector Is Taking Shape

Decision Intelligence Sector Is Taking Shape | Decision Intelligence News | Scoop.it

It’s nice to see Decision Intelligence making waves. The subject of what we like to call DI here at Element Data was top of mind last week at the AI Decision Making Summit event held by Prowler.io in Palo Alto. There some of the top minds driving the sector spoke about issues including computational neuroscience, probabilistic modeling and AI simulations for regulatory decision-making.

 

We were especially pleased to see Lorien Pratt, PH.D. and chief data scientist at machine learning and Decision Intelligence firm Quantellia discuss DI in her presentation. Pratt, like Element Data, is a big proponent of DI, and called on attendees and people in this burgeoning field to “reduce the friction between tech and decisions.”

Lorien Pratt's insight:

It's a nice moment history when a field is born.  And it never happens with just one person. Rather, an ecosystem of like thinkers begin to find each other as their density increases, and synergies grow.  I hope you can join us in this journey, whether you're a retiree who wants to play your small part in helping with the biggest decisions, or a multinational corporation looking to maximize the good you do in the world, as well as profits. 

Here's a little summary by Element Data, who I don't know yet, about my talk at the Prowler.io summit, run by a company I didn't know a month ago.  Yet we are all talking the same language.  It's a little magical.

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