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.
Curated by Lorien Pratt
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Guest Post: The Shape of Big Lies

Guest Post: The Shape of Big Lies | Decision Intelligence News | Scoop.it
Social media bombards us with big lies. The juicier and click-baitier, the better, and the happier are advertisers. Unfortunately, disinformation is often plausible as well as attractive. By promising to right an imaginary or misplaced wrong it can tempt us to engage in bullying, persecution, and—in the extreme—bloodshed and even murder. The good news is that there’s a pattern to big lies, and so a pattern as well to beating them.
Lorien Pratt's insight:

Nadine Malcolm shows how a DI causal picture can be used to understand - and combat - Big Lies.  The Salem Witch trials, Mein Kampf, and more.

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The long road to getting to AI value

The long road to getting to AI value | Decision Intelligence News | Scoop.it

"While 70% of business leaders say they understand how AI will change how their organization generates business value, only 10% report significant financial benefits in 2020.

So while 59% of organizations have a strategy for AI, many of the promised benefits remain elusive."

Lorien Pratt's insight:

Decision Intelligence (DI) strengthens the gap between AI and business users, substantially mitigating AI implementation risks, for both fully autonomous as well as human-in-the-loop use cases.

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Limitations of summary statistics in understanding complex problems

Limitations of summary statistics in understanding complex problems | Decision Intelligence News | Scoop.it

If annual averages were the only information we considered, 79 AD in Pompeii was a slightly warmer year than usual—hardly a situation worthy of serious concern. As you can see with this example, averages, when assessing outlier risks, often make very bad metrics.

Lorien Pratt's insight:

More about how average values can be misleading, and so getting more granular can help us understand covid-19, climate change, and more.

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#SpaceWatchGL Opinion: Toward a decision-intelligent process to assess collision risks in space

#SpaceWatchGL Opinion: Toward a decision-intelligent process to assess collision risks in space | Decision Intelligence News | Scoop.it

Many of us were made aware of an alleged near-miss between two satellites in low earth orbit, one operated by SpaceX and the other by OneWeb....we seek to understand, use and manage information in such a way that leads to desired outcomes. This ability is known as Decision Intelligence, and it’s the reason for developing situational or domain awareness."

Lorien Pratt's insight:

DI was used by NASA.ai's Frontier Development Lab a few years back for a similar use case.  Because data wants to be relevant to a decision.

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How to Avoid the Next AI Winter

How to Avoid the Next AI Winter | Decision Intelligence News | Scoop.it

"...quality AI information is clouded by the AI apocalypse narrative. If you google the field, you’ll be challenged to separate medical imaging wheat from AGI chaff. (Don’t tell anyone, friends, there’s no magic here, it’s just math.) AI alone is no more likely to take over the world than is your calculator. Well, unless it’s used as a deniability smokescreen: “It’s not my fault the killer robot smashed your house, it was the AI that did it”.

Lorien Pratt's insight:

It's essential to cut through the AI (and, increasingly, DI) hype to avoid another "winter", where the bubble of expectations pops AI becomes a pariah (again).

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Why do small changes in average temperature matter so much?

Why do small changes in average temperature matter so much? | Decision Intelligence News | Scoop.it

"...the temperature of 95°F is such a value. Stay below it, and very few people die. Rise above it and people start dying, and the higher the temperature rises, the greater the mortality. The chart below shows why a 5.7°F rise in average temperature over 50 years can lead to such deadly results."

Lorien Pratt's insight:

When we use a summary statistic like an average - whether for climate temperature or Covid-19 incidence - it can mask important underlying dynamics that can make a big difference.

Lorien Pratt's curator insight, February 24, 4:11 PM

when we use a summary statistic like an average - whether for climate temperature or Covid-19 incidence - it can mask important underlying dynamics that can make a big difference.

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Why machine learning struggles with causality

Why machine learning struggles with causality | Decision Intelligence News | Scoop.it

"Lack of causal understanding makes it very hard to make predictions and deal with novel situations. This is why you see self-driving cars make weird and dangerous mistakes even after having trained for millions of miles.
...
Generalizing well outside the i.i.d. setting requires learning not mere statistical associations between variables, but an underlying causal model,” the AI researchers write.

Lorien Pratt's insight:

Truth.  This is why we're a lot further away from solving many domains.  The edge cases are (a) tons harder to solve and (b) often tons more expensive if you get them wrong.

Managing this causal information, and combining it with AI, is a core pillar of DI.

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Incorporate decision intelligence in data practices

Incorporate decision intelligence in data practices | Decision Intelligence News | Scoop.it
Even though the concept of decision intelligence is still relatively new on local shores, the potential to disrupt the AI market is significant. Companies must be cognisant of this framework and gain an understanding of how to leverage it for optimal data analysis.
Lorien Pratt's insight:

This article is correct: understand DI is critical for moving technology forward.

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Decision making during the coronavirus crisis | McKinsey

Decision making during the coronavirus crisis | McKinsey | Decision Intelligence News | Scoop.it
Create a forum for rapid debate to take place. Be clear that everyone has a voice but not a vote.
When following this approach, it is possible to involve a large number of stakeholders and experts without sacrificing speed. Especially when things are unfamiliar and the decisions you are considering are bold, you need many points of view to make sure the decision makers aren’t missing something.
Lorien Pratt's insight:

More and more, I'm seeing leading consulting firms like McKinsey embrace the importance of more structured decision making, and the power that comes from improving connection to an evidence base.

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Kasia Smith: Four Simple Steps to Help Your Team Make Better Decisions

Kasia Smith: Four Simple Steps to Help Your Team Make Better Decisions | Decision Intelligence News | Scoop.it

How can we leverage our understanding of human physiology, neuroscience, and technology to guide and improve the decision making process for organizations and teams?

Lorien Pratt's insight:

Great article by Kasia Smith about how we can get better at decision making. Super important because decisions about invisible things: covid-19, climate, inequality, and more - will arguably determine the fate of the human race.

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Decision Intelligence In The Time Of COVID-19

Decision Intelligence In The Time Of COVID-19 | Decision Intelligence News | Scoop.it

In my situation, I believe that DI could have assisted me with the best action to take to achieve my ultimate goal, which is to drive engineering pride across SAP. …

 

While we may be facing the biggest threat of our lifetime, the good news is that Decision Intelligence (DI) can leverage AI as well as epidemiological, social, and other knowledge sources to help. Including beautiful visualizations, DI can be used by policymakers, media, business leaders and individuals, to make and communicate the impact of their decisions in a complex world.

Lorien Pratt's insight:

It is time for the Covid-19 era to become the decision intelligence era. Over the past months we have seen thousands of coronavirus decisions play out around the world. Some have saved lives and prevented suffering. Others have cost lives and created misery. We are still early days in this pandemic. We can leverage DI and DI tools to improve our future decisions. Even modest improvements in the quality of decisions can prevent huge amounts of death and suffering.

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ComputerAmerica: Quantellia, Decision Intelligence

The human-computer partnership is the future. Decision Intelligence (DI) gives us a formal way to integrate AI into existing decision making. Just having a structured way of thinking through complex decisions can really move the needle, and especially on big problems, even five percent can save lives or save money.

Lorien Pratt's insight:

DI is inter-disciplinary. As I have talked to decision makers in governments and companies worldwide, I have learned that where the innovation has to occur is in the interstitial spaces between disciplines. It’s not just where exciting developments can be built, it’s where they’re desperate for solutions.

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Link is a finalist for the prestigious 2020 PROSE award in Business, Management and Finance

Link is a finalist for the prestigious 2020 PROSE award in Business, Management and Finance | Decision Intelligence News | Scoop.it

Since 1976, the Association of American Publishers’ awards for Professional and Scholarly Excellence (PROSE Awards) have recognized publishers who produce books, journals, and digital products of extraordinary merit that make a significant contribution to a field of study in the humanities, biological and physical sciences, reference and social sciences.

Lorien Pratt's insight:

Dr. Pratt’s book Link: How Decision Intelligence Connects Data, Actions, and Outcomes for a Better World points out that most businesses review basic numbers, then make tactical and strategic decisions.  Most of the time, the review is based on historical or current numbers, and the task of thinking about how decisions will interact with the future is left as an exercise that happens inside the decision makers’ heads.  We can do much better.   

 

If we work backwards from business outcomes using a decision intelligence approach, we not only can integrate data, AI, and human expertise at multiple points in the decision process, we create a vehicle for exploring multiple futures and bringing forward simulation into the boardroom. 

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Ten scientific reasons in support of airborne transmission of SARS-CoV-2

Ten scientific reasons in support of airborne transmission of SARS-CoV-2 | Decision Intelligence News | Scoop.it

"Decades of painstaking research, which did not include capturing live pathogens in the air, showed that diseases once considered to be spread by droplets are airborne.[4] Ten streams of evidence collectively support the hypothesis that SARS-CoV-2 is transmitted primarily by the airborne route.[5]"

Lorien Pratt's insight:

One of the consequences of a lack of a decision intelligence bridge from research to decision makers, is that important findings like this are slow to be disseminated, and slower to be implemented as part of personal or organization decisions.  We ignore this "last mile" action challenge at our peril.

Lorien Pratt's curator insight, April 21, 3:50 PM

One of the consequences of a lack of a decision intelligence bridge from research to decision makers, is that important findings like this are slow to be disseminated, and slower to be implemented as part of personal or organization decisions.  We ignore this "last mile" action challenge at our peril.

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FICO Announces New Virtual Event, "Success Realized: Digital

FICO Announces New Virtual Event, "Success Realized: Digital | Decision Intelligence News | Scoop.it

"Building decision intelligence applications and delivering prescriptive analytics wherever and whenever needed is challenging in the best of times. Establishing a future-proof platform with analytic and AI powered insights, state-of-the-art optimization, and decision rules solutions can help businesses transform into customer-centric, automated and intelligent enterprises."

Lorien Pratt's insight:

We've been tracking FICO as one of the most important decision intelligence companies for a few years. Here's its current position.

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Orphaned Analytics: The Great Destroyers of Economic Value - Data Science Central

Orphaned Analytics: The Great Destroyers of Economic Value - Data Science Central | Decision Intelligence News | Scoop.it
Orphaned Analytics are one-off Machine Learning (ML) models written to address a specific business or operational problem, but never engineered for sharing, re-use and continuous-learning and adapting.
Lorien Pratt's insight:

This article doesn't talk about decision intelligence directly, but including ML models into an open architecture (like the World Wide Decision Web - WWDW) is an important future direction in making machine learning models reusable.

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Understanding what we mean by “Decision” in ML/AI/DI

Understanding what we mean by “Decision” in ML/AI/DI | Decision Intelligence News | Scoop.it
In artificial intelligence, machine learning, decision intelligence, statistics, and science, we use the word “decision” to mean a lot of things. Let’s tease out some distinctions:
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How to choose between buy, build, and hybrid resourcing for machine learning projects

How to choose between buy, build, and hybrid resourcing for machine learning projects | Decision Intelligence News | Scoop.it
Are you thinking: “I’ve heard that AI can provide some value to my organization?” but wondering where to start?
Lorien Pratt's insight:

Good judgment about applied AI is an important part of many DI project.  Here's how to think about how to resource this function.

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Introducing the Alliance for Decision Education

Introducing the Alliance for Decision Education | Decision Intelligence News | Scoop.it
Our mission is to improve lives by empowering students with essential skills and dispositions for making better decisions
Lorien Pratt's insight:

This looks like a great organization!  Looking forward to integrating their work with AI/ML/DI.

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Modeling Software Once Led Us to the Precipice of Nuclear War. What Will AI Do?

Modeling Software Once Led Us to the Precipice of Nuclear War. What Will AI Do? | Decision Intelligence News | Scoop.it

"What could happen when we start using artificial intelligence and machine learning to shape policy? ...The Pentagon must heed the lessons of RYAN and Able Archer amid its artificial-intelligence aspirations."

Lorien Pratt's insight:

Is anybody seriously considering using AI and ML to shape policy without rigorous human oversight / QA / testing / humans deeply and profoundly in the loop?   AI/ML do not understand the structure of action-to-outcome pathways, and even if they did, the future is never like the past.  So I wonder why this is even on the table, and I suspect that it's been colored by AI hype. What do you think?

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Taking the Right Decisions in the COVID-19 Crisis

Taking the Right Decisions in the COVID-19 Crisis | Decision Intelligence News | Scoop.it
To be able to spot business sense in data and find a true answer to the initially asked questions at the required time and adapted to the audience, result visualization is crucial. Humans only have a limited capacity to process information. This is why insight-driven organization’s intelligent tools that serve people by producing target-group specific dashboards ease the decision-making process. In the event of missing or simply not identifiable capabilities in your workforce, the most efficient solution is to get a professional data analyst aboard. In order to create C-level insights and derive first implications a special skill mix between science and art is required. 
Lorien Pratt's insight:

Deloitte is completely right to move from data-driven to insight-driven thinking and organizations. And they're directly on target, as few others are, in understanding the importance of visual thinking to this process. However, insights alone stop short of visualizing how actions lead to outcomes, which is how DI would layer on top of Deloitte's offering. 

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Latest Big Data and Analytics Trends to Consider in 2021

Latest Big Data and Analytics Trends to Consider in 2021 | Decision Intelligence News | Scoop.it
It is expected that many organizations will have analysts practicing decision intelligence including decision modeling in the future.
Lorien Pratt's insight:

We were right!

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DI leads the way to industrialized AI

DI leads the way to industrialized AI | Decision Intelligence News | Scoop.it

The industrialization of AI platforms enables the reusability, scalability and safety of AI, which accelerates its adoption and growth. This industrialization aims at getting new adopters of AI on par with early adopters. 

 

According to a recent Gartner survey, the C-suite is steering AI projects, with nearly 30% of projects directed by CEOs. Having the C-suite in the driver’s seat accelerates AI adoption and investment in AI solutions.

 

For example, decision intelligence indicates that companies want to use AI to make better decisions faster, such as selecting best treatment options for patients or accelerating discovery and prevention of anomalies and vulnerabilities.

Lorien Pratt's insight:

Decision Intelligence has now occupied the Gartner Hype Cycle for two years: it's here to stay.

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‘Tell me what to do! Please!’: Even experts struggle with coronavirus unknowns

‘Tell me what to do! Please!’: Even experts struggle with coronavirus unknowns | Decision Intelligence News | Scoop.it

Brian Nosek, a University of Virginia psychology professor who has devoted his career to making scientific data more reliable and trustworthy, is frustrated. Like everyone else, he's trying to understand the pandemic, particularly in his own community of Charlottesville, and in California, where he has family.

 

So he wonders: Where is the virus spreading? Where is it suppressed? Where are people social distancing as they should, and where are they not? Where will he and his family be safe?

 

In this pandemic, we're swimming in statistics, trends, models, projections, infection rates, death tolls. Nosek has professional expertise in interpreting data, but even he is struggling to make sense of the numbers.

 

“What's crazy is, we're three months in, and we're still not able to calibrate our risk management. It's a mess,” said Nosek, who runs the Center for Open Science, which advocates for transparency in research. “Tell me what to do! Please!”

Lorien Pratt's insight:

Decision Intelligence (DI) lets us decide what to do. DI manages data overload and lets us focus on a specific decision. Covid-19 safety decisions do not require holding all the global, aggregated statistics and projections in your head. Most critical decisions address risks at point in time for a specific facility or activity; they require not mountains of data, but understanding how, in this time and place, actions lead to outcomes.  As individuals, business owners, executives, or government officials, once we look at the causal links in a coronavirus decision, we can identify the subset of data that is actually relevant. And we can build AI and other models to render that data understandable and actionable and to let us update our decisions as the pandemic changes over time. DI gives us tools and a process to answer the Covid-19 question, “what should I do?” For an example of applying DI to covid-19 decision-making, look here.

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Congratulations to Decision Intelligence Tokyo. Omedetou gozaimasu!

Congratulations to Decision Intelligence Tokyo. Omedetou gozaimasu! | Decision Intelligence News | Scoop.it

Decision Intelligence Tokyo (DIT) is a non-profit organization in Japan. DIT is dedicated to making actionable artificial intelligence (AI) for the prosperity of commons. DIT connects experts (AI, ML, data scientists, and engineers)—for the development of next-generation actionable AI—which coordinates human decision-makers with data, models, and others. Actionable future AI supports humans to make responsible decisions.

Lorien Pratt's insight:

One of the indicators that a discipline is moving up the Gartner Hype Cycle is that it generates books, videos, user groups, and conferences. The new Tokyo DI user group joins Link, videos by Lorien Pratt and Cassie Kozyrkov, the LinkedIn Applied Decision Intelligence group, and  the Responsible AI/DI Summit & Ecosystem (RAIDI) as evidence of DI’s growing importance

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