人工智能的新阶段：决策智能2.帮助每个人企业和个人绘制思想和决策的DNA3.书中提供了优良方法绘制因果决策图4.各大科技公司都在运用的决策智能方法论
「简介」最发达的科技为何不能解决最复杂最重要的问题？缺失的实际上是决策智能。这本书是关于如何以一种新的方式思考决策，与古老的思维模式相联系，并由无限的新信息来源和合作提供新信息。这个领域被称为决策智能(DI)。本书将当前最敏锐的思维从决策智能、人工智能、因果分析和行为经济学整合到一种任何人都可以使用的决策方法中。

Translation: 1. A new stage of artificial intelligence: decision-making intelligence 2. To help everyone, companies and individuals draw the DNA of thoughts and decisions 3. The book provides excellent methods to draw causal decision-making diagrams 4. Decisions that are used by major technology companies Intelligent methodology
"Introduction" Why can't the most advanced technology solve the most complex and important problems? What is missing is actually the decision-making intelligence. This book is about how to think about decision-making in a new way, connect with old modes of thinking, and provide new information from infinite new sources and collaborations. This field is called Decision Intelligence (DI). This book integrates the current sharpest thinking from decision intelligence, artificial intelligence, causal analysis, and behavioral economics into a decision-making method that anyone can use.

"Decide as a team. Include diverse views. Engage people & drive performance with transparent decision-making....Know who decided what and why. Be accountable. Improve decision-making by measuring decision results."

The opportunity cost of these poor decisions is massive. In a 2019 Gartner study, the firm found that on average, S&P500 companies can improve EBITDA by as much as 3% (absolute increase by improving decisions). They measured good decisions vs. bad decisions based on exception rates and a few other factors. This is a nearly 30% improvement based on average EBITDA of S&P500 firms, or a $700 billion opportunity in EBITDA expansion for S&P500 companies.

...

decision systems of record allow us to go back to previous decisions, track how they did vs. expectations, understand where things went well and most importantly learn and disseminate decision best practices across the organization."

Bain & Company that found a company’s past decision effectiveness is 95 percent correlated with financial performance one year in the future. So, while it may be true that a company’s past financial performance does not guarantee future returns, it turns out that a company’s past decisions are an excellent indicator of future growth, good or bad.

"Our goal in the Prescription phase of the competition is to develop an interpretable, data-driven and flexible prescription framework that would be usable by non machine-learning experts, such as citizens and policy makers in the Valencian Government. Our design principles are therefore driven by developing interpretable and transparent models.

Given the intervention costs, it automatically generates up to 10 Pareto-optimal intervention plans. For each plan, it shows the resulting number of cases and overall stringency, its position on the Pareto front and the activation regime of each of the 12 types of interventions that are part of the plan."

"In scathing report, State Comptroller cites lack of preparation, sidelining of experts, incoherent decision-making, failure to learn from mistakes, vast enforcement discrepancies...While the report criticizes a range of issues relating to efforts to prevent the spread of the virus, Englman, a Netanyahu appointee, saves some of his harshest criticism for the overall mechanism under which decisions were made, saying a number of key rulings were made by the former premier without full cabinet approval or proper oversight." [emphasis mine]

The biggest priorities and blockers to the decision making process, according to business leaders

"In such uncertain times, many companies accepted to fly blind. Costing organizations an estimate of $4.3T ($4,300,000,000,000) of lost revenue per year — in the US alone (Signal AI 2021). And in fact, the average S&P500 company spends an average of $250M per year on ineffective decision-making (McKinsey 2019)."

Chances are that many of your attendees have started to recognize a gap in the data science stack: decision makers think in terms of actions and outcomes, yet data science provides answers, insights, facts, and predictions. So, I’ll start by explaining this BI “last mile” gap, then talk about how decision intelligence is a decade-old field that fills it. 

I’ll describe a second important problem addressed by Decision Intelligence (DI), which is that technology assets aren’t well integrated: we typically have a number of statistical models, some machine learning models, a BI tool, a data lake, and sources of data like Microsoft Sharepoint and SAP. As it turns out, the action-to-outcome pattern also provides a mechanism to integrate these BI assets together. 

A unique conference focused on what Business and IT leaders need to be successful with Business Intelligence.

"In the heat of decision-making, it's tempting to go with the flow and accept any suggestion that sounds good. However, not all suggestions are created equal.

Daniel Kahneman, the psychologist turned Nobel Laureate for Economics, found out that executives use two categories of decision-making: swift, almost automatic decisions and slow, deliberate ones.
Teams that have spent time on shared insights, especially when focusing on the things they agree on, can get into a decision flow that feels very, very secure. The decision feels safe because everyone agrees after a lot of arguments have been discussed.
However, being in a flow also reduces our ability to stop and think things through. We're just too busy with the flow!"

"As the U.S. heads toward the winter, the country is going round in circles, making the same conceptual errors that have plagued it since spring...

The grand challenge now is, how can we adjust our thinking to match the problem before us?” says Lori Peek, a sociologist at the University of Colorado at Boulder who studies disasters. Here, then, are nine errors of intuition that still hamstring the U.S. pandemic response, and a glimpse at the future if they continue unchecked. The time to break free is now."

"Linear sequential reasoning is no longer sufficient in our digital age. The twist in our thinking comes from this: Our digital age transports us back into the unified field experience of oral and auditory modes [even if using a visual technology, its universal nature is analogous to traditional oral communication]. This Unified Field is the multi-directional sphere in which the web/cloud operates and where we can address complexity in new ways. *No you won’t find this in a Wikipedia search. We are traversing new ground here."

You already know this (implicitly). Virtually any MMOP (massively multiplayer online game or more commonly, MMO) operates as a Unified Field. Most successful technology companies operate as Unified Fields for both database management, and operations (Amazon, Uber, Facebook, Google). This is good news. Problems can be solved faster and more easily when considered in the frame of this Unified Field reality.

At Accenture, we found that “change management” was the bottleneck to the systemic uptake of new technologies. It was not learning the new technologies that our digital era has birthed but in the limiting mindset of the management class in deploying these technologies."

n a recent survey, Gartner found that 65% of decisions made are more complex (involving more stakeholders or choices) than they were two years ago. The current state of decision making is unsustainable.

Welch outlines the challenges facing government leaders as decision-making is increasingly complex, continuous, and contextual. She also explains how DI reengineers decision-making through data driven approaches that leverage human and machine interactions.

"I also would like to mention that I was following Dr Lorien Pratt from the very beginning and that her promotion and development of the Decision Intelligence concept was a very important influence. However, when I started to offer the first course on Decision Intelligence at the undergraduate level of the University of St.Gallen labelled as “Dealing with Uncertainty in Dynamic Markets” in 2014, I realized that students need some sort of clear visualization — a NAVIGATOR — to better connect the dots. Over a couple of years, I came up with the following Decision Intelligence Navigator which I use nowadays to teach students and executives alike the key ideas of what I believe Decision Intelligence is all about."

Now, we need to make a different kind of story about the future. One that focuses not just on the technologies, but on the systems in which these technologies will reside. The opportunity to focus on a future that holds those systems – and also on a way of approaching them in the present – feels both immense and acute. And the ways we might need to disrupt the present feel especially important in this moment of liminality, disorientation and profound unease, socially and ecologically. In a present where the links towards the future seem to have been derailed from the tracks we’ve laid in past decades, there is an opportunity to reform. Ultimately, we would need to think a little differently, ask different kinds of questions, bring as many diverse and divergent kinds of people along on the journey and look holistically and critically at the many propositions that computing in particular – and advanced technologies in general – present.

"Enterprises spend tens of millions of dollars deploying technologies to deliver deeper and faster insights. While there’s an explosion of insights available to decision-makers, their ability to decide and act on them is still very limited. The reason is simple: the last-mile of analytics – the process of transforming multiple insights from a variety of sources to a recommendation for action – is broken."

"Leading analyst firms, such as Gartner Research, are predicting that decision intelligence will become a major factor in enterprise decision-making in the near future. In fact, Gartner predicts that 33 percent of large enterprises will have analysts that practice decision intelligence by 2023."

"...a number of these organisations claim to be ‘systems thinkers’. In fact, the one that was the very worst to deal with, having excessive phone menus that gave a huge list of ‘codes’ for what department you might want to talk to, makes the biggest claim to be systems thinkers of all of the organisations I encountered"

‘Citizens don’t understand that someone is doing this hard job and sometimes they are going to be wrong and if they’re wrong, it’s not because they’re idiots or malicious or corrupt; it’s that the job is making decisions in conditions of uncertainty."

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"AI greats such as Lorien Pratt and Google’s chief decision scientist Cassie Kozyrkov are quick to say that the ultimate business advantage in using AI is decision intelligence — the automation of the full action-to-outcome process."