Lorien Pratt 09月25日
决策智能的探索与应用
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决策智能(DI)在人工智能领域填补了数据不足但需即时决策的空白,它结合人类专长与现有数据,通过复杂系统模拟和优化方法提升决策质量。DI关注行动与结果的映射,适用于影响重大的场景,如商业策略、公共政策和风险管理。它区别于依赖大量数据的机器学习分类与回归,更强调在信息不完整时做出更优选择。

💡决策智能(DI)的核心是解决数据不完整但需快速做出重大影响决策的问题,它利用人类专业知识与部分数据,通过复杂系统模拟和优化方法提升决策质量。

🔄DI强调行动到结果的因果映射,通过模拟不同决策的潜在后果,帮助决策者在信息不完整时选择最优路径,这与依赖大量数据的机器学习分类和回归形成对比。

⚙️DI的典型应用场景包括商业策略制定、公共政策和风险管理,它通过整合因果模型、机器学习、经济学和复杂系统分析,提供比传统方法更全面的支持。

📊在方法论上,DI结合了人类判断与量化分析,例如使用复杂系统仿真验证假设,或通过优化算法确定多目标下的最佳行动组合,强调决策的动态性与适应性。

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:

Decision TypeNameQuestion answeredPrimary information SourceTypical success criterionTypical method
AML classification“Decisions That”: “What is this picture?” “What disease does this person have?” “Is this a cat?”DataTrue positive, true negativeSupervised learning
BML regression“Decision about a prediction”: “What will be the Covid-19 incidence next month?” “What will be this security’s price next month?”DataMean squared error, R^2Supervised learning
CDecision intelligence (forward model)Decision to take an action, action-to-outcome mapping: “If I take this action, in this context, what will be the outcome?”Humans (causal model), ML, economics, complex systems models, much more (causal model links)Correct mapping of actions to outcomesComplex systems simulation
DDecision intelligence (optimization)“Given my set of possible actions, what is the best set of actions to take to meet my goals”(same as above)Best set of decisions to reach multi-objective outcomesComplex systems simulation, optimization
EReinforcement learningPolicy creation: “For each state that I can be in, what is the best next action?” (policy)Data and simulationBest set of policies to maximize value of objective functionReinforcement learning simulation
Types of decisions in ML/RL/DI

Cassie Kozyrkov and I have realized that there’s unmet need to fill the space marked “DI”, above, where:

    We don’t necessarily have data for the entire decision, yet…people need to make this decision today, without waiting to have time to gather the data, and…the decision has big impact, and…we want to make better decisions, and we have some, if not all, data and human expertise available to us yet it’s not being well utilized.

We, along with a few thousand others, have realized that this is an important, yet massively under-treated, corner of the decision problem formulation space.

You can learn about it in this course: Getting Started with Decision Intelligence.

“Decision intelligence is the discipline of turning information into better actions at any scale.” Cassie Kozyrkov, Head of Decision Intelligence, Google

“Decision intelligence answers the question, ‘If I make this decision today, which leads to this action, what will be the outcome tomorrow?’—Lorien Pratt, Chief Scientist, Quantellia

Do you agree? Lately, I’ve heard a case that “Decision Intelligence” should be expanded to include both A and B above.  What do you think?

Thanks to @thenatlog, @neuralnets4life, and @twimlai for inspiring this post

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决策智能 人工智能 复杂系统 优化算法 商业策略
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