Harvard Business Review under the section “Organizational Decision Making” published the article “Leaders: Stop Confusing Correlation with Causation“. It explains how we could eliminate many problems and tons of noise just by recognizing that correlation is not causation. Link
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Modern enterprises quickly evolved from monolithic to microservices architectures and CI/CD pipelines become the common practice. Correspondingly different Decisioning Platforms made necessary adjustments to support CI/CD security, continuous integration and delivery/deployment requirements. Here are recent publications devoted to different decision managers in CI/CD environments:
Please provide references to how other decisioning platforms support CI/CD requirements.
Pierre Haren wrote at LinkedIn: “For once, today, I will not have an answer but a question. It is about the worldwide supply chain, and the question was asked by David Simchi-Levi, MIT professor on a recent phone call: can we predict when the current supply chain issues will be fixed? I came across two opposite documents yesterday: a piece by Will Douglas Heaven in MIT’s Technology Review (https://lnkd.in/eRUQSHVG ) which quotes Professor Simchi-Levi, and a contrasting piece by an actual truck driver (https://lnkd.in/eDqWfJWQ )… If you have time to read it and you have a suggestion, we would love to hear it. The well-being of lots of people depend on a solution to that gnarly problem.”
The AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business value. The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. Link
Peter Norvig is a well-known name in AI. He co-wrote Artificial Intelligence: A Modern Approach, an introductory textbook used by some 1,500 universities worldwide, and he’s taught hundreds of thousands of students through his courses on online education platform Udacity. In this interview, Peter discusses his move from Google’s Director of Research to Stanford, building a human-focused AI curriculum, and broadening access to education. Link
“One way to think of AI is as a process of optimization — finding the course of action, in an uncertain world, that will result in the maximum expected utility. In the past, the interesting questions were around what algorithm is best for doing this optimization. Now that we have a great set of algorithms and tools, the more pressing questions are human-centered: Exactly what do you want to optimize? Whose interests are you serving? Are you being fair to everyone? Is anyone being left out? Is the data you collected inclusive, or is it biased?“
An interesting discussion has started at LinkedIn around this possible answer:
All 5 elements of this formula have been questioned: Link
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