Continuous Decisioning

Arash Aghlara started a good discussion at LinkedIn: “Many times, based on the decisions that we execute on a specific case, we influence the future of the case. Although the case is the same but, it belongs to an altered situation where the decision we had executed has changed the situation of the case. Now, in this new state of the case, the already applied decision is either still applicable or we need a set of new decision models based on the new states of the case and the new situations the case belongs to.

The fact is that the case’s final outcome has not yet been determined by the first cycle of decision execution. We still need to continuously execute more decisions on the case until the final outcome is conclusive. Or we determine the outcome is inconclusive, so we need an alternative approach (manual review, domain expert input, marking the case infeasible, etc.) to finalize the case and find the best outcome for the case
.” Link

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Focus on Decision-Making Under Uncertainty

Meinoff Sellmann, a well-known expert in Operation Research (OR), gives this advice: “No surfer has ever surfed a wave by paddling to a place where others are already surfing the tube. In 2024, generative AI is the latest fashion. And guess what many OR researchers are looking at right now. OR, focus on your craft. Focus on decision-making under uncertainty. And be prepared for the next wave. It is coming.” Link

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LLMs and Attributed Provenance

George Keller Hart: “Large language models are potentially our civilization’s self blinding. How? By undermining our 5,000+ year heritage of written language – specifically because LLMs substitute memetics for attribution, breaking the first rule of shared, collective knowledge. Our vast corpus of recorded language has always rested on the provenance of each text, whether books, laws, correspondence, etc. – and across media formats as well. Attributed provenance is the foundation for evaluation and discernment, as opposed to LLMs that generate probabilistic ‘mimema’ – Greek for ‘imitations’.Link

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Tim Berners-Lee: 35 years of Internet

Tim Berners-Lee, the inventor of the web, marked the 35th anniversary of its creation (March 12, 1989) with a letter about the big challenges web technology faces as it moves towards its fourth decade of existence. He sees monopoly power and the exploitation of our personal data as the major issues currently keeping the web from reaching its potential. “The future hinges on our ability to both reform the current system and create a new one that genuinely serves the best interests of humanity.” Link

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Arash Aghlara: What is a Decision Model

“A decision model is a roadmap and blueprint of a business decision that depicts a holistic view of how a business decision is made. At its core, this blueprint is an executable artifact that uses multiple composite techniques to bring together smaller, more understandable, and self-sufficient decision units. It specifies how a decision is made using the relationship and dependencies between the decision units.

The decision model essentially acts as the coordinator between multiple decision units, passes information in, sends the outcomes of one unit to another, and proceeds until the decision is made. Once the model is defined, then each decision unit in the decision model can use different techniques and technologies such as business rules, AI/ML, data processing, workflow, algorithms, etc.” Link

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BBC-2024

Building Business Capability (BBC) comes to Loews Sapphire Falls Resort at Universal Orlando, Florida, on April 15 – 19, 2024. The conference enhances your ability to advance People, Product, Data, and Knowledge, to build your core leadership skills, to create a customer centric organization, and to deliver digital transformation. Link

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Linear Regression in DMN

In his recent post Bruce Silver wrote: “DMN is not optimized for machine learning algorithms, but it’s good enough for simple problems such as fitting a straight line to a set of data points, known as linear regression.  In this post we’ll look at two ways to do it.” Link

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Decision Intelligence at Gartner Summit

Decision intelligence will be well presented at Gartner Data & Analytics Summit that starts on Mar 11 in Orlando. In particular, Erick Brethenoux, Distinguished VP Analyst, will present “Decision Intelligence and Optimization Across Your Enterprise and Ecosystem”. Here is the abstract: “Faster and optimal decision-making is a competitive differentiator. But silo data, silo decisions and silo mentality are not cutting it in today’s global and highly interconnected business ecosystems. A more networked approach is required, bringing together technologies such as optimization, graph analytics and AI. This session will provide practical guidance to bring your decision intelligence to the next level.” View complete Agenda

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Decision-makers behind the curtain

Cassie Kozyrkov: When it comes to AI, which part am I most concerned about? The decision-maker behind the curtain. Forget creepy robots — if there’s anything to fear, it’s human negligence. Most people think of AI as a tool for decision-making, but it’s very much the product of decision-making…

  • Whose decision-making?
  • Did they have the skills needed?
  • Are we amplifying decision intelligence… or decision stupidity?
  • Who is making the decisions behind an AI system?
  • Which success metrics are they choosing to optimize for?
  • Which datasets are they selecting to train their models?
  • How do they know their system is safe to launch?
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What makes a system “real time”?

Roy Schulte wrote an interesting article about it. “Real time is whatever you need it to be, but with an eye toward speed and using some reasonable constraints. In both engineering and business, real time is all about acting in the “right time” for that particular process. You need to identify the point of diminishing returns where going faster doesn’t improve the results or where the costs of going faster outweigh the benefits of going faster. Real time refers to the duration of the end-to-end process from the observation of new information to the execution of the response. It’s often useful to analyze a process using the observe-orient-decide-act (OODA) loop” Link

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