Thursday, November 11, 2021

g-f(2)647 THE BIG PICTURE OF THE DIGITAL AGE (11/11/2021), HBR, Managing AI Decision-Making Tools




ULTRA-condensed knowledge


"g-f" fishing of golden knowledge (GK) of the fabulous treasure of the digital ageArtificial Intelligence, Managing AI Decision-Making Tools (11/11/2021)  g-f(2)426 


OPPORTUNITY, HBR 

Managing AI Decision-Making Tools 


      • It’s important to recognize that these systems will evolve over time, enabled by new technology, an organizations’ desire to make ever more surgical decisions, and greater management confidence in automation. You must decide what level of human management is possible and desirable, and your appetite for risk and iteration. There is no correct answer.
      • Whichever model you adopt, we believe it’s critical to put the AI on the org chart and in the process design to ensure that human managers feel responsible for its output. 
      • To succeed, you need to understand the different ways you can interact with AI and pick the right management option for each of your AI systems.


        Genioux knowledge fact condensed as an image




        References





        Extra-condensed knowledge


        Lessons learned, HBR 


            • The four main management models we developed vary based on the level and nature of the human intervention: We call them HITL, HITLFE, HOTL, HOOTL. It’s important to recognize this is a spectrum, and while we have pulled out the key management models, there are sub-variants based on the split between human and machine, and the level of management abstraction at which the human engages with the system.



            Condensed knowledge



            Lessons learned, HBR 

            The Range of Management Options

                1. Human in the loop (HITL): A human is assisted by a machine. In this model, the human is doing the decision making and the machine is providing only decision support or partial automation of some decisions, or parts of decisions. This is often referred to as intelligence amplification (IA).
                2. Human in the loop for exceptions (HITLFE): Most decisions are automated in this model, and the human only handles exceptions. For the exceptions, the system requires some judgment or input from the human before it can make the decision, though it is unlikely to ask the human to make the whole decision. Humans also control the logic to determine which exceptions are flagged for review.
                3. Human on the loop (HOTL): Here, the machine is assisted by a human. The machine makes the micro-decisions, but the human reviews the decision outcomes and can adjust rules and parameters for future decisions. In a more advanced set-up, the machine also recommends parameters or rule changes that are then approved by a human.
                4. Human Out of the Loop (HOOTL): In this model, the machine is monitored by the human. The machine makes every decision, and the human intervenes only by setting new constraints and objectives. Improvement is also an automated closed loop. Adjustments, based on feedback from humans, are automated.


                Some relevant characteristics of this "genioux fact"

                • Category 2: The Big Picture of the Digital Age
                • [genioux fact deduced or extracted from HBR]
                • This is a “genioux fact fast solution.”
                • Tag Opportunities those travelling at high speed on GKPath
                • Type of essential knowledge of this “genioux fact”: Essential Analyzed Knowledge (EAK).
                • Type of validity of the "genioux fact". 

                  • Inherited from sources + Supported by the knowledge of one or more experts.


                References


                “genioux facts”: The online programme on MASTERING “THE BIG PICTURE OF THE DIGITAL AGE”, g-f(2)647, Fernando Machuca, November 11, 2021, blog.geniouxfacts.comgeniouxfacts.comGenioux.com Corporation.


                ABOUT THE AUTHORS


                PhD with awarded honors in computer science in France

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