Decision Automation

Abstract

AbstractThis chapter takes on the difficult task of relating the key aspects of rapidly evolving decision automation – along with the emerging techno-informational reality – to the goals and the mechanics of organizational sensemaking. Framed more by examples than by ontologically clear definition, the notion of decision automation is nonetheless rooted in some long-established principles, even though more than any other aspect of organizational learning, it is tied to technological change. With that in mind, the overview of this broad domain of knowledge and practice begins with a high-level discussion of the key automation manifestations, ranging from decision support systems to autonomous decision systems, followed by an overview of automation-enabling data analytic techniques, all set in the context of contrasting mini-case studies. The second part of this chapter takes a speculative, forward-looking view on how the combination of artificial and human intelligence will likely fuel the next evolutionary chapter of human creative development, all framed in the broad context of human-machine interactions.KeywordsDecision automationMachine learningMachine learning – supervisedMachine learning – unsupervisedMachine learning – reinforcedArtificial neural networksDeep learningArtificial intelligenceDilemma of wicked problemsDiffusion of innovationCognitive diversity quotientMental models – machineLearning – multimodalCreativity