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Chapter 6 Conclusion
Pages 61-64

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From page 61...
... 3. There is a need to better understand the social implications of human-machine collaboration for decision making.2 Whether machines ought to "decide" when to pull the trigger has been 1 Artificial intelligence, cognitive science, computer science, data analytics, decision science, machine learning, natural language processing, neuroscience, psychology, statistics, systems engineering.
From page 62...
... hypotheses, to enable continuous learning by the system (e.g., so the system can learning how to predict an analyst's needs and preferences, to guide continuous ingesting of data and its metadata and fusing it into the existing data, to cue decision makers to relevant, unexplored data or behavior; and to facilitate the sharing of hypotheses and derived knowledge among team members (such as by developing languages that make it easy for decision makers to state what they want the data to tell them)
From page 63...
... CONCLUSION 63 The committee members found more questions than answers during the course of this study. Their observations, however, do not call into doubt the importance of future humanmachine collaboration for complex decision making as much as they underscore a present-day reality: The development of human-machine collaboration for complex decision making is still in its infancy relative to where cross-disciplinary research could take it over the next generation.


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