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  1. Is your machine better than you?
    you may never know
    Author: Véricourt, Francis de; Gurkan, Huseyin
    Published: May 23, 2022
    Publisher:  ESMT Berlin, Berlin, Germany

    Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based... more

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    Verlag (kostenfrei)
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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 450
    Inter-library loan:
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    Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based prescriptions. This paper explores the extent to which a decision maker (DM) supervising a machine to make high-stake decisions can properly assess whether the machine produces better recommendations. To that end, we study a set-up, in which a machine performs repeated decision tasks (e.g., whether to perform a biopsy) under the DM's supervision. Because stakes are high, the DM primarily focuses on making the best choice for the task at hand. Nonetheless, as the DM observes the correctness of the machine's prescriptions across tasks, she updates her belief about the machine. However, the DM observes the machine's correctness only if she ultimately decides to act on the task. Further, the DM sometimes overrides the machine depending on her belief, which affects learning. In this set-up, we characterize the evolution of the DM's belief and overruling decisions over time. We identify situations under which the DM hesitates forever whether the machine is better, i.e., she never fully ignores but regularly overrules it. Moreover, the DM sometimes wrongly believes with positive probability that the machine is better. We fully characterize the conditions under which these learning failures occur and explore how mistrusting the machine affects them. Our results highlight some fundamental limitations in determining whether machines make better decisions than experts and provide a novel explanation for human-machine complementarity.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/259795
    Series: ESMT working paper ; 22, 02
    Subjects: machine accuracy; decision making; human-in-the-loop; algorithm aversion; dynamic learning
    Scope: 1 Online-Ressource (circa 42 Seiten), Illustrationen
  2. Relación entre estilos de liderazgo y funciones ejecutivas de planificación y toma de decisiones en oficiales jefes de la Armada Argentina
    Author: Martínez, Luis Marcelo; Canga, Lucas
    Published: [2022]
    Publisher:  Universidad del CEMA, Buenos Aires, Argentina

    The objective of this research was to analyze the relationship between leadership styles and executive functions of planning and decision-making, in chief officers of the Argentine Navy, who are working as students of the Command and General Staff... more

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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 245
    Inter-library loan:
    No inter-library loan

     

    The objective of this research was to analyze the relationship between leadership styles and executive functions of planning and decision-making, in chief officers of the Argentine Navy, who are working as students of the Command and General Staff course at the Naval War School. A survey was carried out where a sample of 21 chief officers of the Argentine Navy in the rank of Lieutenant Commander was analyzed, in a population of 153 qualified for command function, whose age range is between 37 and 46 years old, resulting in an average of 40.71 years and an average length of service in the force of 20.88 years, ranging between 18 and 24 years of service. This sample was made up of officers from three different ranks, naval (n = 9), naval aviators (n = 6) and marines (n = 6). The results obtained indicate the absence of correlation between the leadership styles that these officers demonstrated and the skills in the executive functions of decision-making and planning. Likewise, it was found that the values obtained from the tests carried out yielded results that allow to conclude that the chief officers of the Argentine Navy in the Lieutenant Commander hierarchy possess very high competencies in decision-making and planning, as well as oriented leadership profiles to transformational leadership. The conclusions is that these competencies are significant for the operational and tactical leadership of the means and personnel in the Argentine Navy.

     
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    Source: Union catalogues
    Language: Spanish
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/260520
    Series: Array ; nro. 826 (Febrero 2022)
    Subjects: leadership styles; decision making; planning; management and leadership; ArgentineNavy; estilos de liderazgo; toma de decisiones; planificación; conducción y liderazgo,Armada Argentina
    Scope: 1 Online-Ressource (circa 74 Seiten), Illustrationen
  3. Social distancing and risk taking
    evidence from a team game show
    Author: Bourgeon, Jean-Marc; Sousa, José de; Noir-Luhalwe, Alexis
    Published: November 2022
    Publisher:  CESifo, Munich, Germany

    We examine the risky choices of pairs of contestants in a popular radio game show in France. At one point during the COVID-19 pandemic the show, held in person, had to switch to an all-remote format. We find that such an exogenous change in social... more

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    Verlag (kostenfrei)
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    Signature:
    DS 63
    Inter-library loan:
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    We examine the risky choices of pairs of contestants in a popular radio game show in France. At one point during the COVID-19 pandemic the show, held in person, had to switch to an all-remote format. We find that such an exogenous change in social context affected risk-taking behavior. Remotely, pairs take far fewer risks when the stakes are high than in the flesh. This behavioral difference is consistent with prosocial behavior theories, which argue that the nature of social interactions influences risky choices. Our results suggest that working from home may reduce participation in profitable but risky team projects.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/267296
    Series: CESifo working papers ; 10063 (2022)
    Subjects: COVID-19; social distancing; social pressure; decision making; risk
    Scope: 1 Online-Ressource (circa 47 Seiten), Illustrationen
  4. Expert adoption of composite indices
    a randomized experiment on migrant resettlement decisions in Bangladesh
    Author: Kolstad, Ivar; Karim, Azreen; Lujala, Päivi; Wiig, Arne
    Published: [2022]
    Publisher:  Chr. Michelsen Institute (CMI), Bergen, Norway

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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    VS 792
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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9788280628251
    Other identifier:
    hdl: 11250/3029990
    Series: CMI working paper ; 2022, number 03 (September 2022)
    Subjects: Migration; climate change; resettlement index; decision making; Bangladesh; discretechoice experiment
    Scope: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  5. Is your machine better than you?
    you may never know
    Author: Véricourt, Francis de; Gurkan, Huseyin
    Published: Dec 8, 2022
    Publisher:  ESMT Berlin, Berlin, Germany

    Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based... more

    Access:
    Verlag (kostenfrei)
    Resolving-System (kostenfrei)
    Resolving-System (kostenfrei)

    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 450
    Inter-library loan:
    No inter-library loan

     

    Artificial intelligence systems are increasingly demonstrating their capacity to make better predictions than human experts. Yet, recent studies suggest that professionals sometimes doubt the quality of these systems and overrule machine-based prescriptions. This paper explores the extent to which a decision maker (DM) supervising a machine to make high-stake decisions can properly assess whether the machine produces better recommendations. To that end, we study a set-up in which a machine performs repeated decision tasks (e.g., whether to perform a biopsy) under the DM's supervision. Because stakes are high, the DM primarily focuses on making the best choice for the task at hand. Nonetheless, as the DM observes the correctness of the machine's prescriptions across tasks, she updates her belief about the machine. However, the DM is subject to a so-called verification bias such that the DM verifies the machine's correctness and updates her belief accordingly only if she ultimately decides to act on the task. In this set-up, we characterize the evolution of the DM's belief and overruling decisions over time. We identify situations under which the DM hesitates forever whether the machine is better, i.e., she never fully ignores but regularly overrules it. Moreover, the DM sometimes wrongly believes with positive probability that the machine is better. We fully characterize the conditions under which these learning failures occur and explore how mistrusting the machine affects them. These findings provide a novel explanation for human-machine complementarity and suggest guidelines on the decision to fully adopt or reject a machine.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/267687
    Series: ESMT working paper ; 22, 02 (R1)
    Subjects: machine accuracy; decision making; human-in-the-loop; algorithm aversion; dynamic learning
    Scope: 1 Online-Ressource (circa 54 Seiten), Illustrationen
  6. Decision making in the pre-deal stage of acquisitions
    toward an improved cognitive perspective
    Author: Bian, Di
    Published: [2022?]

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    Source: Union catalogues
    Language: English
    Media type: Dissertation
    Format: Online
    Other identifier:
    hdl: 20.500.14171/108233
    Subjects: Mergers and Acquisitions; Kognition; Entscheidungsprozess; EDIS-5211; cognition; decision making; Mergers and acquisitions
    Scope: 1 Online-Ressource, Illustrationen
    Notes:

    Sperrfrist: Zugriff auf den Volltext ab 17.09.2024

    Dissertation, Universität St. Gallen, 2022