Abstract
AbstractAgents evaluate their performances to assess progress, learn, and improve. In doing so, they refer to criteria of various kinds. Some criteria are deeply encoded in mental models, organizational procedures, or cultural norms and logics, while other evaluative criteria are adaptive and may upregulate or downregulate, depending on the agent’s goals, expectations, and context. Here, too, digitalization is transformative. Artificial agents bring unprecedented power to the evaluation of performance, including the rapid intra-cyclical evaluation of ongoing processes. These mechanisms support feedforward guidance in real time. Therefore, when human and artificial agents combine in the evaluation of augmented performance, they face additional risks. Artificial evaluative processing could be fast and precise, while at the same time, human evaluation may be relatively sluggish and imprecise. Overall evaluations of performance could be distorted and dysfunctional.
Highlights
Especially in task domains which require more rapid or discriminate evaluation
The foregoing analysis suggests at least four different metamodels of evaluation, in terms of the upregulation or downregulation of human and artificial processes
Other situations will combine the downregulation of human evaluative processes, with the upregulation of artificial ones
Summary
Agents consistently evaluate their performances to measure progress toward goals, to assess the efficacy of action, and to learn. Studies show that some features of collectives can be relatively stable over time, owing to imprinting and isomorphism within institutional fields, and deeply embedded cultural norms (Hannan et al, 2006; Marquis, 2003) Collectives reference such criteria in the evaluation of performance. Studies show that collectives reference adaptive criteria which reflect changing contexts, goals, and commitments, plus different levels of sensitivity to variance (Hu et al, 2011). Such variability mitigates the negative effects of low evaluations of performance. Digitalization brings significant opportunities and risks to the evaluation of performance
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