Does providing AI recommendation ease cognitive process in forecasting during uncertain period?
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Providing AI recommendations can indeed ease the cognitive process in forecasting during uncertain periods. AI advisory systems, equipped with causal models and decision-making frameworks, help link potential actions to outcome probabilities, aiding in decision-making under uncertainty . Additionally, AI models can reduce prediction uncertainty, overcome data sparsity, and enhance item recommendation accuracy by leveraging auxiliary information through multitask learning approaches . Furthermore, when individuals engage deeply with AI explanations, they not only make better decisions but also experience learning gains, showcasing the cognitive benefits of interacting with AI recommendations . Human decision makers in AI-assisted scenarios tend to adopt AI recommendations based on their judgment, confidence levels, and the stakes involved in the decision-making task .
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11 Feb 2022 | Not addressed in the paper. |
3 Citations | Yes, AI recommendation eases cognitive processes in forecasting during uncertainty by explaining decisions through causal models, aiding in understanding outcomes and risks, as discussed in the paper. |
25 Apr 2022 | In AI-assisted decision making, human cognitive processes are influenced by AI recommendations, impacting utility evaluation and action selection, potentially easing forecasting during uncertain periods. |
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