提高专家技术预测的策略。
A strategy to improve expert technology forecasts.
机构信息
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213.
Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213
出版信息
Proc Natl Acad Sci U S A. 2021 May 25;118(21). doi: 10.1073/pnas.2021558118.
Forecasts of the future cost and performance of technologies are often used to support decision-making. However, retrospective reviews find that many forecasts made by experts are not very accurate and are often seriously overconfident, with realized values too frequently falling outside of forecasted ranges. Here, we outline a hybrid approach to expert elicitation that we believe might improve forecasts of future technologies. The proposed approach iteratively combines the judgments of technical domain experts with those of experts who are knowledgeable about broader issues of technology adoption and public policy. We motivate the approach with results from a pilot study designed to help forecasters think systematically about factors beyond the technology itself that may shape its future, such as policy, economic, and social factors. Forecasters who received briefings on these topics provided wider forecast intervals than those receiving no assistance.
对未来技术的成本和性能的预测通常被用来支持决策。然而，回顾性研究发现，许多专家做出的预测并不十分准确，而且往往过于自信，实际价值经常超出预测范围。在这里，我们概述了一种混合的专家征询方法，我们相信这可能会提高对未来技术的预测。所提出的方法迭代地结合了技术领域专家的判断和那些对技术采用和公共政策等更广泛问题有知识的专家的判断。我们用一项旨在帮助预测者系统地思考可能影响技术未来的技术本身以外的因素（如政策、经济和社会因素）的试点研究的结果来说明该方法。接受了这些主题介绍的预测者提供的预测区间比没有接受帮助的预测者提供的预测区间要宽。
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