CRCNS US-German Research Proposal: Choice-induced biases in human decision-making

CRCNS 美德研究提案：人类决策中选择引起的偏见

• 批准号: 1912232
• 负责人: Alan Stocker
• 金额: $ 100万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1912232&HistoricalAwards=false
• 关键词: CRCNS; US; German; Research; Proposal

The choices we make not only influence how we remember the past but also how we will perceive the future. In both cases, our judgments are biased in favor of our preceding choice. Such choice-induced biases have been known for centuries. They affect our judgments in daily life including in situations where judgment errors are critical (e.g., medical diagnoses, scientific hypothesis testing, or political decisions). Why the human brain generates these biases and tends towards self-confirmation has long remained elusive. Supported by the Collaborative Research in Computational Neuroscience program, the proposed research will set out to identify the underlying computational and neural mechanisms of choice-induced biases in human decision-making. The proposed work employs a highly interdisciplinary approach that combines measures of behavior and brain activity with theory and computational modeling. It perfectly draws from the complimentary experimental and computational expertise of each PI and their laboratories. The goal is to develop and validate a novel theory of decision-making under uncertainty, in which choice-induced biases play a central role. Unraveling the source and function of choice-induced biases is not only critical for understanding the limits of human rationality but has also immediate and important implications for society at large. For example, the insights can help training of physicians to reduce judgment errors in clinical diagnostics, as well as that of other decision-makers in the legal and corporate sectors. Finally, the experimental methods and results of the proposed research may help to shed light on the biological underpinnings of important brain disorders, in particular schizophrenia, for which confirmation biases are aggravated.The central focus of the proposed work is to test the hypothesis that choices generate subjective expectations that influence the subsequent evaluation process of both past and future evidence. The proposed research will record psychophysical and functional neuroimaging (magnetoencephalography (MEG)) measurements of healthy human subjects while they are performing a range of novel behavioral tasks specifically developed to assess choice-induced biases in low-level perception as well has high-level cognition. Theory and computational modeling will be crucial to interpret these signals and ultimately to help infer the underlying cognitive operations. The results of this research will not only advance our understanding of choice-induced bias effects in decision-making, but of decision-making in general. The combined approach of simultaneously using behavioral, neural, and theoretical/computational measurements and methods imposes strong constraints on the expected results and explanations while at the same time lending also extraordinarily strong confidence to the findings as they are supported on all levels. To the degree that they demonstrate how choices influence subsequent evidence evaluation, our results have the potential to drastically change the traditional understanding of decision-making as a simple feedforward accumulation-to-bound process.A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

我们所做的选择不仅影响我们如何记住过去，也影响我们如何看待未来。在这两种情况下，我们的判断都偏向于我们之前的选择。这种由选择引起的偏见已经存在了几个世纪。它们影响我们在日常生活中的判断，包括在判断错误是关键的情况下（例如，医学诊断、科学假设检验或政治决策）。为什么人类的大脑会产生这些偏见，并倾向于自我确认，这一直是一个谜。在计算神经科学合作研究计划的支持下，拟议的研究将着手确定人类决策中选择诱导偏见的潜在计算和神经机制。拟议的工作采用了一种高度跨学科的方法，将行为和大脑活动的测量与理论和计算建模相结合。它完美地借鉴了每个PI及其实验室的免费实验和计算专业知识。我们的目标是开发和验证一种新的不确定性下的决策理论，其中选择引起的偏见发挥了核心作用。揭开选择导致的偏见的来源和功能不仅对理解人类理性的局限性至关重要，而且对整个社会具有直接和重要的影响。例如，这些见解可以帮助培训医生减少临床诊断中的判断错误，以及法律的和企业部门的其他决策者。最后，拟议的研究的实验方法和结果可能有助于阐明重要的大脑疾病的生物学基础，特别是精神分裂症，其中确认偏差加剧，拟议的工作的中心焦点是测试的假设，即选择产生主观期望，影响随后的评估过程中的过去和未来的证据。拟议的研究将记录健康人类受试者的心理物理和功能神经成像（脑磁图（MEG））测量，同时他们正在执行一系列专门开发的新行为任务，以评估低水平感知中的选择诱导偏见以及高水平认知。理论和计算建模对于解释这些信号并最终帮助推断潜在的认知操作至关重要。这项研究的结果不仅将促进我们对决策中的选择诱导偏差效应的理解，而且将促进我们对一般决策的理解。同时使用行为，神经和理论/计算测量和方法的组合方法对预期的结果和解释施加了强有力的约束，同时也为研究结果提供了非常强的信心，因为它们在各个层面上都得到了支持。在一定程度上，他们展示了选择如何影响随后的证据评估，我们的结果有可能彻底改变传统的理解决策作为一个简单的前馈积累到绑定过程。一个配套项目正在由联邦教育和研究部资助，德国（BMBF）。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。