Evidence and Uncertainty in Human Reasoning

尽管有些决定是基于对“直觉”的简单直接评估或各种选择的效用而做出的，但许多决定都涉及相互矛盾的情感;解决冲突的过程往往会考虑到一些不确定事件的证据。一个典型的例子是一个大学生面临的冲突，他第二天有一个重要的考试，但他想放弃学习，花一些时间和朋友在一起。 在解决这一冲突的过程中，许多学生考虑到了即使他们现在停止学习，他们也会在考试中失败的不确定性事件。 与此事件相关的证据包括考试的难度以及学生整个学期在这门课上做了多少准备。 如果考试只是有点重要，而证据使学生感到不需要进一步学习就能做得很好，学生可能会决定放弃学习。 即使考试是非常重要的，一个非常肯定会做得很好的学生很可能会放弃学习。对于某些决定，部分证据包括来自科学模型的估计概率。 医生在推荐治疗之前可能会考虑癌症复发的估计概率，或者房主在决定是否加固地基时可能会考虑地震的可能性。目前的研究是基于最近发展起来的不确定性下的决策理论。 核心思想是人们对不确定事件进行分类（例如，“相当肯定”或“非常肯定”在考试中取得好成绩），并且这种分类是基于各种证据（有时包括从科学模型估计的概率）。 一个集中在涉及冲突的决策情况。 我们研究了决策规则如何变化，这取决于目标的价值（例如，学生可能会使用“相当肯定”的规则，对于一个有点重要的考试，但一个“非常肯定”的规则，对于一个非常重要的），以及如何使用证据来分类不确定的事件。 我们的初步研究结果表明，不同的证据权重用于不同的抽象类别的不确定性。 这部分研究还考察了人们为自己的决定所做的辩护，以便更好地理解辩护与决定背后的实际决策规则之间的关系。研究的第二个分支集中在证据判断上，与最终的决定无关--例如，侦探或科学家在形成或证实假设时可能使用的判断。 我们感兴趣的是最初产生一个假设和证实它之间的区别;人们对相互矛盾的证据的反应;人们如何使用基本比率和相对倾向作为证据;以及当相关证据被不相关的东西所掩盖时，如何选择相关证据。研究如何科学的概率估计可以在政策决策中使用;和描绘之间的差异探索性使用的证据在制定假说与假说确认。

Although some decisions are made on the basis of simple directevaluation of "gut" feelings, or the utilities of the variousalternatives, many decisions involve conflicting feelings; and theconflict-resolution process often takes into account evidence aboutsome uncertain events.A typical example would be the conflict faced by a college student whohas an important exam the next day but wants to quit studying tospend some time with friends. In the process of resolving thisconflict, many students consider the uncertain event that they will dowell in the exam even if they stop studying now. Evidence relevant tothis event includes how difficult the exam is expected to be and howmuch preparation the student has done all semester in this course. Ifthe exam is only somewhat important, and the evidence leads the studentto feel pretty sure of doing well without further studying, the studentwill probably decide to quit studying. Even if the exam is highlyimportant, a student who is very sure of doing well will probablyquit studying.For some decisions, part of the evidence consists of estimatedprobabilities derived from scientific models. A physician mayconsider estimated probabilities of recurrence of cancer beforerecommending therapy, or a homeowner may take account of earthquakeprobabilities in deciding whether to reinforce the foundation.The present research is based on a recently developed theory ofdecision-making under uncertainty. The core idea is that peoplecategorize uncertain events (e.g., "pretty sure" or "very sure"of doing well on the exam), and that such categorization is based onvarious kinds of evidence (sometimes including probabilitiesestimated from scientific models).The research has two main branches. One focusses on decisionsituations involving conflict. We study how decision rules change,depending on value of goals (for example, a student may use a"pretty sure" rule for a somewhat important exam, but a "very sure"rule for a highly important one) and how evidence is used tocategorize the uncertain events. Our preliminary findings suggestthat different evidence weightings are used for different abstractcategories of uncertainty. This part of the research also examinespeople's justifications for their decisions, in order to understandbetter how justifications relate to actual decision rules underlyingchoices.The second branch of the research focusses on evidence judgment, inisolation from the ultimate decision--for example, the judgmentsthat a detective or a scientist might use in forming or confirminghypotheses. We are interested in the difference between initiallygenerating a hypothesis and confirming it; in how people react toconflicting evidence; in how people use base rates and relativelikelihoods as evidence; and in the process of selecting relevantevidence when it is obscured by irrelevancies.To summarize, the major goals of the research include testing anddeveloping a rather new theory of decision making; studying howscientific probability estimates can be used in policy decisions;and delineating the differences between exploratory use of evidencein formulating hypotheses versus hypothesis confirmation.