Lieder Falk, Griffiths Thomas L, M Huys Quentin J, Goodman Noah D
Helen Wills Neuroscience Institute, University of California, Berkeley, USA.
Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zürich and Swiss Federal Institute of Technology (ETH) Zürich, Zürich, Switzerland.
Psychon Bull Rev. 2018 Apr;25(2):775-784. doi: 10.3758/s13423-017-1288-6.
People's estimates of numerical quantities are systematically biased towards their initial guess. This anchoring bias is usually interpreted as sign of human irrationality, but it has recently been suggested that the anchoring bias instead results from people's rational use of their finite time and limited cognitive resources. If this were true, then adjustment should decrease with the relative cost of time. To test this hypothesis, we designed a new numerical estimation paradigm that controls people's knowledge and varies the cost of time and error independently while allowing people to invest as much or as little time and effort into refining their estimate as they wish. Two experiments confirmed the prediction that adjustment decreases with time cost but increases with error cost regardless of whether the anchor was self-generated or provided. These results support the hypothesis that people rationally adapt their number of adjustments to achieve a near-optimal speed-accuracy tradeoff. This suggests that the anchoring bias might be a signature of the rational use of finite time and limited cognitive resources rather than a sign of human irrationality.
人们对数值量的估计会系统性地偏向于他们的初始猜测。这种锚定偏差通常被视为人类非理性的标志,但最近有人提出,锚定偏差反而源于人们对其有限时间和有限认知资源的合理利用。如果这是真的,那么调整应该会随着时间的相对成本而减少。为了验证这一假设,我们设计了一种新的数值估计范式,该范式控制人们的知识,并独立改变时间成本和误差成本,同时允许人们根据自己的意愿投入或多或少的时间和精力来完善他们的估计。两项实验证实了这一预测,即无论锚点是自我生成的还是提供的,调整都会随着时间成本的增加而减少,但会随着误差成本的增加而增加。这些结果支持了这样一种假设,即人们会合理调整他们的调整次数,以实现接近最优的速度-准确性权衡。这表明,锚定偏差可能是合理利用有限时间和有限认知资源的标志,而不是人类非理性的标志。