Measuring awareness in implicit cognition research: Developing research methods for the next decade.

研究人员的一个共识是，我们的大部分行为都是基于我们几乎没有意识到、也几乎无法控制的相当自动的过程。研究表明，接触到微妙的线索会对我们的决定产生巨大影响。例如，要求人们提供其社会安全号码的最后两位数字会导致他们愿意为产品和商品支付多少钱。同样，根据一些研究人员的研究，如果人们在解决字谜时接触到与粗鲁相关的单词，他们更有可能变得不礼貌和不尊重。另一项研究表明，我们在分心和思考其他事情时做出了许多（重要的）决定，这种“无意识的思考”过程实际上提高了我们决策的质量。这些研究属于一个更大的研究领域，通常被称为“内隐认知”，它探讨了无意识机制如何促进认知过程，包括感知、学习、记忆和决策。这一研究领域吸引了媒体的大量关注，并经常出现在科普书籍、博客和纪录片中。一些作者甚至提出，这项研究的部分内容可以用于改善我们在社会层面不同领域的决策（例如，在健康行为和养老金计划方面）。目前的项目集中在这个文献的一个特定领域，内隐学习。在这一领域进行的研究试图确定我们是否能够在没有意识到这些规律的情况下发现环境中的规律。换句话说，这些研究解决了我们是否可以在没有意识到我们确实在学习的情况下学习一些东西。近年来，在科学文献中有成千上万的内隐学习效应的证明，毫不奇怪，这些文献在心理学的各个领域越来越有影响力，对我们对人类认知和精神病理学的理解产生了重要影响。不幸的是，我们之前的研究表明，这些证据大多被基本的方法问题所破坏，这些问题阻碍了对无意识学习效果的可靠性得出任何强有力的结论。我们已经证明，许多这样的研究发现了无意识学习，因为研究人员使用较弱的方法来评估人们是否意识到他们学到了什么，而不是评估学习是否发生了。当然，这意味着学习很容易被发现，但意识却不容易，这就造成了学习是在无意识中发生的错觉。在这些领域找到意识的证据是很重要的，因为它表明某种程度的控制可能也是可用的。在本项目中，我们提出了研究无意识学习的新方法。我们在之前的研究中发现的许多问题可以通过采用尖端的统计分析来改善，包括贝叶斯和元分析方法以及模型拟合。然而，这些方法在内隐认知领域的有效性仍有待检验。第二个目标是对这些问题的普遍性和严重性进行大规模的探索。我们之前的研究集中于内隐学习研究中的一个非常特殊的效应（“上下文提示”）。我们怀疑，许多这些问题超出了这一领域，并影响了目前内隐学习的很大一部分研究。这一评估的潜在影响怎么估计都不过分。最后，我们将与其他研究这一主题的国际实验室建立合作，以收集迄今为止最大和最敏感的内隐学习效应数据集。该数据集将对所有研究人员公开，这将使其成为未来许多年无意识认知过程研究的基础资源。

A consensus among researchers is that much of our behaviour is based on rather automatic processes we are barely aware of and over which we have little control. Research suggests that exposure to subtle cues can have dramatic effects on our decisions. For instance, asking people to provide the last 2 digits of their social security number biases how much they are willing to pay for products and commodities. Similarly, according to some researchers, people are more likely to be impolite and disrespectful if they have been exposed to words related to rudeness while solving anagrams. Another line of research suggests that we take many of our (important) decisions when distracted and thinking about other things and that this 'unconscious thought' process actually improves the quality of our decisions.These studies pertain to a larger area of research usually called 'implicit cognition', which explores how unconscious mechanisms contribute to cognitive processes including perception, learning, memory, and decision making. This area of research has attracted a great deal of attention from the media and features frequently in popular science books, blogs, and documentaries. Some authors have even suggested that parts of this research could be used to improve our decisions in different domains at a societal level (for example, in health behaviour and pension planning).The present project focuses on a particular domain of this literature, implicit learning. Studies conducted in this area try to determine whether we are able to detect regularities in our environment without awareness of those regularities. In other words, these studies address whether we can learn something without realising that we are indeed learning it. In recent years there have been thousands of demonstrations of implicit learning effects in the scientific literature and, not surprisingly, this literature has become increasingly influential in all areas of psychology, with an important impact in our understanding of human cognition and psychopathology.Unfortunately, our previous research suggests that much of this evidence is undermined by fundamental methodological problems that preclude any strong conclusions about the reliability of unconscious learning effects. We have shown that many of these studies find unconscious learning because researchers use weaker methods to assess whether people are conscious of what they have learned than to assess whether learning has taken place. Naturally, this implies that learning is easily detected but awareness is not, which creates the illusion that learning has taken place unconsciously. Finding evidence of awareness in these domains is important because it suggests that some degree of control may be available as well.In the present project we propose new methods for the study of unconscious learning. Many of the problems that we have detected in our previous research can be ameliorated by employing cutting-edge statistical analysis, including Bayesian and meta-analytic methods and model fitting. However, the validity of these approaches in the domain of implicit cognition remains untested. A second goal is to conduct a large-scale exploration of the prevalence and magnitude of these problems. Our previous studies have focused on a very particular effect studied in implicit learning research ('contextual cueing'). We suspect that many of these problems transcend this domain and affect a large proportion of current studies on implicit learning. The potential impact of this assessment is difficult to overestimate. Finally, we will set up a collaboration with other international laboratories working on this topic to gather the largest and most sensitive data set of implicit learning effects available so far. This data set will be publicly available for all researchers, which will make it a fundamental resource for the study of unconscious cognitive processes for many years to come.