Humans inherit artificial intelligence biases.

Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own decisions, even when they move to a context without AI support. In three experiments, participants completed a medical-themed classification task with or without the help of a biased AI system. The biased recommendations by the AI influenced participants' decisions. Moreover, when those participants, assisted by the AI, moved on to perform the task without assistance, they made the same errors as the AI had made during the previous phase. Thus, participants' responses mimicked AI bias even when the AI was no longer making suggestions. These results provide evidence of human inheritance of AI bias.

A HTML5 open source tool to conduct studies based on Libet's clock paradigm.

Libet's clock is a well-known procedure in experiments in psychology and neuroscience. Examples of its use include experiments exploring the subjective sense of agency, action-effect binding, and subjective timing of conscious decisions and perceptions. However, the technical details of the apparatus used to conduct these types of experiments are complex, and are rarely explained in sufficient detail as to guarantee an exact replication of the procedure. With this in mind, we developed Labclock Web, a web tool designed to conduct online and offline experiments using Libet's clock. After describing its technical features, we explain how to configure specific experiments using this tool. Its degree of accuracy and precision in the presentation of stimuli has been technically validated, including the use of two cognitive experiments conducted with voluntary participants who performed the experiment both in our laboratory and via the Internet. Labclock Web is distributed without charge under a free software license (GPLv3) since one of our main objectives is to facilitate the replication of experiments and hence the advancement of knowledge in this area.

The lack of side effects of an ineffective treatment facilitates the development of a belief in its effectiveness.

Some alternative medicines enjoy widespread use, and in certain situations are preferred over conventional, validated treatments in spite of the fact that they fail to prove effective when tested scientifically. We propose that the causal illusion, a basic cognitive bias, underlies the belief in the effectiveness of bogus treatments. Therefore, the variables that modulate the former might affect the latter. For example, it is well known that the illusion is boosted when a potential cause occurs with high probability. In this study, we examined the effect of this variable in a fictitious medical scenario. First, we showed that people used a fictitious medicine (i.e., a potential cause of remission) more often when they thought it caused no side effects. Second, the more often they used the medicine, the more likely they were to develop an illusory belief in its effectiveness, despite the fact that it was actually useless. This behavior may be parallel to actual pseudomedicine usage; that because a treatment is thought to be harmless, it is used with high frequency, hence the overestimation of its effectiveness in treating diseases with a high rate of spontaneous relief. This study helps shed light on the motivations spurring the widespread preference of pseudomedicines over scientific medicines. This is a valuable first step toward the development of scientifically validated strategies to counteract the impact of pseudomedicine on society.