An fMRI and effective connectivity study investigating miss errors during advice utilization from human and machine agents

Abstract

As society becomes more reliant on machines and automation, understanding how people utilize advice is a necessary endeavor. Our objective was to reveal the underlying neural associations during advice utilization from expert human and machine agents with fMRI and multivariate Granger causality analysis. During an X-ray luggage-screening task, participants accepted or rejected good or bad advice from either the human or machine agent framed as experts with manipulated reliability (high miss rate). We showed that the machine-agent group decreased their advice utilization compared to the human-agent group and these differences in behaviors during advice utilization could be accounted for by high expectations of reliable advice and changes in attention allocation due to miss errors. Brain areas involved with the salience and mentalizing networks, as well as sensory processing involved with attention, were recruited during the task and the advice utilization network consisted of attentional modulation of sensory information with the lingual gyrus as the driver during the decision phase and the fusiform gyrus as the driver during the feedback phase. Our findings expand on the existing literature by showing that misses degrade advice utilization, which is represented in a neural network involving salience detection and self-processing with perceptual integration.

From automata to animate beings: the scope and limits of attributing socialness to artificial agents

“…For instance, repeated exposure to robotic actions was shown to increase automatic imitation of these actions to levels comparable to human actions . Moreover, several recent studies on trust during interactions with artificial agents or machines provide compelling first evidence on how expectations and changes in the involvement of the ToM network shape these interactions over time . An exciting opportunity for future research is to study in more detail the dynamic, temporal dimensions of these processes.…”

From automata to animate beings: The scope and limits of attributing socialness to artificial agents

“…For instance, repeated exposure to robotic actions was shown to increase automatic imitation of these actions to levels comparable to human actions 89 . Moreover, several recent studies on trust during interactions with artificial agents or machines provide compelling first evidence on how expectations and changes in the involvement of the ToM network shape these interactions over time 165,169,170 . An exciting opportunity for future research is to study in more detail the dynamic, temporal dimensions of these processes.…”

Learning From the Slips of Others: Neural Correlates of Trust in Automated Agents

“…Consistent with this idea, a recent study found that false alarm-prone advice activated different brain regions for a human compared to a machine, including the precuneus, posterior cingulate cortex, and temporoparietal junction ( Goodyear et al, 2016 ). Alternatively, miss-prone advice activated salience and mentalizing brain networks differentially for a human compared to a machine ( Goodyear et al, 2017 ). Another study showed that observing errors for humans and machines results in very similar activation in the medial prefrontal cortex ( Desmet et al, 2014 ), although other work showed that this effect can be moderated by human-likeness of the machine agent ( Krach et al, 2008 ).…”