Simple autonomous agents can enhance creative semantic discovery by human groups.

Innovation is challenging, and theory and experiments indicate that groups may be better able to identify and preserve innovations than individuals. But innovation within groups faces its own challenges, including groupthink and truncated diffusion. We performed experiments involving a game in which people search for ideas in various conditions: alone, in networked social groups, or in networked groups featuring autonomous agents (bots). The objective was to search a semantic space of 20,000 nouns with defined similarities for an arbitrary noun with the highest point value. Participants (N = 1875) were embedded in networks (n = 125) of 15 nodes to which we sometimes added 2 bots. The bots had 3 possible strategies: they shared a random noun generated by their immediate neighbors, or a noun most similar from among those identified, or a noun least similar. We first confirm that groups are better able to explore a semantic space than isolated individuals. Then we show that when bots that share the most similar noun operate in groups facing a semantic space that is relatively easy to navigate, group performance is superior. Simple autonomous agents with interpretable behavior can affect the capacity for creative discovery of human groups.

Reducing variance or helping the poorest? A mouse tracking approach to investigate cognitive bases of inequality aversion in resource allocation.

Humans dislike unequal allocations. Although often conflated, such 'inequality-averse' preferences are separable into two elements: egalitarian concern about the variance and maximin concern about the poorest (maximizing the minimum). Recent research has shown that the maximin concern operates more robustly in allocation decisions than the egalitarian concern. However, the real-time cognitive dynamics of allocation decisions are still unknown. Here, we examined participants' choice behaviour with high temporal resolution using a mouse-tracking technique. Participants made a series of allocation choices for others between two options: a 'non-Utilitarian option' with both smaller variance and higher minimum pay-off (but a smaller total) compared with the other 'Utilitarian option'. Choice data confirmed that participants had strong inequality-averse preferences, and when choosing non-utilitarian allocations, participants' mouse movements prior to choices were more strongly determined by the minimum elements of the non-Utilitarian options than the variance elements. Furthermore, a time-series analysis revealed that this dominance emerged at a very early stage of decision making (around 500 ms after the stimulus onset), suggesting that the maximin concern operated as a strong cognitive anchor almost instantaneously. Our results provide the first temporally fine-scale evidence that people weigh the maximin concern over the egalitarian concern in distributive judgements.

How does social information affect charitable giving?: Empathic concern promotes support for underdog recipient.

Charitable giving represents a unique cooperative characteristic of humans. In today's environment with social media, our charitable decisions seem to be influenced by social information such as a project's popularity. Here we report three experiments that examined people's reactions to social information about a charitable endeavor and their psychophysiological underpinnings. Participants were first solicited to make donations to either the Africa or Syria project of UNICEF. Then participants were provided an opportunity to learn social information (i.e., how much each project had raised from previous participants) and change their decision if desired. Contrary to expectation, participants who learned that their initial preferences were consistent with the majority of previous participants' choices exhibited a sizable tendency to switch to the less popular project in their final choices. This anti-conformity pattern was robust across the three experiments. Eye-tracking data (gaze bias and pupil dilation) indicated that these "Changers" were more physiologically aroused and formed more differential valuations between the two charity projects, compared to "Keepers" who retained their initial preferences after viewing the social information. These results suggest that social information about relative popularity may evoke empathic concern for the worse-off target, in line with the human tendency to avoid unequal distributions.

Deciding for others as a neutral party recruits risk-neutral perspective-taking: Model-based behavioral and fMRI experiments.

Risky decision making for others is ubiquitous in our societies. Whereas financial decision making for oneself induces strong concern about the worst outcome (maximin concern) as well as the expected value, behavioral and neural characteristics of decision making for others are less well understood. We conducted behavioral and functional magnetic resonance imaging (fMRI) experiments to examine the neurocognitive underpinnings of risky decisions for an anonymous other, using decisions for self as a benchmark. We show that, although the maximin concern affected both types of decisions equally strongly, decision making for others recruited a more risk-neutral computational mechanism than decision making for self. Specifically, participants exhibited more balanced information search when choosing a risky option for others. Activity of right temporoparietal junction (rTPJ, associated with cognitive perspective taking) was parametrically modulated by options' expected values in decisions for others, and by the minimum amounts in decisions for self. Furthermore, individual differences in self-reported empathic concern modified these attentional and neural processes. Overall, these results indicate that the typical maximin concern is attenuated in a risk-neutral direction in decisions for others as compared to self. We conjecture that, given others' diverse preferences, deciding as a neutral party may cognitively recruit such risk-neutrality.