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The evaluation of the use of Artificial Intelligence (AI) in legal decisions still has unsolved questions. These may refer to the perceived degree of seriousness of the possible errors committed, the distribution of responsibility among the different decision-makers (human or artificial), and the evaluation of the error concerning its possible benevolent or malevolent consequences on the person sanctioned. Above all, assessing the possible relationships between these variables appears relevant. To this aim, we conducted a study through an online questionnaire (N = 288) where participants had to consider different scenarios in which a decision-maker, human or artificial, made an error of judgement for offences punishable by a fine (Civil Law infringement) or years in prison (Criminal Law infringement). We found that humans who delegate AIs are blamed less than solo humans, although the effect of decision maker was subtle. In addition, people consider the error more serious if committed by a human being when a sentence for a crime of the penal code is mitigated, and for an AI when a penalty for an infringement of the civil code is aggravated. The mitigation of the evaluation of seriousness for joint AI-human judgement errors suggests the potential for strategic scapegoating of AIs. [ABSTRACT FROM AUTHOR]

Research on gender role stereotypes activated in interactions with humanoid robots has yet to produce conclusive knowledge. To analyse how much, and in which way, gender role stereotypes used in interactions with humans are also called into play in interactions with humanoid robots, a study was conducted with 240 participants. The study was an online survey in which a scale was used for determining the appropriateness for performing four stereotypically masculine and four feminine by humans and robots. Overall, eight humanoid robots – four judged feminine and four masculine – were considered. Results showed that gender role stereotypes are activated for both genders, but men most strongly activate those pertaining to male roles. These stereotypes are also adopted in reference to humanoid robots, though robots are generally considered less suitable for performing female roles. Furthermore, an increased degree of similarity of robots to humans has a positive effect in assessing the appropriateness to perform female roles only for female robots. The same does not happen with male robots. These results suggest that male and female robots are not categorised in the same way. Robots are essentially perceived as male entities, a particularly relevant hypothesis for the gender-sensitive design of humanoid robots. [ABSTRACT FROM AUTHOR]

This paper presents an experiment in which participants had to discriminate three mid-air haptic shapes (circle, square, point) by reporting whether the haptic stimulus (e.g. circle on the palm of the hand) was compatible with an image (e.g. a circle) or a word (e.g. 'circle') displayed on a screen. Results indicate that only the 'point' stimulus was appreciably recognised and discriminated in terms of accuracy and time needed for the identification. Accuracy increased with repetition, and response time decreased, suggesting a learning effect. The comparison between visual and textual labels shows that for the haptic point stimulus there is no significant difference but a tendency to have greater accuracy with images than with texts, while the opposite result is found for the circle stimulus. This outcome suggests the need for new experiments focussed of the effect of visual/textual labels to make the recognition/discrimination tasks of haptic stimuli easier. Practitioner Summary: Three haptic shapes were presented with images or texts, matching or not the stimuli. The point was easy to recognise, while the circle and the square were difficult to discriminate against each other. Visual/textual labels bring contradictory results for different shapes. Abbreviations: 1D: one-dimensional; 2D: two-dimensional; 3D: three-dimensional; API: application programming interface; cm: centimeter; GLMM: generalised linear mixed-effect model; HCI: human-computer interaction; Hz: hertz; LMM: linear mixed-effect model; MCC: Matthews' correlation coefficient; mm: millimeter; ms: millisecond; QQ-plot: Quantile-Quantile plot; SD: standard deviation [ABSTRACT FROM AUTHOR]

As collaborative robots and artificial intelligence (AI) systems are being deployed in ever-increasing contexts, we are more and more called upon to make judgements on their moral behaviour. Understanding the factors, affecting our ethical judgements involving these types of agents, would thus seem of the uttermost importance to allow for safer and well-regulated interactions between humans and machines. So far, however, this topic has been rarely investigated. We compared the perception of the seriousness of an action committed by either a person or a robot, causing harm to either some persons or some robots, and the attribution of the appropriated punishment for that action. The results showed a significant effect of the type of victim: the action was considered more a serious offence, and deemed worthy of more severe punishment, if the victims were humans than if they were robots. A significant agent-by-victim interaction was also found in the punishment judgements: for human victims, a human agent was punished more severely than a robot, while for robot victims, a robot agent was attributed a more severe punishment than a human one. The results are discussed in the light of the theories linking moral judgements to mind perception. [ABSTRACT FROM AUTHOR]

The goal of the present study is to explore the role of empathic and emotional skills in virtual negotiation, and to try to verify their possible role in different contexts: monetary/non-monetary, in circumstances in which a counterparty is familiar or unknown, and with respect to polite or rude responses from the negotiating counterparty. To this end, 320 participants aged between 19 to 25 years old were involved in a simulated virtual negotiation. Participants were required to fill in a Basic Empathy Scale (BES) questionnaire, they were also asked to report the prevalent emotion they had felt during the interaction, and if they thought they were interacting with a real person. The results of this research confirm the tendency of participants to minimise losses. Although the capacity for empathy does not seem to have a role, the behaviour of participants appears more cooperative when they have to deal with a familiar negotiation counterparty. Emotions appear to play a positive role when negotiating with, what is perceived to be, a real person. Practitioner summary: We conducted this study as part of a Master's Degree programme which was specifically focussed on human-computer interaction. Results show that negotiation was affected by emotions experienced during the experiment, and by the perception of the negotiating counterparty as a familiar person more so than by empathy. Abbreviations: AE: affective empathy; AMIS: assessment model of internet systems; ANOVA: ANalysis Of VAriance; BES: base empathy scale; CE: cognitive empathy; CMC: computer mediated communication; ENS: e-negotiation systems; FTF: face-to-face communication; NSA: negotiation support agents; PC: personal computer. [ABSTRACT FROM AUTHOR]

The issue of the periodical presents selected highlights from ECCE 2021, the 32nd European Conference on Cognitive Ergonomics. It mentions that the conference is the annual event of the European Association of Cognitive Ergonomics (EACE), a leading conference on human-media interaction that provides an opportunity for researchers and practitioners to exchange new ideas and practical experiences for a variety of domains.

“Nomadic” patients are people who, mainly for work, move around the world very often. Such people have the right to an effective, safe, fast health-care assistance wherever they are. Some technological devices are currently being experimented, in order to let personal health-related information be portable and easily transferable. However, each of these devices follows an idiosyncratic concept. An explorative study has been carried out in order to understand which procedures, if any are currently being used in Italy to manage nomadic patients' data. The goal of this work was to outline a concept of information architecture for an efficient technological support device, essential to the transfer of medical data. [ABSTRACT FROM AUTHOR]