Could social robots facilitate children with autism spectrum disorders in learning distrust and deception?

Do Children with Autism Spectrum Disorders Show Selective Trust in Social Robots?

PURPOSE

Previous researches suggest that social robots can facilitate the learning of children with Autism Spectrum Disorder (ASD) by enhancing their interests, engagement, and attention. However, there is limited understanding regarding whether children with ASD can learn directly from the testimony of social robots and whether they can remain vigilant based on the perceived accuracy of these robots. Therefore, the present study was conducted to examine whether children with ASD demonstrated selective trust towards social robots.

METHODS

Twenty-nine children with ASD between ages of 4-7 years, and 38 typically-developing (TD) age and IQ-matched peers participated in classic selective trust tasks. During the tasks, they learned the names of novel objects from either a pair of social robots or a pair of human informants, where one informant had previously been established as accurate and the other inaccurate.

RESULTS

Children with ASD trusted information from an accurate social robot over an inaccurate one, similar to their performance with human informants. However, compared to TD children, children with ASD exhibited lower levels of selective trust regardless of the type of informants they learned from.

CONCLUSIONS

Our study suggests that children with ASD can selectively trust and acquire knowledge from social robots, shedding light on the potential use of social robots in supporting individuals with ASD.

Assisted Robots in Therapies for Children with Autism in Early Childhood

Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). Currently, one way to address this problem is by using robotic systems to address the abilities that are altered in these children. The aim of this review will be to analyse the effectiveness of the incorporation of the different robotic systems currently existing in the treatment of children up to 10 years of age diagnosed with autism. A systematic review has been carried out in the PubMed, Scopus, Web of Science, and Dialnet databases, with the following descriptors: child, autism, and robot. The search yielded 578 papers, and nine were selected after the application of the PRISMA guideline. The quality of the studies was analysed with the PEDRo scale, and only those with a score between four and six were selected. From this study, the conclusion is that the use of robots, in general, improves children's behaviour in the short term, but longer-term experiences are necessary to achieve more conclusive results.

People with Autism Spectrum Disorder Could Interact More Easily with a Robot than with a Human: Reasons and Limits

Individuals with Autism Spectrum Disorder show deficits in communication and social interaction, as well as repetitive behaviors and restricted interests. Interacting with robots could bring benefits to this population, notably by fostering communication and social interaction. Studies even suggest that people with Autism Spectrum Disorder could interact more easily with a robot partner rather than a human partner. We will be looking at the benefits of robots and the reasons put forward to explain these results. The interest regarding robots would mainly be due to three of their characteristics: they can act as motivational tools, and they are simplified agents whose behavior is more predictable than that of a human. Nevertheless, there are still many challenges to be met in specifying the optimum conditions for using robots with individuals with Autism Spectrum Disorder.

Effectiveness of a Robot-Assisted Psychological Intervention for Children with Autism Spectrum Disorder

Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The main aim of this randomised controlled study was to evaluate the effectiveness of a robot-assisted psychosocial intervention and the secondary aim was to investigate potential differences between a robot-assisted intervention group and a control group receiving intervention by humans only. The analysis of the results showed that robot-assisted intervention could be beneficial by improving children's psychosocial skills. This improvement was highlighted by neuropsychological testing and parent reporting. Group comparison only presented minimal statistically significant differences. The study underpins the potential of robot-assisted interventions to augment standard care.

Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis

(1) Background: Social robot interaction design is crucial for determining user acceptance and experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, we conducted this study in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: We conducted a comprehensive review based on 2416 papers related to social robot interaction design obtained from the Web of Science (WOS) database. Our review utilized bibliometric techniques and integrated VOSviewer and CiteSpace to construct a knowledge map. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1 the study of human-robot relationships in social robots, #2 research on the emotional design of social robots, #3 research on social robots for children's psychotherapy, #4 research on companion robots for elderly rehabilitation, and #5 research on educational social robots. The reference co-citation analysis identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers

An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ensemble learning system (also known as multiple classifier learning systems) yields the most significant benefits in the size or diversity of the ensemble? In this paper, the ability of ensemble learning to predict and identify factors that influence or contribute to autism spectrum disorder therapy (ASDT) for intervention purposes is investigated. Given that most interventions are typically short-term in nature, henceforth, developing a robotic system that will provide the best outcome and measurement of ASDT therapy has never been so critical. In this paper, the performance of five single classifiers against several multiple classifier learning systems in exploring and predicting ASDT is investigated using a dataset of behavioural data and robot-enhanced therapy against standard human treatment based on 3000 sessions and 300 h, recorded from 61 autistic children. Experimental results show statistically significant differences in performance among the single classifiers for ASDT prediction with decision trees as the more accurate classifier. The results further show multiple classifier learning systems (MCLS) achieving better performance for ASDT prediction (especially those ensembles with three core classifiers). Additionally, the results show bagging and boosting ensemble learning as robust when predicting ASDT with multi-stage design as the most dominant architecture. It also appears that eye contact and social interaction are the most critical contributing factors to the ASDT problem among children.

Assessing the Potential of Robotics Technology for Enhancing Educational for Children with Autism Spectrum Disorder

Robotics technology has been increasingly used as an educational and intervention tool for children with autism spectrum disorder (ASD). However, there remain research issues and challenges that need to be addressed to fully realize the potential benefits of robot-assisted therapy. This systematic review categorizes and summarizes the literature related to robot educational/training interventions and provides a conceptual framework for collecting and classifying these articles. The challenges identified in this review are classified into four levels: robot-level, algorithm-level, experimental-research-level, and application-level challenges. The review highlights possible future research directions and offers crucial insights for researchers interested in using robots in therapy. The most relevant findings suggest that robot-assisted therapy has the potential to improve social interaction, communication, and emotional regulation skills in children with ASD. Addressing these challenges and seeking new research avenues will be critical to advancing the field of robot-assisted therapy and improving outcomes for children with ASD. This study serves as a roadmap for future research in this important area.

Altered neural mechanisms of deception in individuals with autistic traits

A successful deception involves making a decision, acting on it, and evaluating results. Here, we investigated deception in a non-clinical sample (n = 36) with varying autism traits using a coin-toss paradigm of active deception. The subjects were asked to react to the instructions by clicking one of the two boxes that could mislead their opponents, followed by feedback on their success or failure. During this reaction, their EEG activity was recorded, and the results suggested that people with high autistic traits exhibited longer reaction times and lower amplitude of P3 in the decision-making stage compared to individuals with low autistic traits. The feedback evaluation stage in the high autistic trait group elicited lower amplitude of FRN and P3. Overall, these results indicated that people with high autistic traits experienced difficulties in deceiving, which could be related to atypical neural mechanisms.

Children-Robot Friendship, Moral Agency, and Aristotelian Virtue Development

Social robots are increasingly developed for the companionship of children. In this article we explore the moral implications of children-robot friendships using the Aristotelian framework of virtue ethics. We adopt a moderate position and argue that, although robots cannot be virtue friends, they can nonetheless enable children to exercise ethical and intellectual virtues. The Aristotelian requirements for true friendship apply only partly to children: unlike adults, children relate to friendship as an educational play of exploration, which is constitutive of the way they acquire and develop virtues. We highlight that there is a relevant difference between the way we evaluate adult-robot friendship compared to children-robot friendship, which is rooted in the difference in moral agency and moral responsibility that generate the asymmetries in the moral status ascribed to adults versus children. We look into the role played by imaginary companions (IC) and personified objects (PO) in children’s moral development and claim that robots, understood as Personified Robotic Objects (PROs), play a similar role with such fictional entities, enabling children to exercise affection, moral imagination and reasoning, thus contributing to their development as virtuous adults. Nonetheless, we argue that adequate use of robots for children’s moral development is conditioned by several requirements related to design, technology and moral responsibility.

Deceptive behaviour in autism: A scoping review

LAY ABSTRACT

The ability to deceive others is an important skill that usually develops in early childhood. In this review, we give an overview of studies that have examined deceptive behaviour in autistic children, adolescents and adults. We separated the study findings into three main categories and seven sub-categories: (1) Deception ability and prevalence (1a) gameplay deception; (1b) naturalistic deception; (2) Psychological processes in deception (2a) verbal, intellectual and social ability; (2b) ability to understand others' thoughts and beliefs; (2c) cognitive ability; and (3) Social learning (3a) training; (3b) social contexts. Contrary to some stereotypes, we found that autistic people can and do deceive but often find this more difficult than non-autistic people. We also found that autistic people may use different psychological processes than non-autistic people when deceiving and may get better at deception in adulthood.

Social Robots in Special Education: A Systematic Review

In recent years, social robots have become part of a variety of human activities, especially in applications involving children, e.g., entertainment, education, companionship. The interest of this work lies in the interaction of social robots with children in the field of special education. This paper seeks to present a systematic review of the use of robots in special education, with the ultimate goal of highlighting the degree of integration of robots in this field worldwide. This work aims to explore the technologies of robots that are applied according to the impairment type of children. The study showed a large number of attempts to apply social robots to the special education of children with various impairments, especially in recent years, as well as a wide variety of social robots from the market involved in such activities. The main conclusion of this work is the finding that the specific field of application of social robots is at the first development step; however, it is expected to be of great concern to the research community in the coming years.

Robot-Assisted Autism Therapy (RAAT). Criteria and Types of Experiments Using Anthropomorphic and Zoomorphic Robots. Review of the Research

Supporting the development of a child with autism is a multi-profile therapeutic work on disturbed areas, especially understanding and linguistic expression used in social communication and development of social contacts. Previous studies show that it is possible to perform some therapy using a robot. This article is a synthesis review of the literature on research with the use of robots in the therapy of children with the diagnosis of early childhood autism. The review includes scientific journals from 2005-2021. Using descriptors: ASD (Autism Spectrum Disorders), Social robots, and Robot-based interventions, an analysis of available research in PubMed, Scopus and Web of Science was done. The results showed that a robot seems to be a great tool that encourages contact and involvement in joint activities. The review of the literature indicates the potential value of the use of robots in the therapy of people with autism as a facilitator in social contacts. Robot-Assisted Autism Therapy (RAAT) can encourage child to talk or do exercises. In the second aspect (prompting during a conversation), a robot encourages eye contact and suggests possible answers, e.g., during free conversation with a peer. In the third aspect (teaching, entertainment), the robot could play with autistic children in games supporting the development of joint attention. These types of games stimulate the development of motor skills and orientation in the body schema. In future work, a validation test would be desirable to check whether children with ASD are able to do the same with a real person by learning distrust and cheating the robot.

How Technology Applied to Music-Therapy and Sound-Based Activities Addresses Motor and Social Skills in Autistic Children

Autism affects how people perceive and make sense of the world around them. Autism is a spectrum condition which impacts people in different ways. Also referred to as Autism Spectrum Disorder (ASD), it is characterized by challenges in the domains of social, cognitive and motor functioning, which differ in severity. Previous research suggests that music can have cognitive, psychosocial, behavioural, and motor benefits in this population. We systematically review the use of technology in Music-therapy and related sound-based activities to improve the motor and social skills of children. In May 2020 we conducted a systematic search on Music-therapy and musical activities for autistic children in research databases including Science Direct, APA PsycNet, Cochrane, IEE and Web of Science, to collect relevant studies. We initially collected 5179 papers of which only 27 studies were identified as suitable for the scope of this review. In the paper, we analyse and describe key characteristics of each project. We then highlight the commonalities, strengths and limitations of existing work, and identify implications for future interaction design.

Adherence and acceptability of a robot-assisted Pivotal Response Treatment protocol for children with autism spectrum disorder

The aim of this study is to present a robot-assisted therapy protocol for children with ASD based on the current state-of-the-art in both ASD intervention research and robotics research, and critically evaluate its adherence and acceptability based on child as well as parent ratings. The robot-assisted therapy was designed based on motivational components of Pivotal Response Treatment (PRT), a highly promising and feasible intervention focused at training “pivotal” (key) areas such as motivation for social interaction and self-initiations, with the goal of establishing collateral gains in untargeted areas of functioning and development, affected by autism spectrum disorders. Overall, children (3–8 y) could adhere to the robot-assisted therapy protocol (Mean percentage of treatment adherence 85.5%), showed positive affect ratings after therapy sessions (positive in 86.6% of sessions) and high robot likability scores (high in 79.4% of sessions). Positive likability ratings were mainly given by school-aged children (H(1) = 7.91, p = .005) and related to the movements, speech and game scenarios of the robot. Parent ratings on the added value of the robot were mainly positive (Mean of 84.8 on 0–100 scale), while lower parent ratings were related to inflexibility of robot behaviour.