Evaluating people's perceptions of trust in a robot in a repeated interactions study

Funding Information: Acknowledgment. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642667 (Safety Enables Cooperation in Uncertain Robotic Environments - SECURE). KD acknowledges funding from the Canada 150 Research Chairs Program. Publisher Copyright: © 2020, Springer Nature Switzerland AG This is a post-peer-review, pre-copyedit version of an article published of 'Rossi A., Dautenhahn K., Koay K.L., Walters M.L., Holthaus P. (2020) Evaluating People’s Perceptions of Trust in a Robot in a Repeated Interactions Study. In: Wagner A.R. et al. (eds) Social Robotics. ICSR 2020. Lecture Notes in Computer Science, vol 12483. Springer, Cham. https://doi.org/10.1007/978-3-030-62056-1_38'Trust has been established to be a key factor in fostering human-robot interactions. However, trust can change overtime according to different factors, including a breach of trust due to a robot’s error. In this exploratory study, we observed people’s interactions with a companion robot in a real house, adapted for human-robot interaction experimentation, over three weeks. The interactions happened in six scenarios in which a robot performed different tasks under two different conditions. Each condition included fourteen tasks performed by the robot, either correctly, or with errors with severe consequences on the first or last day of interaction. At the end of each experimental condition, participants were presented with an emergency scenario to evaluate their trust in the robot. We evaluated participants’ trust in the robot by observing their decision to trust the robot during the emergency scenario, and by collecting their views through questionnaires. We concluded that there is a correlation between the timing of an error with severe consequences performed by the robot and the corresponding loss of trust of the human in the robot. In particular, people’s trust is subjected to the initial mental formation

Mediated behavioural change in human-machine networks: exploring network characteristics, trust and motivation

Human-machine networks pervade much of contemporary life. Network change is the product of structural modifications along with differences in participant be-havior. If we assume that behavioural change in a human-machine network is the result of changing the attitudes of participants in the network, then the question arises whether network structure can affect participant attitude. Taking citizen par-ticipation as an example, engagement with relevant stakeholders reveals trust and motivation to be the major objectives for the network. Using a typology to de-scribe network state based on multiple characteristic or dimensions, we can pre-dict possible behavioural outcomes in the network. However, this has to be medi-ated via attitude change. Motivation for the citizen participation network can only increase in line with enhanced trust. The focus for changing network dynamics, therefore, shifts to the dimensional changes needed to encourage increased trust. It turns out that the coordinated manipulation of multiple dimensions is needed to bring about the desired shift in attitude.Comment: Paper submitted to SocInfo, organised by the Oxford Internet Institute, September 201

Sexually Antagonistic Selection in Human Male Homosexuality

Several lines of evidence indicate the existence of genetic factors influencing male homosexuality and bisexuality. In spite of its relatively low frequency, the stable permanence in all human populations of this apparently detrimental trait constitutes a puzzling ‘Darwinian paradox’. Furthermore, several studies have pointed out relevant asymmetries in the distribution of both male homosexuality and of female fecundity in the parental lines of homosexual vs. heterosexual males. A number of hypotheses have attempted to give an evolutionary explanation for the long-standing persistence of this trait, and for its asymmetric distribution in family lines; however a satisfactory understanding of the population genetics of male homosexuality is lacking at present. We perform a systematic mathematical analysis of the propagation and equilibrium of the putative genetic factors for male homosexuality in the population, based on the selection equation for one or two diallelic loci and Bayesian statistics for pedigree investigation. We show that only the two-locus genetic model with at least one locus on the X chromosome, and in which gene expression is sexually antagonistic (increasing female fitness but decreasing male fitness), accounts for all known empirical data. Our results help clarify the basic evolutionary dynamics of male homosexuality, establishing this as a clearly ascertained sexually antagonistic human trait

Diabetes and pregnancy:national trends over a 15 year period

Aims/hypothesis: We aimed to examine time trends in national perinatal outcomes in pregnancies complicated by pre-existing type 1 or type 2 diabetes. Methods: We analysed episode-level data on all obstetric inpatient delivery events (live or stillbirth) between 1 April 1998 and 31 March 2013 (n = 813,921) using the Scottish Morbidity Record (SMR02). Pregnancies to mothers with type 1 (n = 3229) and type 2 (n = 1452) diabetes were identified from the national diabetes database (Scottish Care Information-Diabetes), and perinatal outcomes were compared among women with type 1 diabetes, type 2 diabetes and those without diabetes. Results: The number of pregnancies complicated by diabetes increased significantly, by 44% in type 1 diabetes and 90% in type 2 diabetes, across the 15 years examined, to rates of 1 in 210 and 1 in 504 deliveries, respectively. Compared with women without diabetes, delivery occurred 2.6 weeks earlier (type 1 diabetes 36.7 ± 2.3 weeks) and 2 weeks earlier (type 2 diabetes 37.3 ± 2.4 weeks), respectively, showing significant reductions for both type 1 (from 36.7 weeks to 36.4 weeks, p = 0.03) and type 2 (from 38.0 weeks to 37.2 weeks, p < 0.001) diabetes across the time period. The proportions of preterm delivery were markedly increased in women with diabetes (35.3% type 1 diabetes, 21.8% type 2 diabetes, 6.1% without diabetes; p < 0.0001), and these proportions increased with time for both groups (p < 0.005). Proportions of elective Caesarean sections (29.4% type 1 diabetes, 30.5% type 2 diabetes, 9.6% without diabetes) and emergency Caesarean sections (38.3% type 1 diabetes, 29.1% type 2 diabetes, 14.6% without diabetes) were greatly increased in women with diabetes and increased over time except for stable rates of emergency Caesarean section in type 1 diabetes. Gestational age-, sex- and parity-adjusted z score for birthweight (1.33 ± 1.34; p < 0.001) were higher in type 1 diabetes and increased over time from 1.22 to 1.47 (p < 0.001). Birthweight was also increased in type 2 diabetes (0.94 ± 1.34; p < 0.001) but did not alter with time. There were 65 perinatal deaths in offspring of mothers with type 1 diabetes and 39 to mothers with type 2 diabetes, representing perinatal mortality rates of 20.1 (95% CI 14.7, 24.3) and 26.9 (16.7, 32.9) per 1000 births, respectively, and rates 3.1 and 4.2 times, respectively, those observed in the non-diabetic population (p < 0.001). Stillbirth rates in type 1 and type 2 diabetes were 4.0-fold and 5.1-fold that in the non-diabetic population (p < 0.001). Perinatal mortality and stillbirth rates showed no significant fall over time despite small falls in the rates for the non-diabetic population. Conclusions/interpretation: Women with diabetes are receiving increased intervention in pregnancy (earlier delivery, increased Caesarean section rates), but despite this, higher birthweights are being recorded. Improvements in rates of stillbirth seen in the general population are not being reflected in changes in stillbirth or perinatal mortality in our population with diabetes

Trust in financial services: the influence of demographics and dispositional characteristics

So far, very little attention has been paid to examining consumer perceptions of trust from an interdisciplinary perspective. The purpose of this study is to examine how consumer trusting belief and disposition to trust within the financial services sector vary on the basis of individual demographic differences in trust. The research provides new insights into how consumers with higher dispositional trust have higher institutional trust and higher trusting belief and how consumers’ trusting belief significantly differs according to their demographic background in terms of age, marital status, ethnicity and gross annual income. The findings offer useful insights for the managers in financial institutions to carefully consider the impact of the influence of these individual differences on consumer behaviour in order to serve the needs of consumers in their target market and be able to design financial products and develop trust building strategies to attract and retain them. They also call for the action of the regulators and the financial institutions to play their part in building strong institutional systems that contribute to engendering higher levels of consumer trust

Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support

Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms' complexity is a reason for their increased performance, it also leads to the "black box" problem, consequently decreasing trust towards AI. In this regard, "Explainable Artificial Intelligence" (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability

Similarities and Differences in Chinese and Caucasian Adults' Use of Facial Cues for Trustworthiness Judgments

All cultural groups in the world place paramount value on interpersonal trust. Existing research suggests that although accurate judgments of another's trustworthiness require extensive interactions with the person, we often make trustworthiness judgments based on facial cues on the first encounter. However, little is known about what facial cues are used for such judgments and what the bases are on which individuals make their trustworthiness judgments.In the present study, we tested the hypothesis that individuals may use facial attractiveness cues as a “shortcut” for judging another's trustworthiness due to the lack of other more informative and in-depth information about trustworthiness. Using data-driven statistical models of 3D Caucasian faces, we compared facial cues used for judging the trustworthiness of Caucasian faces by Caucasian participants who were highly experienced with Caucasian faces, and the facial cues used by Chinese participants who were unfamiliar with Caucasian faces. We found that Chinese and Caucasian participants used similar facial cues to judge trustworthiness. Also, both Chinese and Caucasian participants used almost identical facial cues for judging trustworthiness and attractiveness.The results suggest that without opportunities to interact with another person extensively, we use the less racially specific and more universal attractiveness cues as a “shortcut” for trustworthiness judgments

Zelda Binding in the Early Drosophila melanogaster Embryo Marks Regions Subsequently Activated at the Maternal-to-Zygotic Transition

The earliest stages of development in most metazoans are driven by maternally deposited proteins and mRNAs, with widespread transcriptional activation of the zygotic genome occurring hours after fertilization, at a period known as the maternal-to-zygotic transition (MZT). In Drosophila, the MZT is preceded by the transcription of a small number of genes that initiate sex determination, patterning, and other early developmental processes; and the zinc-finger protein Zelda (ZLD) plays a key role in their transcriptional activation. To better understand the mechanisms of ZLD activation and the range of its targets, we used chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-Seq) to map regions bound by ZLD before (mitotic cycle 8), during (mitotic cycle 13), and after (late mitotic cycle 14) the MZT. Although only a handful of genes are transcribed prior to mitotic cycle 10, we identified thousands of regions bound by ZLD in cycle 8 embryos, most of which remain bound through mitotic cycle 14. As expected, early ZLD-bound regions include the promoters and enhancers of genes transcribed at this early stage. However, we also observed ZLD bound at cycle 8 to the promoters of roughly a thousand genes whose first transcription does not occur until the MZT and to virtually all of the thousands of known and presumed enhancers bound at cycle 14 by transcription factors that regulate patterned gene activation during the MZT. The association between early ZLD binding and MZT activity is so strong that ZLD binding alone can be used to identify active promoters and regulatory sequences with high specificity and selectivity. This strong early association of ZLD with regions not active until the MZT suggests that ZLD is not only required for the earliest wave of transcription but also plays a major role in activating the genome at the MZT