Horia Alexandru Maior

As of November 2022—following the release of OpenAI’s ChatGPT—the general public’s awareness of generative AI, and specifically Large Language Models (LLMs) has increased. LLMs such as ChatGPT now have the capability to generate text indistinguishable from human authored text, which comes with numerous risks. In this paper, we investigate public perception and willingness to use LLMs as a substitute for legal advice from legal professionals. Our findings show that while few people have used it for this purpose, the willingness to rely on LLMs in the future is growing. Interestingly, this depends on the specific area of law, and while LLMs are perceived to be highly valuable in relation to topics such as tenancy and tax law, they seem to be perceived as less valuable in contexts such as divorce or civil disputes.

Domestic robots are fast becoming an integrated part of daily life. In anticipation of increased uptake of robotic assistants in the home, researchers and designers must investigate what makes domestic robotic interventions trustworthy or untrustworthy as a matter of urgency. This paper explores the concept of failure in domestic robotics, using the case of a dishwasher robot, and its impact on trustworthiness. It asks what constitutes trust, what constitutes failure, and what are the impacts failure may have on service providers, users, and the robot itself. We present the findings from four workshops with robotics experts and potential end users. We show that failure is simultaneously complex and predictable and re-evaluate existing taxonomies of failure, applying them to the domestic sphere, thereby highlighting social and corporate facets of failure that are not currently represented. We also provide a new taxonomy of failure outcomes to highlight how failures can breach trust, and what effects that breach may have.

Telepresence robotics enable people to synchronously communicate and interact at a distance. The Covid-19 pandemic caused in-person teaching and research activities to migrate online in almost all society sectors (including higher education). In hybrid learning environments, telepresence robots have the potential to increase the effectiveness of distance learning by enhancing user presence, allowing students to remain physically embodied and socially connected. However, to be accepted, trusted, and adopted in higher education, more work is needed to investigate the specific requirements of telepresence robotics in these settings. In this paper, we present the results of a mixed methods study exploring how the use of a telepresence robot in a simulated learning and research environment affects trust in and user experience of telepresence robots used in higher education. We aimed to understand users’ attitudes and requirements for the use of telepresence robots in academic teaching and research. Our findings suggest that the level of trust is contingent upon the user, the performance of the robot, and the credibility of the developing organisation. We additionally map out the current challenges encountered by the use of telepresence robots in these settings and provide suggestions to improve user experience by highlighting new software and hardware capabilities.

While Human-Computer Interaction (HCI) has contributed to demonstrating that physiological measures can be used to detect cognitive changes, engineering and machine learning will bring these to application in consumer wearable technology. For HCI, many open questions remain, such as: What happens when this becomes a cognitive form of personal informatics? What goals do we have for our daily cognitive activity? How should such a complex concept be conveyed to users to be useful in their everyday lives? How can we mitigate potential ethical concerns? This is different to designing BCI interactions; we are concerned with understanding how people will live with consumer neurotechnology. This workshop will directly address the future of Cognitive Personal Informatics (CPI), by bringing together design, BCI and physiological data, ethics, and personal informatics researchers to discuss and set the research agenda in this inevitable future.

Cognitive style has been shown to influence users’ interaction with search interfaces. However, as a fundamental dimension of cognitive styles, the relationship between the Verbal-Imagery (VI) cognitive style dimension and search behaviour has not been studied thoroughly, and it is not clear whether VI cognitive style can be used to inform search user interface design. We present a study (N=29), investigating how search behaviour and mental workload (MWL) changes relate to VI cognitive styles by examining participants’ search behaviour across three increasingly complex tasks. MWL was subjectively rated by participants, and blood oxygenation changes in the prefrontal cortex were measured using functional near-infrared spectroscopy (fNIRS). Our results revealed a significant difference between verbalisers and imagers in search behaviour. In particular, verbalisers preferred a Sporadic navigation style and adopted the Scanning strategy as they processed information, according to their viewing and bookmarking patterns, whereas imagers preferred the Structured navigation style and reading information in detail. The fNIRS data showed that verbalisers had significantly higher blood oxygenation in the prefrontal cortex when using the same search interface, suggesting a higher MWL than imagers. When based on task complexity bias, the search time significantly increased as task complexity increased, but there were no significant differences in search behaviours. Our study indicated that VI cognitive styles have a noticeable and stronger impact on users’ searching behaviour and their MWL when interacting with the same interface than task complexity, which can be considered further in future search behaviour studies and search user interface design.

While Human-Computer Interaction (HCI) has contributed to demonstrating that physiological measures can be used to detect cognitive changes, engineering and machine learning will bring these to application in consumer wearable technology. For HCI, many open questions remain, such as: What happens when this becomes a cognitive form of personal informatics? What goals do we have for our daily cognitive activity? How should such a complex concept be conveyed to users to be useful in their everyday life? How can we mitigate potential ethical concerns? These issues are different from physiologically controlled interactions, such as BCIs, to a time when we have new data about ourselves. This workshop will be the first to directly address the future of Cognitive Personal Informatics (CPI), by bringing together design, BCI and physiological data, ethics, and personal informatics researchers to discuss and set the research agenda in this inevitable future before it arrives.