Intelligent User Research Articles

Extended artificial intelligence aversion: People deny humanness to artificial intelligence users.

Artificial intelligence (AI) tools are often perceived as lacking humanlike qualities, leading to a preference for human experts over AI assistance. Extending prior research on AI aversion, the current research explores the potential aversion toward those using AI to seek advice. Through eight preregistered studies (total N = 2,317) across multiple AI use scenarios, we found that people denied humanness, especially emotional capacity and human nature traits, to AI advice seekers in comparison to human advice seekers (Studies 1-5 and S1-S3). This is because people perceived less similarity between themselves and AI advice seekers (vs. human advice seekers), with a stronger mediating role of perceived similarity among individuals with greater aversion to AI (Studies 2 and S1). Dehumanization of AI advice seekers predicted less behavioral support for (Study 3) and helping intention toward (Studies S2 and S3) them and could be alleviated through anthropomorphism-related interventions, such as perceiving humanlike qualities in AI or utilizing generative AI (Studies 4 and 5). These findings represent an important theoretical step in advancing research on AI aversion and add to the ongoing discussion on the potential adverse outcomes of AI, focusing on AI users. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Designing a Tactile Document UI for 2D Refreshable Tactile Displays: Towards Accessible Document Layouts for Blind People

Understanding document layouts is vital for enhancing document exploration and information retrieval for sighted individuals. However, for blind and visually impaired people, it becomes challenging to have access to layout information using typical assistive technologies such as screen readers. In this paper, we examine the potential benefits of presenting documents on two-dimensional (2D) refreshable tactile displays. These displays enable the tactile perception of 2D data, offering the advantage of dynamic and interactive functionality. Despite their potential, the development of user interfaces (UIs) for such displays has not advanced significantly. Thus, we propose a design of an intelligent tactile user interface (TUI), incorporating touch and audio feedback to represent documents in a tactile format. Our exploratory study for evaluating this approach revealed satisfaction from participants with the experience of directly viewing documents in their true form, rather than relying on screen-reading interpretations. Additionally, participants offered recommendations for incorporating additional features and refining the approach in future iterations. To facilitate further research and development, we have made our dataset and models publicly available.

Оценка антропологического воздействия интерфейсов на этапе проектирования программно-аппаратного обеспечения

In the information society, as the scope of human activity expands and deepens, continuous formalisation occurs, underpinned by ontological models of technical and natural systems. The user's perception of comprehensive information about a complex subject area leads to information overload. This situation encourages the use of algorithms that present information in a compressed form. The paper introduces modified indicators and qualitative criteria to estimate the potential for errors in compressing subject area information, as well as evaluate the anthropometric nature of the interface using threshold values set by experts, both for artificial intelligence algorithms and users. A method is proposed for quantitatively assessing the anthropological impact of application-level interfaces during the design stage of hardware and software. The method consists of eight stages, which assess the comprehensibility of the hardware and software interface for both artificial intelligence algorithms and users. This approach reduces the likelihood of developing destructive hardware and software systems.

Supplemental Material for Extended Artificial Intelligence Aversion: People Deny Humanness to Artificial Intelligence Users

Supplemental Material for Extended Artificial Intelligence Aversion: People Deny Humanness to Artificial Intelligence Users

Generative AI and Media Content Creation: Investigating the Factors Shaping User Acceptance in the Arab Gulf States

This article aims to investigate the factors that affect behavioural intention (BI) and user behaviour (UB) among Arabian users of generative artificial intelligence (GenAI) applications in the context of media content creation. The study’s theoretical framework is grounded in the unified theory of acceptance and use of technology (UTAUT2). A sample of 496 users was analysed using the partial least squares structural equation modelling technique (PLS-SEM). The results revealed that BI is significantly influenced by performance expectancy, effort expectancy, social influence, hedonic motivation, habit, and user trust, with hedonic motivation having the greatest impact. In terms of UB, facilitation conditions, habit, user trust, and BI were all found to have a positive and significant impact. This study contributes to the existing theory on the utilisation of GenAI applications by organising findings pertaining to the use of AI technology for media content creation.

Analysis of Studies Based on Türkiye Examining the Relationship between Artificial Intelligence and Education: A Meta Synthesis Study

Artificial intelligence is defined as human-made systems that mimic the thinking, perception, and learning abilities of the human brain, using the information they gather and having the ability to improve themselves. With the changes and developments in the field of technology, the use of artificial intelligence has also expanded. The increasing popularity of artificial intelligence in the field of education has led to a rise in research on this topic. This paper aims to synthesize the existing literature on the applications of artificial intelligence in education within a specific time frame and to develop a holistic perspective. In the paper, 20 studies written in the last five years on artificial intelligence and education were examined using the metasynthesis method. The research question is defined as: "What trends exist in academic research on artificial intelligence and education conducted in Turkey over the past five years?" The data source for the research was determined using the criterion sampling method. For this purpose, a detailed search was conducted in databases such as Google Scholar, Academia, TÜBİTAK ULAKBİM, and Dergipark using the keyword "artificial intelligence and education." As a result of the analyses, it was found that while the study emphasizes the contributions of artificial intelligence to the field of education, there are also some concerns on the subject. The contributions of artificial intelligence, particularly in terms of providing personalized learning experiences, saving time, and improving student performance, were highlighted, but concerns were raised regarding data privacy and the ethical principles in the use of artificial intelligence. Additionally, it was found that there are educational and developmental needs for artificial intelligence users.

Intelligent User Experience Design in Digital Media Art under Internet of Things Environment

Intelligent User Experience Design in Digital Media Art under Internet of Things Environment

An Early Snapshot of Attitudes Toward Generative Artificial Intelligence in Physical Therapy Education

Introduction. Generative artificial intelligence (AI) is rapidly gaining popularity across health care, education, and society. The purpose of this study was to assess perceptions and use of generative AI in academic physical therapy (PT). Review of Literature. Generative AI became one of the fastest-growing technologies ever after the public release of ChatGPT in November 2022. Early data indicate that attitudes toward generative AI in higher education are mixed and rapidly evolving, with significant ethical concerns around use and potential misuse. There are no published studies investigating perceptions and use of generative AI in PT education. Subjects. A total of 175 surveys were completed and analyzed. Respondents included PT educators, administrators, and students. Methods. An anonymous, online survey on use and perception of AI was distributed through email and social media. Descriptive statistics and cross-tabulations were performed to analyze respondent characteristics and responses to survey questions. Results. Most respondents (61.1%) reported they did not use generative AI during the 2022-2023 academic year, whereas 35.4% were generative AI users. More than 40% of respondents were optimistic or very optimistic toward generative AI. Users of AI were more likely to report an optimistic or very optimistic disposition toward AI compared with nonusers. AI users were more likely to agree or completely agree that generative AI has more benefits than drawbacks compared with nonusers. Discussion and Conclusion. Results of this survey suggest that, despite the rapid uptake of generative AI in society, many PT educators and students harbor reservations and uncertainties toward its use. Artificial intelligence users were less likely to hold negative perceptions toward it and were more likely to find it useful. Understanding use and perceptions of generative AI in PT education may inform strategies to promote innovation, policy-making, and ethical integration of this new and rapidly evolving technology.

Synthesizing a three Layer Architectural Framework for Adaptive Intelligent User Interfaces for the Disabled Community

Knowledge acquisition has been a bottleneck in the design for efficient User Interfaces for Disabled Community. The best suited interfaces have been oriented towards adaptability that is the User Interface needs to adapt and configure itself according to the needs and likes of the user. Such user interfaces can arouse interest in the mind of the disabled and motivate them to become an asset to the nation, and use their intellect to contribute to the society. This study pioneers an innovative approach, aiming to develop User Interfaces (UIs) for the Disabled Community. The research introduces a comprehensive three-layer architectural framework employing Learning, Trust, and Knowledge Models. Unlike conventional approaches, this Architectural Framework is designed to learn not only from the Disabled but also from their Assistants/Guides, employing principles of knowledge engineering. While the former offers static context, the latter contributes dynamic insights by observing behaviors, responses, and actions of the Disabled. This symbiotic relationship forms the foundational basis for developing intelligent adaptive UI’s that not only accommodate but actively engage and motivate the Disabled Community. The proposed research methodology involves a meticulous gathering of data through extensive user studies and interactions. By using the Human Computer Interface technology, the study aims to develop a robust framework capable of comprehensively understanding the preferences, needs, and nuances of disabled users. The expected outcomes include the development of a prototype adaptive UI, validated through rigorous testing and feedback from the disabled community. Additionally, the study anticipates contributing a comprehensive set of guidelines and best practices for designing intelligent adaptive UIs, ensuring comfort and ease for impaired users, boosting their confidence and encouraging greater involvement in socio-development activities.

Research on intelligent building decoration design and user experience based on VR technology

The continuous development of virtual reality (VR) technology has been widely used in all walks of life, bringing unprecedented design possibilities and user experience improvement to the field of architectural decoration design. This paper aims to explore how to use VR technology for intelligent building decoration design and evaluate its impact on user experience through empirical research. Firstly, through the review of relevant literature at home and abroad, the application status and development trend of VR technology in architectural decoration design is sorted out. Then, the design process and implementation scheme based on VR technology are introduced in detail, and the design framework suitable for different application scenarios is constructed. Then, through the design of the user experience evaluation index system, using the combination of qualitative and quantitative methods, the intelligent decoration design scheme based on VR technology is systematically evaluated. Finally, select a typical case for in-depth analysis, show the application effect of VR technology in actual projects, and summarize the feedback of users. The research results show that the intelligent building decoration design based on VR technology can not only improve the design efficiency and quality but also significantly enhance the user's sense of immersion and satisfaction, providing a new perspective and development direction for future architectural design. In addition, this paper also points out the challenges in this field and the possible research directions in the future, which provides a valuable reference for subsequent scholars.

Principles of constructing mental models of a solution for external users in the task of generating explanations in an intelligent system

The subject of the research is the process of constructing user mental models in intelligent information systems. The aim is to improve the principles of building mental models of external users regarding the decisions of an intelligent information system to form explanations in accordance with both the needs of these users and the limitations on the use of solutions in a specific subject area. Objectives: improvement of existing principles of mental model construction based on structuring the description of the intelligent system's solution; development of a principle for constructing mental models of the intelligent system user, considering the limitations when using the obtained solution. The scientific novelty of the obtained results is as follows. The existing principles of human mental model construction have been adapted, considering the differences in constructing explanations for a solution in an intelligent system represented as a «black box». The adapted principles consider the correspondence between the structure of the mental model and the solution, the multiplicity of mental models regarding the solution, and the incompleteness of input data for decision-making. The principle of input data supplementation is proposed, which consists in using the values of solution properties that are irrelevant from the user's point of view to limit the set of relevant solutions. The use of this principle in constructing an explanation makes it possible to consider the negative aspects of using the obtained result and thereby simplify the user's choice and application of this solution.

Legal Liability Arising from Artificial Intelligence Activities

Criminal liability concept has become widespread in light of the increasing use of artificial intelligence technologies all life aspects and it is within a wide scope that requires urgent legislative intervention. With this use of artificial intelligence, many artificial intelligence crimes have emerged in all areas of artificial intelligence in addition to problems in determining criminal liability. This study aimed to investigate artificial intelligence characteristics, clarify the legal responsibility resulting from the actions of artificial intelligence and to determine the penalty resulting from artificial intelligence actions. Results indicated that the legal responsibility resulting from the artificial intelligence actions, which has emerged at the present time after the expansion of the use of these technologies in all sectors of life is inseparable from the responsibility of the innovator, part of the factory, or all of the responsibility of each individual. Intervention in all areas of work through artificial intelligence. The study recommended with the necessity of establishing mechanisms to monitor the work that falls within artificial intelligence techniques by specialists for the purpose of avoiding technical errors that affect the safety of users of artificial intelligence technique.Artificial Intelligence

Thinking critically about scientific information generated by ChatGPT

PurposeIn November 2022, the commercial company, OpenAI, launched ChatGPT. Since then, university students have rapidly become regular users of this artificial intelligence (AI) platform. One reason for this is the powerful capability of this generative AI tool to produce textual content, which in many cases, is almost indistinguishable from human-generated content. Another reason is that ChatGPT easily gives anyone access to knowledge. However, there is a problem as the vast majority of its users have no idea how this AI platform works and thus overlook the importance of thinking critically about information communicated in ChatGPT. While some call for banning this generative AI tool, this study aims to provide evidence that science classrooms can become scenarios where students find explicit, concrete, and realistic opportunities to critically evaluate scientific information generated by ChatGPT.Design/methodology/approachAn intervention study was conducted with 55 students (26 females and 29 males, 17–24 years old) during a university Spanish-English bilingual science course taught within an active learning environment. The data consist of the written critiques of the students about Spanish-English bilingual scientific texts produced by ChatGPT.FindingsResults indicate that the intervention had a positive effect on students’ abilities to construct sound arguments in Spanish and in English while judging the quality of scientific texts produced by this AI bot. Moreover, the findings suggest that the intervention enriched students’ skills to make improvements to texts produced by this generative AI tool.Originality/valueThe evidence provided in this study contributes to the exploration of possibilities to help students become critical users of ChatGPT.

Generative AI as a Strategic Intelligent User Interface for Human-AI Collaboration

Generative AI as a Strategic Intelligent User Interface for Human-AI Collaboration

Artificial Intelligence, Big Data, and Information System User Experience: A Comprehensive Approach to Cross-cultural Adaptation in Educational Management of International Students

This study analyses how AI integration, Big Data, information system quality, and cultural variables affect foreign student education and cross-cultural adaption. We discover patterns and connections in technological and cultural aspects affecting educational effectiveness using Explainable AI (XAI) and machine learning. The study found that big data, AI integration, and high-quality information systems increase international student user experience. Collectivism may prefer collaboration, whereas individualism may prefer tailored AI learning. Moderation shows that student culture strongly impacts technological interventions, highlighting the need for culturally suitable instructional technology. AI integration, big data use, and high-quality information systems boost user experience and academic performance more in China than in Pakistan. To help international students succeed, schools must use technology and culturally sensitive management. Schools must use technology with student culture in mind. Create technologically advanced and culturally flexible educational management solutions for all pupils. This study found that AI integration, big data, information system quality, and culture affect international students' education and performance. The research helps schools choose and manage technology to help foreign students succeed.

Research on the Influence of Humor Response in the Context of Artificial Intelligence Service Failure: Moderating Effect Based on User Humor

With the development of high and new technology, artificial intelligence technology has been widely used in all walks of life. However, limited by the technical development level and the complexity of the service environment, the failure of artificial intelligence robots is inevitable. How to make an effective remedy has become the focus of attention of enterprises and academia. Based on cognitive-affective system theory of personality, benign violation theory and personality trait congruence theory, this paper conducts three situational experiments. This paper explores the relationship between artificial intelligence humor response, perceived sincerity and user forgiveness in the context of artificial intelligence service failure, and discusses the moderating effect of user humor degree. It is found that artificial intelligence humor response has a positive effect on user forgiveness in the context of service failure, and perceived sincerity plays a part of mediating role. In addition, for users with different degrees of humor, the same humorous reply will cause users to perceive different sincerity, and then lead to different users' forgiveness. This study complements the research on consumer psychology and behavior theory and remedy strategies in the context of service failure by artificial intelligence robots. At the same time, it provides a reference for enterprises how to dynamically adjust the artificial intelligence humor response level according to the user portrait, and further provides practical enlightenment for enterprises to implement effective remedy strategies.

Evolutionary regulatory dynamics in a pluralist and polarized journalism landscape: a case study of the normative framework in Spanish media

Within the European Union, the pluralist polarized journalistic model suggests the presence of journalistic cultures rooted in the connections between political parties and media organizations. In this classical framework, the state exerts significant intervention to influence a media system characterized by lower levels of professionalization. In this regard, Spain serves as a well-examined example of a pluralist polarized Western democracy. Our study entails a systematic review based on two distinct dimensions. Firstly, we scrutinized all legal documents pertaining to media regulation in Spain published between the Spanish transition and the present 1977–2024. From this perspective, we propose a chronological evolution to categorize this extensive collection of norms. Secondly, we complement our primary source assessment with an examination of secondary sources to validate the proposed evolution. Our findings indicate that the Spanish media regulation is evolving due to two pivotal factors: the influence of the European Union and the preservation of the narrative established during the transition to democracy. While contemporary communication grapples with issues such as the rise of artificial intelligence, journalistic instability, algorithmic communication, and fragmented user consumption, these areas are only addressed peripherally within the Spanish media normative context.

Exploration of a method for insight into accessibility design flaws based on touch dynamics

The widespread use of smartphones implies that intelligent systems must address the negative emotions experienced by a diverse user group when encountering usability difficulties. Therefore, exploring the relationship between users’ emotions and operational behaviors is crucial for further enhancing the accessibility of intelligent systems. Touch dynamics, as a method of dynamic touch data monitoring, has already provided many models for emotion recognition, which are beneficial in gaining insight into users’ accessibility needs for smartphones and exploring intelligent solutions to design issues. This paper validates this aspect through interviews and experimental studies. The study first conducted an open-ended interview, and then used a touch behavior experiment with emotional labels and a questionnaire to validate the association between accessibility design flaws in intelligent systems and user emotions. The interview results show that middle-aged and older smartphone users have difficulty activating accessibility tools independently. Consequently, this paper establishes a dataset for emotion classification based on touch gesture data, which is used to gain insight into implicit difficulties in the interaction process through negative emotions. From a touch experiment and questionnaire survey of 57 sample users, there is approximately a 78.57% match between the accessibility needs of intelligent systems and users’ negative emotions, with interaction fluency and interface cognition being the main reasons for this phenomenon. Therefore, touch dynamics, as a non-invasive method of emotion recognition, can use negative emotional feedback to gain insights into user needs that are difficult to detect by other methods. This has application value for enhancing users’ emotional experience and promoting a transformation in interaction design thinking.

Earthquake prediction using satellite data: Advances and ahead challenges

Due to the considerable loss of life and damages caused by powerful Earthquakes, along with the strengthening of structures and disaster management systems, many researches are being conducted associated with the possibility of creating Earthquake warning systems. However, no reliable scientific report on successful Earthquake prediction has been published so far. Although there are a couple of published scientific papers indicating the detection of unusual changes in physical and chemical parameters obtained from ground stations, but due to the limitations of in-situ measurement in terms of number, location, time and cost, there was no noticeable progress in Earthquake warning. After the advent of remote sensing satellites, the number of statistical studies related to Earthquake precursors increased significantly, and most of them emphasized the existence of abnormal behaviors in physical and chemical precursors around the time (about 1–30 days before) and locations of powerful Earthquakes. In this study, an attempt has been made to address the advances and challenges in the way of Earthquake prediction using satellite data and provide a perspective of the future of these researches. It should be noted that the increase in the number of satellites designed and launched specially for Earthquake studies, the variety of available Earthquake precursors (multi-precursor analysis), the development of classic and intelligent anomaly detection and predictor algorithms (multi-method analysis), the provision of intelligent systems for the integration of various precursors (fusion and decision systems), the creation of cloud storing and processing data services (Google Earth Engine, Giovanni, etc.) and the development of intelligent user interfaces for public, have made researchers more hopeful for the appearance of low-uncertainty Earthquake warning systems in the near future.

OpenWeedGUI: An Open-Source Graphical Tool for Weed Imaging and YOLO-Based Weed Detection

Weed management impacts crop yield and quality. Machine vision technology is crucial to the realization of site-specific precision weeding for sustainable crop production. Progress has been made in developing computer vision algorithms, machine learning models, and datasets for weed recognition, but there has been a lack of open-source, publicly available software tools that link imaging hardware and offline trained models for system prototyping and evaluation, hindering community-wise development efforts. Graphical user interfaces (GUIs) are among such tools that can integrate hardware, data, and models to accelerate the deployment and adoption of machine vision-based weeding technology. This study introduces a novel GUI called OpenWeedGUI, designed for the ease of acquiring images and deploying YOLO (You Only Look Once) models for real-time weed detection, bridging the gap between machine vision and artificial intelligence (AI) technologies and users. The GUI was created in the framework of PyQt with the aid of open-source libraries for image collection, transformation, weed detection, and visualization. It consists of various functional modules for flexible user controls and a live display window for visualizing weed imagery and detection. Notably, it supports the deployment of a large suite of 31 different YOLO weed detection models, providing flexibility in model selection. Extensive indoor and field tests demonstrated the competencies of the developed software program. The OpenWeedGUI is expected to be a useful tool for promoting community efforts to advance precision weeding technology.