AI has great potential to transform education and daily life. However, before integrating AI into classrooms, it is crucial to first educate children on what AI is and how to use it responsibly. Effective AI education should build on children's existing perceptions, address misconceptions, and establish a solid foundation for AI literacy. This study explores primary school students’ perception of AI and its relationship to their demographic characteristics and digital skills. A survey was conducted in seven local schools, with 233 students participating. The results indicate that most of them were unfamiliar with AI, and those who attempted to define or depict it often associated it with robots or digital devices. The study also found significant differences in students’ AI perceptions based on factors like gender, grade, and prior digital skills training. These variables were also linked to students’ awareness and understanding of AI. These findings underscore the need for targeted AI educational interventions for primary school students, leveraging their existing perceptions.

As AI technologies grow more influential in shaping modern life, there is an urgent need to make AI literacy accessible beyond academic and technical communities. This paper presents the design, delivery, and evaluation of an online AI course targeting the general public. The course combined asynchronous lectures, interactive live sessions, and reflective assignments. Of the 343 people who registered, 169 completed the program. Using validated instruments administered before and after the course, we measured changes in participants’ attitudes toward AI and their AI literacy. Our findings revealed statistically significant changes in AI literacy, specifically in awareness, usage, and evaluation constructs, as well as a rise in positive attitudes toward AI. High satisfaction scores and qualitative feedback further support the course’s effectiveness. These findings reinforce the importance of inclusive, scalable educational interventions for empowering the public to navigate AI technologies.

The widespread adoption of Generative AI (GenAI) tools by students across different educational levels highlights the need for them to develop robust GenAI literacy, including a working understanding of these systems' fundamental concepts, their limitations, and implications for responsible use. However, misconceptions about GenAI, such as perceiving these systems as mere search engines or database lookup systems, are commonly observed among students, while the availability of teaching resources remains fragmented, and learning objectives lack alignment. This Working Group aims to design pedagogical resources for computing science instructors, enabling them to develop students' GenAI literacy. To achieve this, the Working Group will first identify a concise set of GenAI literacy learning objectives informed by instructor experience, research literature, and community input, and subsequently design pedagogical resources aligned with these objectives.

Educational tools are increasingly used to introduce AI to children. However, there are few tools co-designed with teachers that aim to tackle the misconceptions children have about AI. This paper presents the results of a participatory design process aimed at creating educational tools that help primary school students develop AI literacy by addressing misconceptions of AI. Our two-phase process began with a workshop in which teachers were introduced to misconceptions children hold about AI and invited to co-design mock-ups for tools to address one of these misconceptions. Building on teachers' designs, we developed a prototype comprising three games that address the misconception that ''AI is always right.'' We then conducted two evaluation studies, one with the workshop participants and one crowdsourcing survey with primary school teachers. By analyzing survey responses, we examine teachers' …

Teens are increasingly interacting with AI systems in their everyday lives, yet many have a limited understanding of how these technologies function or what their limitations are. This highlights the need for early AI education. To create effective learning programs, it is crucial first to explore how teens perceive AI. This study examines the perceptions of middle school students about AI and their level of AI literacy, while also analyzing how factors such as demographics, attitudes, and prior training in digital skills influence these perceptions. Our findings show that students commonly view AI as tools or programs that deliver information or answers. Overall, participants demonstrated a moderate level of AI literacy and generally held neutral attitudes toward AI. Notably, gender, grade level, and digital skills training emerged as key influences on both AI literacy and perceptions. Furthermore, student attitudes, both positive and negative, were significantly associated with their level of AI literacy, with marked differences observed based on gender and previous exposure to training in digital skills.

AI systems are increasingly integrated into critical domains such as healthcare, law enforcement, education, and finance, often operating with limited transparency and raising concerns about fairness and ethics. As AI continues to shape society, it is crucial to equip individuals, especially teachers, with the knowledge and tools to critically evaluate these technologies. This paper explores how an educational tool - Canvas City - aimed at enhancing awareness of AI decision-making processes and their societal implications, might enhance AI literacy. A crowdsourcing experiment conducted with 90 teachers on Prolific evaluated the tool's effectiveness. Our findings reveal a disconnect between the acknowledged importance of AI education and its practical application in classrooms. Despite recognizing the value of teaching AI, many teachers lack the confidence, training, and resources necessary to effectively convey AI concepts. The study underscores how AI knowledge, confidence, and teaching capability influence teachers' views on the tool's educational value, highlighting the need for robust training programs and educational tools to facilitate effective AI instruction.

We all interact with AI daily, however, our understanding of it often remains limited. We present a training conducted as part of an Erasmus YE, with 36 individuals aged 18 to 30 from Austria, Armenia, Bulgaria, Latvia, Poland and Portugal. Our findings indicate that participants improved their AI literacy and recognized the value of such training, expressing that AI training is useful for everyone.

In today’s world, children are increasingly interacting with AI technologies as part of their daily routines. However, many children may not fully grasp how these technologies function or their implications. Misconceptions about AI capabilities, risks, and benefits abound, underlining the importance of early education on the subject. Designing educational tools and materials tailored for children necessitates a deep understanding of their existing knowledge and perceptions of AI. By leveraging children’s insights and experiences with AI, we can develop effective educational strategies that cater to their specific needs and enhance their understanding of this rapidly evolving technology.

As Artificial Intelligence (AI) continues to make its presence felt in transforming workplaces around the world, and the Information Technology industry in particular, it is essential to understand its impact on the work practices of IT professionals, and the implications for computing students and curricula. This research project builds on work initiated jointly, in Sweden, New Zealand and Scotland, investigating concerns about the increasing impacts of Artificial Intelligence in IT Sector workplaces for employee work engagement and the implications for tertiary study, assessment and curricula in computing. "Work engagement", has been defined as the positive inner state where employees are fully present and engaged in their work, and is closely linked to motivation, learning, productivity, and accountability. Within the context of (Generative) AI at work, IT professionals have been noted as early adopters of AI. Their involvement in implementing and utilising AI technologies can provide valuable insights into the interplay between AI and work engagement. The implications for students are significant as future IT professionals, who must acquire and enhance competencies to adapt and thrive in digital workplaces.

With the surge in data-centric AI and its increasing capabilities, AI applications have become a part of our everyday lives. However, misunderstandings regarding their capabilities, limitations, and associated advantages and disadvantages are widespread. Consequently, in the university setting, there is a crucial need to educate not only computer science majors but also students from various disciplines about AI. In this experience report, we present an overview of an introductory course that we offered to students coming from different majors. Moreover, we discuss the assignments and quizzes of the course, which provided students with a firsthand experience of AI processes and insights into their learning patterns. Additionally, we provide a summary of the course evaluation, as well as students' performance. Finally, we present insights gained from teaching this course and elaborate on our future plans.

Abstract Bias in news search engines has been shown to influence users' perceptions of a news topic and contribute to the polarisation of society. As a result, there is a need for news search engines that increase user awareness of biases in the search results. While technical approaches have been developed to mitigate biases in search, very few studies have investigated user preferences in interface designs for potentially raising their awareness of biases in news search engines. In this study, we utilized a participatory design methodology to develop eight prototypes with different features that could potentially be used to raise user awareness of biases in news search engines. We conducted three user studies, involving 132 participants with Computer Science backgrounds, to evaluate these prototypes. Our findings indicate the importance of news search engines that (a) inform users of possible biases in the results (bias visualization approach) and (b) allow users to access alternative search results (results‐reranking approach). Our study provides further insights into the strengths and possible risks of each approach, which are important for future research on designing interfaces for raising user awareness of biases in news search engines.

AI is progressively being incorporated into our daily lives, however, public awareness of AI is limited. AI literacy is and will continue to be an important skill for everyone. This project aims to investigate how various members of the public -- in particular, children, educators and adults -- perceive AI. Finally, it intends to promote AI literacy of the public and find the best practices for developing effective educational activities.

With the rise of data-driven AI and its "democratization", we are all interacting with AI-enabled technologies in everyday life. However, not everyone understands how these technologies work. There are many misconceptions surrounding what they can and cannot do, and what are the risks and benefits. Thus, there is a need to educate the general public about everyday AI, upscaling their algorithmic literacy and helping them become more informed, responsible users. We describe the development and evaluation of an eight-week course open to the public, AI in Everyday Life. Pre- and post-course questionnaires were used to evaluate the impact of the course and participants' attitudes towards AI applications. The results suggest that more targeted educational approaches are needed for the general public to fully understand the strengths and weaknesses of the use of AI-enabled technologies.

The increased involvement that AI plays in people's lives highlights the demand for greater public knowledge about AI. Lifelong learning environments are especially crucial for building AI literacy as they possess the ability to reach a larger audience and create opportunities for everyone to learn. This ongoing project aims at exploring the perception and understanding of AI by different members of the public (i.e., children, adults). In addition, it aims at promoting AI literacy among different groups of the public (e.g., educators, adults, elderly and children) through an open course and identifying the best practices for developing appropriate training activities for each group. As an initial step, a pilot study was conducted for investigating the response of the general public to a distance learning initiative and their educational needs for learning about AI. Results indicate that after attending a short course on AI, participants were able to understand and recognize what AI is, appreciate its positive and negative aspects, and most importantly, acknowledge the need for educating children and adults about AI. Finally, the results highlight that educating the general public about AI is a complex task that must be informed by further research. As a next step, questionnaires will be distributed in an attempt to understand how public perceive AI. Considering public's knowledge and understanding of AI, appropriate learning activities will be developed aiming to help different groups of the public to acquire the necessary skills related to AI literacy.

Professionals are increasingly relying on algorithmic systems for decision making however, algorithmic decisions occasionally perceived as biased or not just. Prior work has provided evidences that education can make a difference on the perception of young developers on algorithmic fairness. In this paper, we investigate computer science students' perception of FATE in algorithmic decision-making and whether their views on FATE can be changed by attending a seminar on FATE topics. Participants attended a seminar on FATE in algorithmic decision-making and they were asked to respond to two online questionnaires to measure their pre- and post-seminar perception on FATE. Results show that a short seminar can make a difference in understanding and perception as well as the attitude of the students towards FATE in algorithmic decision support. CS curricula need to be updated and include FATE topics if we want algorithmic decision support systems to be just for all.