Programma della conferenza

Artificial Intelligence has been a part of journalism since the Associated Press embraced it in 2014, experiencing a significant surge with the advent of OpenAI's ChatGPT in late 2022. This period marks an era of exploration into GenAI's future role in journalism, as leading publishers like the BBC, Reuters, NYT, and Financial Times transparently initiate task forces to weave GenAI into news production processes. This paper presents a systematic literature review based on searches in Scopus and Google Scholar including terms "GenAI and Journalism," "machine learning and journalism," "artificial intelligence and journalism," "automating news," and "bot+journalism." Additionally, over 300 articles published in global media from the first use of GenAI (January 2023) to the end of March 2024 were analyzed. These articles were categorized based on themes such as News Production, responsible AI, misinformation, fact-checking, education and training, AI Strategy, and AI Tools.The dual aspects of GenAI in journalism emerge distinctly. Ethical concerns and the potential for misinformation pose significant risks to democracy, complicating the distinction between authentic and AI-generated content, alongside issues like plagiarism, "hallucinations," opaque communication, and the threat of displacing journalists. However, GenAI also holds potential as a catalyst for creative news production and can enhance investigative journalism if applied with strict controls, reader-centric motivations, and adherence to the enduring principles of journalism: truth and transparency. The study underscores the need for an ethical framework guiding AI's journalistic use, arguing that, with conscientious human oversight, GenAI can significantly transform journalism, balancing technological innovation with journalistic integrity

In relation to developments in Visual Generative AI (Combs, Moyer, Bihl, 2024), this contribution wants to focus on the generation of images through the recursive prompting (Yang, et al. 2022). In particular, the reference is to the production of the manifesto, a visual textual form analysed as an image-suitcase within a semio-pragmatic approach (Odin, 2011). This image is the bearer of different iconic signifiers which refer to distinct meanings that intersect and whose general meaning is defined in relation to the context in which it is produced and received. The image-manifesto condenses what circulates in an expanded and disorderly way and isolates the main axes and values of a content (Pezzini, 2008). In this sense, the manifesto also has a dynamic function within a broad social and cultural discursiveness that brings together different texts and practices with even the biases involved in their constitution (Fabbrizzi, et al. 2022; Panciroli, Rivoltella, 2023). Specifically, the contribution proposes an analysis of the generative stories of these textual forms, set up within the Manifesto Rooms of the MOdE- Digital Museum of Education, University of Bologna (Panciroli, et al. 2020). These are digital environments in which the visitor can interact with Visual Generative AI tools to create an image-manifesto, showing both the final product and the intermediate visual contents that enables its elaboration. The aim is to analyse the cognitive surplus (Shirky, 2010) related to the visual generation of AI with respect to the initial inputs, formulated through a succession of text-to-image and image-to-image prompts.

Climate change is progressively changing the nature of work in various occupations and the skills required of many workers even in the STEM fields. Education at all levels, including higher education, should face with these changes, adapt to new challenges and conditions, and change its approach to teaching.

Traditionally, hard skills have been considered essential, yet several studies highlight the crucial role of soft skills in rapidly changing working environments. Therefore, the ability to develop these skills as part of a holistic approach to the 'greening' of the economy is essential for educators, as their students are future workers and potential change agents in the green industry.

The findings of this research provide some interesting insights for STEM educators. Soft skills are widely recognised, but green soft skills are not well known. Communication, empathy, and problem-solving are particularly useful for the green transition. This essentially involves changing mindsets, working in multidisciplinary environments, and influencing employees and customers.

The connection with industry stakeholders as co-designer or simply contributors to the learning experience, and collaboration between faculties, fostering transdisciplinarity, can be a leverage to develop such skills.

The prevalence of video-based learning has significantly increased in contemporary educational settings, yet this widespread adoption is not without inherent challenges. One of the primary concerns involves the limited awareness teachers have regarding how students are engaging with the video content: are the concepts being clearly understood, or are there challenging segments that not all students grasp? What questions do students have? What comments might they have? To confront this challenge, Evoli, a video-annotation system aimed at collecting student feedback was developed, to enhance educator awareness. This innovation was conceived within the framework of Design Based Research, characterized by iterative cycles of design, deployment, analysis, and redesign. The initial design allowed the acquisition of feedback from students: time-stamped questions and self-assessment of understanding. In the second iteration, learning analytics were added, facilitated by artificial intelligence algorithms, to construct comprehensive learner profiles by integrating both sets of data. The tool was initially implemented in a real-world setting, involving four courses at a technical university, followed by a deployment in a controlled laboratory environment. To date, it has engaged more than 600 students. The integration of student feedback with usage data distinguishes the tool from the state of the art and enables the provision of comprehensive dashboards to educators that reveal how students engage with and respond to instructional videos, both as a cohort and on an individual level. This innovation paves the way for the enhancement of instructional design in in-person sessions and the personalization of teaching approaches.