Applied Social Studies - Conference Items
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Item Teaching practices and reflections on AIGC in brand advertising design(Springer Nature, 2024-06-08) Wei, Dong; Li, Lingxuan; You, ZongyuanGenerative Artificial Intelligence (AIGC) technology has been quickly evolving since 2022, with advertising becoming one of its most popular applications. This opens up new potential and difficulties for current and future brand advertising design education. This article investigates AIGC's design thinking transformation in brand advertising design using the course “AIGC: Machine-Assisted Innovative Design for Brand Advertising” offered at Communication University of China (CUC) during the summer semester of 2023. The goal is to help students comprehend AI art and machine learning, to break down the homogenization of AIGC-generated outcomes from an art and design standpoint, and to develop students’ critical thinking skills so that they can reconsider the creative value of the human brain. The course is structured into two parts: the first part focuses on learning and experiencing AIGC technologies such as ChatGPT, Midjourney, Runway, and others, and applying them thoroughly in design practice. The second half of the course focuses on China Chic brand advertisements and uses hand-drawing, computer-aided design, and AICG to create a whole case design. The course findings demonstrate that AIGC tools have a high level of innovation in the creative process, but there are some issues such as uncontrollability and homogeneity that require humans to spend more time and energy adapting. Students agreed that generative AI can be an effective technique to inspire human creativity, and that when employing AIGC tools, designers should look for ways to collaborate with AI rather than viewing it as a total replacement for humans.Item Privacy preserving loneliness detection: A federated learning approach(Institute of Electrical and Electronics Engineers (IEEE), 2022-08-24) Qirtas, Malik Muhammad; Pesch, Dirk; Zafeiridi, Evi; Bantry White, Eleanor; Science Foundation IrelandToday's smartphones have sensors that enable monitoring and collecting data on users' daily activities, which may be converted into behavioral indicators of users' health and well-being. Although previous research has used passively sensed data through smartphones to identify users' mental health state, including loneliness, anxiety, depression, and even schizophrenia, the issue of user data privacy in this context has not been well addressed. Here we focus on the feeling of loneliness, which, if persistent, is associated with a number of negative health outcomes. While modern artificial intelligence technology, specifically machine learning, can assist in detecting loneliness or depression, current approaches have applied machine learning to centrally collected user data at a single location with the potential to compromise user data privacy. To address the issue of privacy, we investigated the feasibility of using federated learning on single user data to identify loneliness collected by different smartphone sensors. Federated learning can help protect user privacy by avoiding the transmission of sensitive data from mobile devices to a central server location. To evaluate the federated method's performance in detecting loneliness, we also trained models on all user data using a centralised machine learning approach and compared the results. The results indicate that federated learning has considerable promise for detecting loneliness in a binary classification problem while maintaining user data privacy.Item Saying it out loud: how Rights theory frames and shapes practice for students with ID in a university setting(joinIN – Inclusive Higher Education Network Europe, 2022-10) Maxwell, Nicola; Leane, Máire; European CommissionThis paper tells the story of the development of a rights-based education programme for students with intellectual disability (ID) in one Irish university, the University College Cork (UCC). It explores how the philosophy underpinning the programme has emerged from an instinctive response to the segregation and isolation of people with ID into a more clearly articulated commitment to a model of provision based on a commitment to human rights. This represents a paradigm shift in how we view and work with people with ID and marks a break from traditional paternalistic and charity-based approaches to provision. Articulating what we are doing and why we are doing it, is vital for developing communities of inclusive practice who are sustained by an ongoing process of reflection, disruption, and reimagining.Item The changing landscape of local and community development in Ireland: policy and practice(The Institute for Social Sciences in the 21st Century (ISS21), University College Cork, 2016-04) Forde, Catherine; O'Byrne, Déirdre; O'Connor, Ray; Ó hAdhmaill, Féilim; Power, Carol; University College Cork