Inclusive Learning Analytics with Embedded Data Comics: A Conceptual Framework for Public Understanding of AI Ethics

• URL: http://arxiv.org/abs/2604.22322v1
• Date: Fri, 24 Apr 2026 07:51:38 GMT
• Title: Inclusive Learning Analytics with Embedded Data Comics: A Conceptual Framework for Public Understanding of AI Ethics
• Abstract summary: This review paper proposes a conceptual framework for inclusive learning analytics with embedded data comics.<n>By providing equal and easily accessible channels for AI ethics issues, we aim to encourage the public to reflect on AI ethics incidents from multiple perspectives.
• Score: 4.304297868990205
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Public awareness of AI ethics plays a crucial role in fostering the responsible and sustainable development of AI technology. However, finding effective ways to promote public understanding of the ethical risks of AI remains a challenge. Given the complexity of AI ethical issues and the cognitive limitations of the public, this review paper proposes a conceptual framework for inclusive learning analytics with embedded data comics. Data comics help transform complex and abstract AI ethics cases into compelling and relatable stories, fostering public empathy and introspection. More importantly, inclusive learning analytics targets not only people of different demographic attributes, but also different mindsets with inherent cognitive biases. By providing equal and easily accessible channels for AI ethics issues, we aim to encourage the public to reflect on AI ethics incidents from multiple perspectives and develop the habit of continuous learning to adapt to evolving AI technologies and ethical risks.

Related papers

• Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science [48.38628297686686]
  Cognitive Science has profoundly shaped disciplines such as Artificial Intelligence (AI), Philosophy, Psychology, Neuroscience, Linguistics, and Culture.<n>Many breakthroughs in AI trace their roots to cognitive theories, while AI itself has become an indispensable tool for advancing cognitive research.<n>We argue that the future of AI within Cognitive Science lies not only in improving performance but also in constructing systems that deepen our understanding of the human mind.
  arXiv  Detail & Related papers  (2025-08-28T11:26:17Z)
• AI Identity, Empowerment, and Mindfulness in Mitigating Unethical AI Use [0.0]
  This study examines how AI identity influences psychological empowerment and unethical AI behavior among college students.<n>Findings show that a strong AI identity enhances psychological empowerment and academic engagement but can also lead to increased unethical AI practices.<n>IT mindfulness acts as an ethical safeguard, promoting sensitivity to ethical concerns and reducing misuse of AI.
  arXiv  Detail & Related papers  (2025-03-25T22:36:21Z)
• Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground [51.85131234265026]
  I argue that efforts to promote responsible and ethical AI can inadvertently contribute to and seemingly legitimize this disregard for established contextual norms.<n>I question the current narrow prioritization in AI ethics of moral innovation over moral preservation.
  arXiv  Detail & Related papers  (2024-12-06T15:36:13Z)
• Aligning Generalisation Between Humans and Machines [74.120848518198]
  AI technology can support humans in scientific discovery and forming decisions, but may also disrupt democracies and target individuals.<n>The responsible use of AI and its participation in human-AI teams increasingly shows the need for AI alignment.<n>A crucial yet often overlooked aspect of these interactions is the different ways in which humans and machines generalise.
  arXiv  Detail & Related papers  (2024-11-23T18:36:07Z)
• Ethics in the Age of AI: An Analysis of AI Practitioners' Awareness and Challenges [11.656193349991609]
  We conducted a survey aimed at understanding AI practitioners' awareness of AI ethics and their challenges in incorporating ethics. Based on 100 AI practitioners' responses, our findings indicate that majority of AI practitioners had a reasonable familiarity with the concept of AI ethics. Formal education/training was considered somewhat helpful in preparing practitioners to incorporate AI ethics.
  arXiv  Detail & Related papers  (2023-07-14T02:50:46Z)
• FATE in AI: Towards Algorithmic Inclusivity and Accessibility [0.0]
  To prevent algorithmic disparities, fairness, accountability, transparency, and ethics (FATE) in AI are being implemented. This study examines FATE-related desiderata, particularly transparency and ethics, in areas of the global South that are underserved by AI. To promote inclusivity, a community-led strategy is proposed to collect and curate representative data for responsible AI design.
  arXiv  Detail & Related papers  (2023-01-03T15:08:10Z)
• Ethics in AI through the Practitioner's View: A Grounded Theory Literature Review [12.941478155592502]
  In recent years, numerous incidents have raised the profile of ethical issues in AI development and led to public concerns about the proliferation of AI technology in our everyday lives. We conducted a grounded theory literature review (GTLR) of 38 primary empirical studies that included AI practitioners' views on ethics in AI. We present a taxonomy of ethics in AI from practitioners' viewpoints to assist AI practitioners in identifying and understanding the different aspects of AI ethics.
  arXiv  Detail & Related papers  (2022-06-20T00:28:51Z)
• Metaethical Perspectives on 'Benchmarking' AI Ethics [81.65697003067841]
  Benchmarks are seen as the cornerstone for measuring technical progress in Artificial Intelligence (AI) research. An increasingly prominent research area in AI is ethics, which currently has no set of benchmarks nor commonly accepted way for measuring the 'ethicality' of an AI system. We argue that it makes more sense to talk about 'values' rather than 'ethics' when considering the possible actions of present and future AI systems.
  arXiv  Detail & Related papers  (2022-04-11T14:36:39Z)
• Relational Artificial Intelligence [5.5586788751870175]
  Even though AI is traditionally associated with rational decision making, understanding and shaping the societal impact of AI in all its facets requires a relational perspective. A rational approach to AI, where computational algorithms drive decision making independent of human intervention, has shown to result in bias and exclusion. A relational approach, that focus on the relational nature of things, is needed to deal with the ethical, legal, societal, cultural, and environmental implications of AI.
  arXiv  Detail & Related papers  (2022-02-04T15:29:57Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)
• An interdisciplinary conceptual study of Artificial Intelligence (AI) for helping benefit-risk assessment practices: Towards a comprehensive qualification matrix of AI programs and devices (pre-print 2020) [55.41644538483948]
  This paper proposes a comprehensive analysis of existing concepts coming from different disciplines tackling the notion of intelligence. The aim is to identify shared notions or discrepancies to consider for qualifying AI systems.
  arXiv  Detail & Related papers  (2021-05-07T12:01:31Z)
• An Ecosystem Approach to Ethical AI and Data Use: Experimental Reflections [0.0]
  This paper offers a methodology to identify the needs of AI practitioners when it comes to confronting and resolving ethical challenges. We offer a grassroots approach to operational ethics based on dialog and mutualised responsibility.
  arXiv  Detail & Related papers  (2020-12-27T07:41:26Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.