Description
Book Synopsis.- Bias Mitigation and Ethics in AI Systems.
.- Research Ethics for Data Collection from Human Participants – Case Study and Recommendations.
.- A Synthesis of Reflections, Attitudes and Suggestions Towards Mindful Implementation of LLMs in Digital First Pathways.
.- Mechanistic Exploration of the Architectural Impact of DPO Fine-Tuning on Ethical Alignment in LLMs.
.- Prompting Fairness: How End Users Can Mitigate Bias in AI Systems.
.- Bias in AI Recommender Systems: Examining Gender Disparities in STEM and Non-STEM Career Recommendations for Professional Development.
.- Mapping Moral Reasoning Circuits: A Mechanistic Analysis of Ethical Decision-Making in Large Language Model.
.- Evaluating Fairness and Bias in Large Language Models for Tabular Data.
.- Human-AI Collaboration and Teaming.
.- Exploring the Application of AI to Qualitative Data Analysis: A Comparative Study in the Field of Industrial Design Education.
.- The Core Building Blocks of Human-AI Teaming: Conceptualization and Typology Development.
.- AI as a Sparring Partner – an HCAI Approach to Promote Human Capabilities.
