Building Trust in AI Education: Addressing Transparency and Ensuring Trustworthiness

The controversial nature of Artificial Intelligence (AI) has ignited debates and conversations across domains. In educational settings, despite its potential to transform educational institutions and teaching structures and usher in a new era of learning, AI has further complicated issues of trustworthiness and transparency. This chapter maps and brings together scholarship on AI pedagogical applications with work that problematizes AI based on trust- and transparency-related considerations and initiatives. Arguing that these terms serve as an entry point to the world of policy, I highlight concerns and limitations of AI, including data privacy, the need for monitoring and governance, and algorithmic transparency and bias. Additionally, the work adds to a growing body of literature that calls for robust frameworks. As such, it aims to evaluate the social impact of human-machine interaction and gain a comprehensive understanding of the decision-making processes that govern them.