Hard to find, harder to understand: examining transparency in educational generative AI

Abstract Along with general-purpose generative AI (GenAI) tools like ChatGPT, educational GenAI tools are being increasingly launched to support teachers in enhancing their instructional practices and productivity. To establish a relationship of trust with teachers, tools need to be transparent and provide clear disclosures regarding their underlying mechanisms, training data and processes, origin of information, privacy policies, and limitations. This document analysis examined the transparency of 20 GenAI tools for teachers by analyzing publicly available information on the tools' websites. Findings indicate a significant lack of transparency across these tools. Most failed to provide explicit details about their AI mechanisms, and none disclosed their training procedures or data sources. While several tools assured users that their data would not be used for further training, discussions on limitations and potential risks were largely absent. In addition, necessary information was often difficult to locate and understand. These findings underscore the need for increased transparency in GenAI tools, so that teachers can critically assess the tools’ functionalities, responses, reliability, and suitability for educational use. The study recommends that developers of educational GenAI provide clearer, more accessible disclosures regarding their tools to build a relationship of trust with educators. Educators should actively seek important information before integrating GenAI tools into their teaching. Greater transparency will facilitate informed decision-making of educators, ultimately enhancing the responsible and effective use of GenAI in education.