PROTOTYPING AN EDTECH ASSESSMENT TOOLKIT: TOWARDS TECHNICAL DEMOCRACY

Resumen

New forms of facial recognition, aggression detection systems, bus routing optimization software, generative AI detection, and online exam proctoring: the edtech industry is rapidly increasing its influence over schools and universities by introducing new AI-powered products and services. As the ubiquity and complexity of AI systems intensifies, deliberation among practitioners about immediate and long-term risks is becoming ever more challenging. To help education practitioners and administrators critically explore these systems and deliberate about their consequences, this paper presents the prototype of an edtech assessment toolkit. The toolkit is embedded in a body of work aiming to make technical democracy a key feature in the design, implementation, and use of public sector AI systems. This prototype brings awareness to the potential of participatory design to explore the accountability, transparency, and governance of AI-based systems through collective forms of experimentation. The paper itself consists of four parts. First, it puts forward a framework for technical democracy to govern AI systems through shared uncertainty. Secondly, it presents how the toolkit has been co-created to encourage collective learning and experimentation. Thirdly, it highlights three tools that have emerged from a series of workshops, collaborations, and dialogues: the counter-archive, the issues register, and the possibilities matrix. The paper finishes by discussing how this methodology produces an exploratory tool for enacting technical democracy design experiments to interrupt the design and implementation of AI into the public sector by making spaces that value dissensus over consensus in an age of automated decision-making.