Creative conversations among designers and stakeholders in a design project enable new ideas to naturally originate and evolve. Language allows for the exchange of values, priorities, and past experience, whilst keeping solution forms usefully ambiguous. Yet there is a danger that only the language of people directly involved in the design process gets to be heard, limiting how inclusively the problems are interpreted, which in turn can impede how complex design problems are addressed.
Recent advances in artificial intelligence (AI) have revealed the exclusionary spaces often inhabited by designers, engineers, and developers of new artefacts and technologies. On the other hand, text data used to train language models for machine-learning applications have the potential to highlight societal biases in ways that designers can utilise.