The Language Labyrinth: Constructive Critique on the Terminology Used in the AI Discourse
This conceptual work addresses a foundational issue for AI researchers, policymakers, and ethicists, but it is incremental as it builds on existing critiques of language in the field.
The paper tackles the problem of unclear and metaphorical terminology in AI discourse, arguing that it distorts discussions on responsibility and use-cases, and proposes more fitting terminology to enable better debates.
In the interdisciplinary field of artificial intelligence (AI) the problem of clear terminology is especially momentous. This paper claims, that AI debates are still characterised by a lack of critical distance to metaphors like 'training', 'learning' or 'deciding'. As consequence, reflections regarding responsibility or potential use-cases are greatly distorted. Yet, if relevant decision-makers are convinced that AI can develop an 'understanding' or properly 'interpret' issues, its regular use for sensitive tasks like deciding about social benefits or judging court cases looms. The chapter argues its claim by analysing central notions of the AI debate and tries to contribute by proposing more fitting terminology and hereby enabling more fruitful debates. It is a conceptual work at the intersection of critical computer science and philosophy of language.