The article further argues that the concept of 'human intelligence' is often used to justify the exploitation of certain types of labor, particularly those involving care work and emotional labor. It suggests that the AI industry's definition of 'intelligence' is often biased towards certain types of work and individuals, particularly those in STEM fields. The author concludes by suggesting that the education system needs to critically engage with these issues, rather than simply accepting the definitions and values imposed by the AI industry.
Key takeaways:
- The original definition of AI was ‘the science and engineering of making intelligent machines’, with the assumption that computational ‘intelligence’ simply reflects what ‘intelligent people’ can do. However, this definition has been criticized for its lack of diversity and inclusivity.
- The term ‘human intelligence’ is being used in the context of AI, suggesting that it is a real and self-evident thing, and that it is what education is about. This term is seen as a way to alleviate anxieties about the restructuring and precaritisation of work.
- AI is seen as a tool to 'liberate' us from certain types of work, but this often results in work being routinised, cheapened, denigrated, frequently offshored, and always disappeared from view. This is particularly true for work that is highly rewarded because it is ‘uniquely human’ and is most likely to be done by white, western, well educated men, preferably in STEM disciplines.
- The concept of 'human intelligence' in the context of AI creates a double bind for students and intellectual workers, who are expected to submit themselves to the pace, productivity, and datafied routines of algorithmic systems, while also being expected to 'be more human'.