“Machine learning (ML) has been widely used in not only daily life (eg online platforms) but also in professional fields (eg medical care, astronomy). However, it is noteworthy that most ML confronts a common Black-box Problem, which is deemed as one of the great policy issues with many ML. In Bathaee’s words, the Black-box Problem is defined as ‘an inability to fully understand an AI’s decision-making process and the inability to predict the AI’s decisions or outputs.’ From a computer scientists’ standpoint, the Black-box ‘is an algorithm that takes data and turns it into something’ and often ‘detects patterns without being able to explain their methodology’ …” (more)
Yangzi Li, ‘Does black-box machine learning shift the US fair use doctrine?’, Journal of Intellectual Property Law and Practice, https://doi.org/10.1093/jiplp/jpab118. Published: 6 September 2021.