The great black box challenge: there is no silver bullet, but there is progress in explainability
One of the most important challenges for the generation of computer scientists working with artificial intelligence models is deciphering the well-known “black box”: computational systems whose internal workings are not visible, and therefore, not auditable. To address this problem, Marcelo Arenas, academic at IMC and DCC UC and researcher at IMFD presented a proposal in…
