Articles about "algorithm transparency"

X's recent release of its recommendation algorithm code has drawn criticism from researchers, who describe it as heavily redacted and of limited transparency. Despite claims of openness, experts highlight the absence of key decision-making details and the growing opaqueness resulting from neural network-based ranking. The lack of access to training data and model weightings leaves substantial gaps for those seeking to evaluate or reproduce X’s system.