Transparency and Accountability in Combating Gender Bias

One of the critical shortcomings in the fight against gender bias in machine learning models is the lack of transparency and accountability. Many models are treated as proprietary, making it challenging to assess them for bias. Openness in sharing methodologies and results, along with public accountability mechanisms, could significantly advance efforts to eliminate bias. Without these, it's difficult to gauge whether we are doing enough.