Embracing AI is wonderful. From a practical business perspective, though, there are limits. This issue is broader than AI. However, I’ll constrain the conversation to that for now, given the attention AI is getting these days. Yes, some processes are undoubtedly good candidates for automation, but avoiding “technocentrism” is critical to
AI has captured the general public's imagination, so it was no surprise that it was nearly the only topic of conversation among data professionals at this year’s Chief Data and Analytics Officer (CDAO) conference in London. Of course, AI and machine learning are not new concepts for those working in
AI – just like humans – can carry biases. Unchecked bias can perpetuate power imbalances and marginalize vulnerable communities. Recognizing the potential for bias is one of the first steps toward responsible innovation. Doing so allows users to include diverse needs and perspectives in building inclusive and robust products. Through
