10 Rules for Collaborative Artificial Intelligence Artificial Intelligence

While the exact number that analysts and AI experts assign to it may vary, the "rule of thumb" statistic is that only 1 out of every 10 Artificial Intelligence initiatives ever makes it into production. Having worked in this field for years, alongside countless clients trying to make AI a reality, it's not a statistic that is difficult to accept. The specific reasons for this difficulty are vast and nuanced, but, in my opinion, can be captured in three big buckets: translating the academic nature of data science to business, having the right data, and collaborating (or lack of collaboration) on building a solution that provides value. Expanding on all of the above is another piece altogether. Instead, I'd like to share some insight into what's possible, specifically related to the third bucket above: building collaborative AI, as a collaborative framework, really is the key to mitigating the risks of bias, distrust, and concept drift in AI deployments.