With the emergence of today’s gigantic business analytics market, many problems have arisen in the organizational and individual level. Due to the inherited complication in the computational space, the visibility and transparency of work quality and performance may not be clear and accessible to executives majoring in different fields. As a result, the complexity of computational services has been exploited by incompetent and/or fraudulent team members by deceptive computer programs, exaggerated computational performance, data leakage, among others.
In addition to that, AI systems may not satisfy a minimum security of privacy, protection against identity theft and other kinds of systemic biases.
Responsible AI is a concept to achieve fairness, quality, transparency and validity of computational intelligence for the good of organizations and users. The cost of failure in any of above-mentioned biases can be as big as collapsing the entire organization, legal penalties, loss of brand value and customer loyalty, loss of time and capital invested, among others.