It is often said, that Artificial Intelligence (AI) positively transforms almost every sector from medicine to urban planning, but it also brings questionable or even dangerous implications with it, like fake news and videos, a surveillance state and loss of privacy. Technical issues like a lack of predictability and explainability, as well as hype and misinterpretations in the media, and further, disagreement within definitions and applications, lead to skepticism and distrust. In the context of AI, there is a critical underlying assumption: No trust, No Use. Since AI holds great promises, experts and AI enthusiasts are especially concerned about how to build trust in AI to foster adoption or usage. Trust can be seen as a psychological mechanism to cope with uncertainty and is located somewhere between the known and the unknown (Botsman, 2017). On the individual level, trust is deeply ingrained in our personality. We are basically born with a tendency to trust or distrust people (or animals or any other things).

Machine learning has a lot of potential to accelerate innovation and ease burdens on workers in finance and other industries. Despite a dark side for those same workers, this form of artificial intelligence (AI) -- in which software uses data to program and improve itself -- could also help organizations manage crippling new demands. "There has been a dramatic increase in work in the last five or six years, coming from the exponential data explosion and an increase in audit regulation bureaucracy," Neil Kinson, chief of staff at enterprise process automation provider (and long-time SAP partner) Redwood Software, said in ZDNet last week. "The automation is being created to solve that problem, rather than to cut costs, [and] a lot of organizations are applying automation just to cope." And we may have only spotted the tip of this iceberg.

There has been a dramatic increase in work in the last five or six years, coming from the exponential data explosion and an increase in audit regulation bureaucracy,

There has been a dramatic increase in work in the last five or six years, coming from the exponential data explosion and an increase in audit regulation bureaucracy,