Like any other data tech, 'garbage in, garbage out' hurts artificial intelligence
Artificial intelligence and machine learning are leapfrog technologies, transforming the way payment processors, banks, online businesses and others are interacting with current and prospective customers.
They far exceed human intelligence and intuition, and can verify the identity of the person on the other end of an online transaction and detect fraud. However, there are limitations, shortcomings and misapplications of data science that can impact results.
To produce reliable and accurate decisions, AI and machine learning depend on three basic elements.
The first is good data. In fact, data engineering is 30% of data science. Without properly vetted inputs, even the most advanced AI systems cannot generate trustworthy outputs. AI is susceptible to garbage in, garbage out.