When enterprises adopt new technology, security is often on the back burner. It can seem more important to get new products or services to customers and internal users as quickly as possible and at the lowest cost. Good security can be slow and expensive.
Artificial intelligence (AI) and machine learning (ML) offer all the same opportunities for vulnerabilities and misconfigurations as earlier technological advances, but they also have unique risks. As enterprises embark on major AI-powered digital transformations, those risks may become greater. “It’s not a good area to rush in,” says Edward Raff, chief scientist at Booz Allen Hamilton.
AI and ML require more data, and more complex data, than other technologies. The algorithms developed by mathematicians and data scientists come out of research projects. “We’re only recently as a scientific community coming to understand that there are security issues with AI,” says Raff.
