AI Implementation Lessons from IBM
Artificial intelligence (AI) continues to improve, which sounds like good news on the surface as it opens up a world of new possibilities for businesses. However, privacy and ethical issues are posing problems for some firms when it comes to deploying AI.
IBM CEO Ginni Rometty recently highlighted what IBM has learned when it comes to AI implementation at the World Economic Forum. Here is a look at a few of the most valuable lessons she shared.
Keep Your Business Model in Mind
All companies have a business model, and this should always be in the front of decision makers’ minds. The people who create the AI tech for a business need to make sure it reflects the people who will actually be using it. For example, MIT Media Lab Director Joichi Ito recounted how a black researcher working in his lab noticed that some of the facial recognition technology they were using was not able to pick up faces that had darker skin tones. He said that a lack of diversity among engineers means that not all of the relevant questions are being asked.
Don’t Think of it as Workers Versus Computers
It is not surprising that people worry about technology taking over their jobs. After all, machines have proven themselves to be far more efficient and much less prone to errors than humans at many tasks. Indeed, some professions could end up being entirely replaced by automation, but most people do not need to fear this technology. Instead, it will help to supplement the tasks that humans are already carrying out. Instead of being viewed as competition for their jobs, workers need to think of AI as something that will help them improve the way they work.