Artificial intelligence can make your organization more efficient, if employees know what it is capable of doing, and what it should never do.
A fast-growing area of artificial intelligence is machine learning, in which a computer program improves its answers to a question by creating and iterating algorithms based on data. It is often regarded as the kind of technology that only the most clever and most mathematically-minded people can understand and work with. But it is a technological tool like any other: It can be understood on various levels, and can still be used by those whose understanding is incomplete.
There are three important questions that any member of your team should be able to answer:
HOW DOES IT WORK? Team members who aren’t responsible for building an AI system should nonetheless know how it processes information and answers questions. It’s particularly important for people to understand the differences between how they learn and how a machine “learns.”
WHAT IS IT GOOD AT? Learning what machine learning is good at quickly helps someone to see what machine learning is not good at. Problems that are novel, or which lack meaningful data to explain them, remain squarely in the realm of human specialties. Help your employees to understand this difference.
WHAT SHOULD IT NEVER DO? Just because machine learning can solve a problem does not mean it should do so. There may be some problems that your organization should never ask an AI application to solve.
The organizations that will do best in the age of artificial intelligence will be good at finding opportunities for AI to help employees do their day-to-day jobs better, and will be able to implement those ideas quickly.
(Emma Martinho-Truswell is the co-founder and chief operating officer of Oxford Insights.)
