"A" question of semantics

The words we choose matter. They shape our perceptions, influence our decisions, and ultimately, determine how we understand the world. This is especially true when it comes to new and complex ideas like artificial intelligence. The term itself is a bit of a problem.

The word "artificial" comes from the Latin artificialis (made by art or skill), but over time it's come to mean something "fake" or "not the real thing". When we call something "artificial intelligence," we are essentially telling people it's a poor imitation, creating a perception gap and triggering skepticism. This linguistic legacy positions AI as a replacement for human intellect, not as a tool that works with us. This framing can increase resistance to adoption and make public acceptance more difficult.

But modern systems often show emergent behaviors not directly programmed, performing tasks in fundamentally different ways than humans would. This isn't a new thought. As early as the 1990s, IBM used the term "Augmented Intelligence" to describe its vision for human-computer collaboration. This approach sees the machine handling complex data while the human handles critical thinking and creativity. It's a much more accurate and helpful way of looking at it.

For government communicators and business leaders, the choice of terminology is a strategic decision that shapes public trust and policy discussion. With a new Minister of AI and Digital Innovation in Canada, the focus is on economic benefits and digital transformation, a collaborative approach that Augmented Intelligence aligns with perfectly.

A small change in language can have a huge impact on public acceptance. By using better words, we can reframe the conversation and build a narrative around collaboration rather than replacement. It’s a simple change, but it's essential for getting our message right.