Why Artificial Intelligence Won’t Replace Human Leadership

Fear.

That’s one of the most common feelings I see when I talk about the impact of artificial intelligence on human resources and the business world. If you read the headlines, we’ll all be out of a job soon due to the prevalence of algorithms that run our daily lives. But is that really the case? Will the impact be a full automation of how work gets done?

The truth is that there are certain things that AI is great at and some things it simply can’t do.

Moravec’s Paradox and the World of Business

In the 1980s, Hans Moravec and other AI researchers discovered a curious finding that we now know as Moravec’s Paradox. Essentially, AI can very easily learn to do things that are “hard” for humans, such as advanced statistics and analysis. On the other hand, things that are very simple for humans, such as identifying colors or recognizing faces, can be incredibly difficult for computers to do.

In short: computers, algorithms, and AI are great at some things, but humans are better at others. So, how can we find the right balance?

The concept that humans and machines have different strengths played out in research from Harvard. In the study, a breast cancer detection algorithm was able to detect cancer cells 92% of the time. However, the doctors were able to identify cancer cells 96% of the time.

This clearly shows that humans are better, right? But wait—the next finding was perhaps the most telling part of the study. By combining the algorithm with human experience and intuition, the team was able to identify more than 99% of cancer cells. This blending of strengths points to the incredible opportunity that is facing HR.

For many business leaders, the question is often “either/or,” as in “I either need people or I need an algorithm.” The truth is, that’s the wrong question to ask. The right answer is an “and” solution, not an “either/or.”

A Practical Application of AI

To offer an insight into what artificial intelligence can do, let’s look at a rich source of data: surveys. Employees and customers both complete surveys, creating rich data for employers. However, having a human read and interpret that information is time-consuming, potentially biased, and may not lead to the best outcomes. However, AI is ideally suited to consuming large amounts of data and offering recommendations and predictions based on what the data say.

Does this mean the humans are no longer needed? Certainly not! While the system may “know” the problem, it’s up to us as human leaders to step forward, build relationships, and develop creative solutions–things an algorithm isn’t designed to do.

The bottom line is that the fear around AI is often misplaced. The systems existing today have narrow applications, as in our example, and they cannot replace human compassion and critical thinking that makes us who we are. By leveraging the best that algorithms and humans have to offer, we will arrive at the best solutions for a more human-centered workplace.