We need more rule breakers in an AI world

My conversation with Bill Boorman, advisor to talent technology companies, keynote speaker, host, researcher and commentator

With his colorful appearance, passion for street art and big heart for those struggling in society, Bill Boorman is certainly not your typical HR expert. He enjoyed an exciting and serendipitous portfolio career, leading him from a classical recruitment business and later a training business to social media recruiting, back in the time were nobody understood the real value of these networks. Which is probably why I’m such a fan of his ideas, because he has always been able to see what others don’t.

This is a pivotal time for those in HR. Just like those in marketing have been able to make the transition from a gut-driven business to one that is informed by data, HR will have to follow suit. As the world of work will undergo tremendous changes in the coming years, it is up to HR to help navigate companies and employees through these challenges and opportunities.

It could go either way, really: the people role inside companies could become weaker, or it could grow stronger. And unfortunately, I see a lot of HR professionals staring into the headlights of the oncoming car and they have no idea how to deal with that. That’s why I was so excited to be able to talk to Bill, because he’s experiencing all these changes from the inside.

Shrinking networks

An interesting evolution that Bill pointed out concerned the nature of our networks. In the beginning of the world wide web, networks used to be not just small (because no one was on them) but also quite restricted. You couldn’t just connect with anyone on LinkedIn back in the day. But then Twitter surfaced and the size of our networks expanded exponentially.

Today, we’re experiencing a change again and that has to do with trust. In this age of disinformation and misinformation, people tend to experience difficulties filtering out the truth. Rather than thinking “what is the message”, they tend to wonder “what is the agenda here”. That’s hard, and tiring. And so we see the networks shrinking again, according to Bill, containing only the people we trust, because they have the same values, beliefs or interests. Like smaller WhatsApp groups, for instance.

An algorithm of trust

Bill referred to the need for an algorithm of trust. For instance, I myself am slowly reaching the top limit of 30K connections (which is not the same as followers) on LinkedIn and the first thing I’ll probably do when that happens is delete about 5000 contacts. But there’s no real filter for that. I’ll have to do that manually. But Bill’s trust algorithm could dictate my networks to only accept and keep “people who talk about these things” or “do those things”. Whatever the case, I do agree that we definitely need a new way of managing these huge networks that most of us have built around ourselves, in ways that will help us fight the current crisis of trust.

Talking about such an algorithm, AI and automatization, Bill also pointed out the importance of wildcards and rule breakers. Machines are great at following rules but we also need to keep some room for outliers and exceptions. And that’s where humans, for now, are still better at. “Machines are making assumptions based on our past performance, past behaviors and past outcomes, but things are changing so fast that we sometimes need new approaches, which the machines cannot (yet) see in the data.”, explained Bill.

The rule breakers

He gave the example of an exceptional hire he once helped make. He had received 10 CVS, 8 of which showed great potential, 1 which he discarded and one that was a bit of an outlier. But he still decided to pull the wildcard and give the outlier a chance. Not only did he get hired, he turned out to be a great fit. What’s interesting here, is that a machine would probably not have selected him. It would have stuck to the safe choices. And that’s where the human premium will lie in the coming years: in breaking the rules of the machines.

But you cannot break the rules if you do not understand the game. Technology, and especially AI has great potential for automating certain – often more repetitive and boring – parts of jobs. “But people still need to understand the methodology behind those decisions”, explained Bill. For instance, he has always been able to understand the stories behind the data because he has known a time - pre-Excel even - when we used calculators to figure out certain tendencies in recruiting and training.

“The more we automate processes, the less people seem to grasp the underlying principles and methodologies about how you do things. And if there are anomalies in the statistics, then people tend to think “well, let’s move on.” Whereas people like Bill, who really understand the data, tend to perform diagnostics: “Well, there are 10 reasons why this could have happened. Let’s look at the evidence and dig a little deeper. Let’s not just follow what the machine says but second-guess the anomaly and perhaps break the rules. Sometimes you need a human to override the AI because we all know that AI is not perfect.”

The same mechanics lie beneath our desire to talk to a human when things go wrong in our banking app, or when our online order never arrived. When automation goes wrong, or even when humans made a mistake, technology - like a chatbot - is not going to second guess the brand it’s ‘working” for. But humans can, a human customer service member can perform diagnostics. They can think “Ok, the rules said that this should have happened. Now let’s find out why it did not work this time.”

Redefining roles

It was also interesting to learn from Bill how the world of HR is evolving and how roles are being redefined. “Talent Acquisition (TA) roles tend to be cut down to about 40%. There were layoffs after the Covid boom and then GenAI entered the market. And we experienced situations that tech companies realized they did no longer need 10.000 programmers. And therefore, neither did they need as many people to hire these programmers and other roles. So these TA teams shrunk to a significantly smaller size.”

“But now I’m seeing a lot of these TA profiles hired again, but in roles - often called something like People Manager - that are a lot more strategic and that have a seat at the board, too. So the good news is that companies are getting a lot more strategic about their talent.”

“And a second evolution I see is the decline of generalist roles in HR", said Bill. "You have the strategic roles on the one hand, and then you have the specialists in new areas, like people analytics, on the other. Or very specialized recruitment marketing functions. And you see this happening everywhere, not just in HR: roles everywhere, in every department, are being redefined. That scares a lot of people, but it really shouldn’t. This is a very exciting time. I tell people “Be glad that aspect of your job is being automated. It’s repetitive, it’s boring. You don’t want to do that.”

And that’s exactly my feeling. That's why I called myself a pathological optimist in one of my earlier pieces. There is so much doom and gloom already. I get it, change is hard. It’s scary. But just think about all the potential that our era holds. I agree with Bill: “This is a very exciting time.”

If you're interested in how AI and other seismic shocks are changing your business, check out my keynote page.

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