The phrase “human in the loop” always struck me a little odd in the context of AI, but for the longest time I couldn’t quite say why. Now I think I realize what it is: Being “in the loop” is often, if not usually, a pretty passive position. It connotes being told about things that you probably won’t have to take any action on yourself, unless something really alarming crops up. But I don’t think that’s what “human in the loop” is shaping up to be for much of the AI experience in the enterprise.
Instead, it’s more like you’re a “human supervisor,” and supervisors tend to do plenty of work and hands-on oversight, at least if they’re doing their jobs. When it comes to AI, there appear to be precious few “set-it-and-forget-it” scenarios, where you can trust the AI enough to not even check its work, or to do so only cursorily.
There’s an example in this recent article from CIO Dive, which discusses a report from Bain that found AI saves time in writing code, but devours more time in review processes than what’s saved in coding. CIO Dive writes:
“‘The bottleneck has moved from writing code to trusting it,’ Purna Doddapaneni, partner at Bain and one of the authors of the report, told CIO Dive. ‘Every change still has to be understood, reviewed, tested, and secured, and most of that work still runs through people. Output goes up, but the system settles at the speed of its slowest human checkpoint.”
There’s no getting around it: Until you trust AI enough to not only do the work, but do it perfectly and/or vet the work flawlessly, you’re not getting rid of people – which means you’re not saving time. Those with a background in network engineering could have told the AI hypesters that the network is only as fast as its slowest link.
I’d argue that communications technology ranks right up there with coding as one of the areas most susceptible to this reality. Code may be complex, but it’s not nearly as complex as human thought and emotion, which are on display in communications systems and the AI-driven capabilities being deployed in them.
Add to this the prospective role of AI agents in communications processes. We’ve yet to see how well agents will perform when it comes to providing real-time assistance during collaboration sessions or independently helping employees manage their communications and information needs as they work on projects. How good will agents be at providing the right information, valid documents, and appropriate follow-up, and including the right colleagues without spamming everyone who ever weighed in on the subject? It may not yet be time for teams to surrender control and oversight of communications processes.
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