Why ‘human in the loop’ falls short – and what to do about it
Agentic artificial intelligence governance depends upon humans to keep agentic AI from going off the rails. However, putting humans in the loop is woefully insufficient. Here are the problems – and perhaps some solutions – to the human-in-the-loop problem.
Since the dawn of automation, humans have always had roles to play: setting them up and troubleshooting them when they fail.
From the Jacquard looms of the 18th century to the robotic process automation or RPA that dominated the automation market leading up to the generative artificial intelligence revolution, humans always had to step in if the machine jammed or otherwise went off the rails.
RPA, however, is yesterday’s news. The automation story across enterprises today centers on agentic AI: orchestrating autonomous AI agents that leverage the power of large language models or LLMs to build and run automations.
