Artificial Stupidity

Yes, we're here already.

You Need the Right Human in the Loop System for Hiring and Recruiting

"Artificial stupidity" in the way we're seeing it play out is an AI term used to describe an "unintentionally flawed AI." It's not a formal technical term, but rather a way to talk about the limitations of increasingly AI-based systems.

Will AI Get Worse?

There are two big reasons AI makes mistakes that a human would not typically make. It's often a result of:

• Flawed Data: The principle of "garbage in, garbage out" applies here. If an AI is trained on incomplete or biased data, it will produce flawed or biased results. 

  
  

• Lack of Context: AI models lack real-world understanding. They are pattern-matching machines. They can make "stupid" errors when asked to apply knowledge to a situation with incomplete or wrong information.

Garbage In, Garbage Out...for Hiring.

In the world of recruiting, the "garbage in, garbage out" principle can be a big problem. One use case is when a hiring team feeds an AI a vague job description or uses a keyword-only approach. They are providing "garbage" data. The AI, in its "stupidity," will then give a flawed list of candidates that don't truly fit the role or miss key attributes. It is especially true with most candidates now using AI-tailored resumes.

You Need a HITL System to Overcome It

This is where a human-in-the-loop system (like HireBoost) becomes essential. It’s a solution that allows the human team to get aligned first. By using a structured playbook for strategic role discovery and a disciplined framework for interviews, HireBoost ensures that the "input" isn't a mess of keywords but a clear, human-vetted set of criteria. The value of this HITL system is that it makes sure the human experts are providing the AI with the correct information so the AI can actually deliver valuable results.

An applicant tracking system (ATS) without a well-thought-out HITL system misses the helpful feedback loop, can't identify blind spots, and lacks the ability to adapt to changing requirements (which we know happens all the time in recruiting!).

Doing the Right Things, Right.

The right level of human involvement depends on the use case of course. Important hiring decisions typically need more oversight, while low-risk, high-volume tasks might function well with minimal human input. It comes down to doing the right things right, not just faster.

Check us out! https://www.hireboost.ai/hireboost-system