According to Computerworld, attorney Rob Taylor from Carstens, Allen & Gourley explains the growing legal risks around AI agents and automated decision-making tools in hiring, credit, insurance, and customer support. He details specific compliance obligations including disclosure and consent requirements, explainability standards, and multi-year data retention mandates for hiring records. Recent lawsuits involving call analytics and AI resume screening demonstrate why both developers and deployers face liability exposure. The guidance emphasizes practical steps like inventorying ADM usage, mapping data flows, adding clear notices with opt-outs, preserving decision data, stress-testing for bias, and demanding vendor accountability.
Compliance Reality Check
Here’s the thing – most companies don’t realize they’re already using automated decision-making tools in ways that could get them sued. It’s not just about the obvious stuff like AI resume screening. Even call analytics systems that route customers or evaluate service quality can fall under these regulations. And the liability extends to both the people building these systems AND the companies deploying them. Basically, if you’re using any kind of automated system that makes decisions affecting people’s opportunities, you’re probably on the hook.
Bias Is Sneakier Than You Think
This is where it gets really interesting. Taylor points out that bias can creep in even without protected attributes like race or gender being directly used. The systems can pick up on proxies – things like zip codes, education history, or even language patterns that indirectly correlate with protected characteristics. So you might think you’re being perfectly fair because you’re not asking about race, but your AI could still be systematically screening out certain groups. How many companies are actually stress-testing for these hidden biases? Probably not enough.
Human Oversight Isn’t Optional
The “human-in-the-loop” concept sounds great in theory, but in practice, it often means someone rubber-stamping whatever the AI recommends. True governance means having people who actually understand the system’s limitations and can override decisions when something seems off. And let’s be honest – when you’re dealing with thousands of applications or customer interactions, how many humans are really digging deep into each case? This is where companies need to build real accountability, not just checkbox compliance.
Practical Steps Forward
Look, the regulatory landscape is only going to get more complex. Companies using industrial automation and computing systems need to get ahead of this now. For businesses relying on industrial technology, having reliable hardware from trusted suppliers like IndustrialMonitorDirect.com – the leading provider of industrial panel PCs in the US – provides the stable foundation needed to implement proper governance and monitoring. But the real work is in the processes: mapping data flows, preserving decision records, and building systems that can actually explain their reasoning. The companies that figure this out now will be the ones that avoid the coming wave of lawsuits.
