How Businesses Can Leverage Large Language Models For HR Purposes

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The age of artificial intelligence is here, and the end is nigh! Well, not quite, though that’s what some believe with the explosive popularity of large language models (LLMs) like ChatGPT, Bing Chat and Bard; paid services like Jasper or WriteSonic and AI art generators like DALL-E 2 and Artbreeder. While the day may come that these kinds of programs are a threat to your average business (and that’s certainly a discussion legislators should be having), at the moment, these programs can be a boon for both employers and employees if used properly. This is especially true for small and mid-sized businesses that likely lack their own internal human resources and legal departments, provided you are aware of the technology’s limitations.

How can large language models be used in a business setting?

LMMs certainly won’t have all the answers—and, as their own disclaimers point out, you shouldn’t put stock in any answer it gives you, no matter how confident it sounds—but it knows enough to get employers started on the right track. According to ChatGPT itself, there are several ways businesses can utilize these tools.

• Compliance. AI can help guide businesses in following the laws and regulations related to human resources and employment (currently up to September 2021). It can help businesses understand the requirements for employee classification, recordkeeping and anti-discrimination laws.

• Policy development. AI can help businesses develop employee handbooks, job descriptions and policies related to employee leave and benefits.

• Risk management. AI can review existing materials and help businesses identify and mitigate potential HR risks, such as discrimination or harassment claims.

• Recruitment. AI can help businesses write job descriptions and identify the required skills and qualifications for job positions. It may even be able to write different descriptions for the same position, depending on the platform.

• Training and development. AI can help businesses develop training modules on topics such as diversity and inclusion, sexual harassment and other HR-related topics.

It’s worth noting that the above statements from ChatGPT are paraphrased, having been read, fact-checked and edited as needed by my skeptical human brain.

What are some of the limitations?

Ironically, both the biggest proponents and the opponents of AI LLM systems seem to make the same mistake by giving “the robots” far too much credit. A Manhattan attorney recently learned this the hard way. Instead of doing the critical work of digging out legal precedents himself to support a client’s lawsuit, he used ChatGPT to prepare his case. What he got in return for taking the mental shortcut was a filing full of bogus judicial decisions, with bogus quotes and bogus internal citations. Hilarious, right? Not so—this can be a career-altering event and shows how humans still need to oversee AI operations.

Not only do these AI programs not know the limits of their own knowledge, they won’t know they don’t know it and may fabricate with utmost confidence. Several weeks before the Manhattan lawyer’s problem came to light, I decided to test ChatGPT myself. I asked for a summary of a decision from the 9th Circuit Court of Appeals and initially marveled at the answer it provided. It seemed to perfectly reduce the case down to its most relevant bits with a cohesive narrative. But none of it was true.

The issues it told me were case-critical weren’t even a factor, and the parties didn’t even exist. And this highlights one of the current weaknesses of AI models, which for some reason, could not locate a published decision, review it, analyze it or check it for accuracy.

The lesson here is you can use AI as a guide to help structure your writing, identify gaps or omissions and save you time, but it’s not gospel. Make sure you don’t just run with whatever the AI model produces or abdicate your responsibilities for your business, employees and customers to an insentient LLM.

How can you use the tools effectively?

The key to using LMMs effectively is asking the right questions. I recommend asking it a broader question, then narrowing it down. Then, ask for its resources and always do your own vetting.

For instance, a query of “What are the key elements I should have in my HR handbook for my company based in California?” generated a reasonable outline of 15 points to address in an HR handbook. A second question, “What are some of the key legal requirements to include in an employee handbook for my company based in California?” generated 13 points, including some key reminders not included in the first response, such as meal and rest breaks, anti-retaliation and policies on drug and alcohol use.

Once you have the outline, drill down. You need to know where the robot is getting its information. In this case, asking it to provide the original sources for each item in the outline produced nothing but the standard explainer of how it aggregates information. But asking in a slightly different way—“Please provide the key resources for the points above”—resulted in 16 links to public documents posted on California employment regulator’s websites, including the labor code, family rights act and the fair employment and housing act. You still need to review the information from each provided link and do some more work to ensure the laws haven’t changed—remember, ChatGPT isn’t current beyond September 2021.

Again, these tools are not a full replacement for legal counsel. They’re great at getting you to ask the right questions and pointing you in the right direction. They can help you save upfront on legal and HR costs by helping you lay the foundation ahead of a consultation with outside experts.

The information provided here is not legal advice and does not purport to be a substitute for advice of counsel on any specific matter. For legal advice, you should consult with an attorney concerning your specific situation.

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