Implementing ChatGPT In Recruiting: Key Considerations And Best Practices

The benefits of AI for recruiters and job seekers

One of the benefits of artificial intelligence (AI) is that it can be used in conjunction with humans to automate mundane tasks so that humans can focus on the things we are uniquely good at. It is still early, however, I expect to see interesting results for those, including candidates and recruiters, who use ChatGPT. 

For recruiters, first drafts of offer letters and job descriptions come to mind as areas where ChatGPT could save time. And candidates could use generative AI to help them improve cover letters and resumes. I am particularly interested in how ChatGPT could be used to help job seekers transition industries by helping them better understand how their skills are applicable across different roles. 

Most of us have interacted with AI in some way, whether it is returning clothes to an online retailer, making a dinner reservation, or asking about the status of a job application. Interactions of this kind are the typical, benign chatbot use cases, however, ChatGPT and other generative AI tools are raising well-deserved concerns.

The primary concern I see is the proliferation of disinformation. Frankly, innovation has outpaced safeguards, and it is critical that researchers and technologists ask critical questions and try to build safeguards. 

Key Considerations and Best Practices

Any powerful tool requires constant and rigorous oversight and generative AI is no exception. Vendors must not integrate ChatGPT into existing tools until they have conducted rigorous testing to substantiate its benefits.

New AI regulations are being proposed and passed regularly, such as the new European Union’s (EU) AI Act, New York City’s (NYC) Local Law 144, etc. Generative AI should be held to the same, if not greater, standards as other AI technologies. 

First and foremost, vendors should be able to explain how their AI systems were trained and how they should be used by people with any level of technical expertise.Vendors must demonstrate that such models work and audit them for bias. I believe creators of these tools should prioritize creating an ‘AI Explainability Statement,’ which is a valuable third party process that documents to the public, customers, and users how a given technology is developed and tested.

Rigorous testing is the bedrock of any product strategy, and every powerful tool should undergo testing before it is deployed, as well as after. The details of that testing will vary by product.

Author Bio

Dr. Lindsey Zuloaga is the Chief Data Scientist at HireVue.