Using artificial intelligence in your hiring process

Using artificial intelligence in your hiring process

Artificial Intelligence is playing a bigger role in today’s hiring process. Learn how to utilise it.

Artificial Intelligence is being increasingly harnessed for interviews. (rawpixel.com pic)

Artificial Intelligence (AI) is playing a bigger role in today’s hiring process. The success of a company depends on making good hiring decisions. AI is currently still riddled with biases and overfit models, and is only as good as the humans who program it.

That doesn’t mean you scrap AI systems or label all uses of it as unethical. Instead, you need to understand the adjunctive role it can play in your hiring processes.

Firstly it’s important to have a clear picture of how to hire. There are seven major steps to the hiring process:

1. Understand your company: its value proposition, culture, indicators of fit. These should include a diversity and inclusion strategy.

2. Understand the position: conduct a detailed job analysis

3. Determine whether the candidates have the right skills

4. Review the resume like a portfolio of experiences and ignore any identifying information like alma mater, name and gender

5. Review cover letters from any remaining candidates

6. Conduct in-person interviews

7. Make and communicate hiring decisions

AI shouldn’t be used for any of these steps except for three and four, where it excels.

Parsing resumes with AI

Employing AI to parse resumes must be done carefully. The temptation is to seek out a set of keywords that fit the job in combination with years of experience, and simply eliminate anyone that doesn’t have the right stuff.

As convenient as that may be, you’re likely to miss a great candidate. Instead, use your creativity and discretion to plan in advance what you want to see on the resumes.

Think about years of experience and keywords, but also think about other knowledge, skills, and experiences that will contribute to your company.

Put that framework into the AI system, and use it to seek out those attributes on resumes. Then, select candidates that are high, medium, and low fits on that basis.

Then give the AI feedback about how well it did. You do this by scoring the same resumes without seeing how the AI did it, and then correcting the AI’s results accordingly.

After three rounds, your AI will have a pretty good idea of what you want, so you can now use it to help you pick candidates. Have the AI order the list of resumes and highlight key terms.

This way, you know which ones to review first. Every time you review a candidate, give feedback to the AI system about how well it did.

Conducting skill tests with AI

The most important part of candidate assessment is ascertaining if the applicant can do the actual tasks required on the job. Before you look at resumes, ensure that its someone who walks the talk.

Design a test that anyone capable of doing the job can pass, but those without the requisite skills will fail. Team up your hiring manager with an HR expert and/or an organizational psychologist.

As you design the test, consider the range of possible answers. Give the AI system your range of answers, then show it examples of responses that are high, medium, and low quality.

You then need to run the AI in parallel with manual grading for a while, comparing how well it fits the expectations of human graders and providing feedback to train the system. At this point, the AI will be ready to suggest which candidates are most likely to give good answers.

You can spend more time reviewing the answers of qualified applicants. It is crucial to keep giving feedback to the AI system. This ensures continuous updating of the AI’s algorithms and that the AI is adjunctive rather than serving as the decision-maker.

Addressing concerns about demographic bias

Where AI can actually protect you from yourself is the fact that it has additional algorithms that look for biases and alerts you when the results look a bit too homogeneous.

The system can continually scan for questions where scores tend to vary by demographic, and likewise for patterns of responses that are more prevalent in certain demographics.

Because these algorithms are separate from the analyses of resumes and skill test responses, they are designed to keep you honest.

This article first appeared in vervoe.com.

At Vervoe, our mission is to fundamentally transform the hiring process from mediocracy to meritocracy.

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