Principle of Charity in AI Assisted Hiring Practices

ChatGPT Use cases and examples
1

I used ChatGPT to produce this. I hope this is the right place to suggest it.

AI Screening: Guided by the Principle of Charity

  1. AI as an Advocate for the Candidate:
    • The principle of charity in AI would mean that the AI doesn’t seek to find flaws or reasons to disqualify a candidate but instead looks for strengths and opportunities to help the candidate present their best self.
    • Instead of flagging “red flags,” the AI could help the candidate frame their background, experience, and skills in the most positive light. For instance, if there’s an employment gap, the AI could encourage the candidate to explain the gap in a way that highlights the growth they experienced during that time (e.g., self-improvement, volunteer work, or taking care of a family member).
    • Lesson takeaway: AI should be constructively supportive—not critical. It should guide the candidate to highlight their strengths, tell their story more effectively, and frame their qualifications in a way that aligns with the role’s needs.

  2. Redefining “Red Flags”:
    • Instead of flagging or pointing out potential red flags, the AI would focus on giving candidates the opportunity to address any potential concerns. For example, if a candidate is switching industries or has a non-linear career path, the AI should help them explain how their unique experiences can be an asset to the company, emphasizing transferable skills and relevant competencies.
    • Lesson takeaway: What AI should flag are opportunities to give a fuller explanation or to highlight strengths that may not have been immediately clear. It shouldn’t act as a gatekeeper but as a tool to help candidates make their best case.

  3. Avoiding Straw Man Scenarios:
    • The straw man fallacy occurs when someone misrepresents a position to make it easier to attack or dismiss. In hiring, if AI were to flag potential issues without giving the candidate a chance to address them, it would be creating a straw man by assuming a negative interpretation of a candidate’s qualifications.
    • Lesson takeaway: AI should ensure every candidate gets the chance to present a well-rounded case for themselves, even if they have non-traditional qualifications or experiences. Instead of focusing on potential weaknesses, the AI should guide them to show how their unique background or experiences can contribute to the role.

  4. Building Candidate Confidence:
    • By shifting AI’s role to be an advocate rather than a gatekeeper, the candidate’s experience in the hiring process is improved. They’ll feel that they’ve been treated fairly and given a chance to showcase their full potential, even if they don’t perfectly match every requirement.
    • Lesson takeaway: This would encourage more diverse applicants to apply, knowing that the AI will help them present their case, rather than dismissing them based on superficial criteria.

  5. Human Final Review with AI Assistance:
    • Ultimately, a human manager should still be the final decision-maker, but with AI providing additional context that helps the hiring manager better understand the candidate’s strengths, experiences, and how they could contribute to the team. This ensures a more holistic review that considers not just skills but also narrative and context.
    • Lesson takeaway: The AI’s role is to help elevate the candidate’s presentation, ensuring that all relevant information is properly conveyed before a final decision is made. The manager should still have the final say, but with the added assistance of AI to level the playing field.

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Summary: AI as a Candidate Advocate

By ensuring AI aligns with the principle of charity, hiring processes would avoid bias, encourage transparency, and provide equal opportunities for all candidates to make their case. This approach not only enhances the candidate experience but also ensures more diverse and holistic evaluations, giving every candidate the best possible chance to showcase their abilities and fit for the role.

2

That would work in a world where applicants are truly interested in working and not only in finding someone who pays for their life.
I had employees who only needed a job to apply for a visum or to stack multiple income streams (by working for multiple employers). They didn’t even want to work nor did they plan to get the required qualification. What they had planned though was getting the money we agreed on in the contracts.

I would suggest to add a kind of lottery for candidates who are red flagged in case the companies policy allows/wants to do some charity.

But giving your customers in HR systems wrong information feels not only wrong but also criminal.

3

So, the idea here is to assist the HR system in understanding the candidate better—not to provide false or misleading information. This would ultimately be beneficial for the company because it helps avoid missing out on potentially great candidates who may not have communicated their strengths effectively in an application process.

If wrong information is provided, that would be a legitimate concern, but using AI to enhance candidate profiles and help them provide more accurate and complete context doesn’t fall into this category. It would be about helping both the employer and applicant understand each other better, ensuring that information is not hidden or misrepresented, but rather fully explored for an objective evaluation.

4

You raise a great point, though.

Ultimately, it comes down to how the system is used. If AI is only helping candidates present true and verified information in a clearer way, then it shouldn’t inherently magnify fraud. But, if AI is used to suggest misleading or deceptive information, that’s a much bigger ethical issue.

So I understand your concern, there’s a balance to be struck here between helping candidates communicate honestly and ensuring that AI doesn’t enable deception. Maybe this is an area that could use further clarification, especially around ethics and transparency when implementing AI in hiring processes.

5

I could imagine some techniques that could find out about the true motivation of candidates which would benefit the ones who really want to work and prevent such fraud. But it would be illegal in most countries.

Something that would really help would be a broader rotation of HR people. for example if they want to hire tech people they should be required to work in tech for at least 3 years.

Keyword picking in CVs is not the right qualification.

6

I love the idea of HR reps getting trained in tech to help them make better decisions. And I completely agree that keyword picking is the wrong approach.

I appreciate your insight. These are really good points about ethics and integrity as well as some really practical solutions for better hiring practices.