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Who is accountable for AI in hiring?
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June 17, 2026
This post originally appeared in Human in the Loop, a biweekly newsletter helping boards, companies, hiring managers, and job seekers navigate work in the age of AI.
A few months ago, a job seeker asked me what has become a fundamental question for what the future of work will look like: "Did AI decide I wasn't good enough before a human ever looked at my application?"
I didn't have a simple answer.
The honest one is: it depends how the recruiter is using AI, and if they fully understand every decision the tool is making on their behalf.
It depends how the AI integration was designed and trained, what data was used and how, and the guardrails and accountability structures in place to prevent bias and accurately identify the candidates best positioned to thrive in the job.
Stepping back, the question forces us to wrestle with the reality that humans aren’t always the antidote to bias. Sometimes, we make assumptions, based on our experience and the limited information we have about the individuals in front of us.
AI can amplify that tendency, or it can help give us the data we need to make better, more transparent, and more informed decisions.
That's why I'm launching Human in the Loop, also available on Substack.
If you work in HR, lead a team, or have ever applied for a job, AI is already a part of your world, whether you realize it or not. It’s screening resumes, ranking candidates, flagging attrition risk, and shaping decisions that affect people’s careers and livelihoods.
A lot of people, understandably, don’t trust it. Over 70% of Americans think AI is moving too quickly, and just 18% of young people ages 14-29 say they feel hopeful about AI.
I get it. That skepticism is earned. AI systems can and do reflect the biases baked into their training data. They can obscure accountability and make consequential decisions with very little explanation.
But here’s what’s also true: AI isn’t going away, and it has enormous potential to make the hiring process fairer, faster, and less frustrating for candidates and employers alike. Getting there, however, depends on the people building and using AI to engage with it critically and responsibly.
I’ll be writing for HR leaders who want to use AI confidently, without compromising their respect for the careers in their hands, for candidates who want to understand how their data is being used, and for anyone trying to figure out what "responsible AI” actually means in practice.
At Findem, we think about AI in concrete terms. What used to take a recruiter 40 hours now takes two, not because we’ve reduced the need for their judgment but because we’ve reduced the noise. That’s the version of AI I believe: not one that replaces the human, but one that gives them the tools they need to make decisions that are effective, equitable, and evidence-based.
A few things you can expect here:
- Practical guidance for using AI in talent decision-making without losing accountability
- Plain-language breakdowns of what AI is actually doing in hiring decisions, and what it isn't
- Honest takes on where the industry is getting it right, and where the marketing is running ahead of reality
- Frameworks and tools you can bring back to your companies to prepare them for AI enablement and governance
I won’t write around these hard questions; I’ll write toward them.
If you’re wrestling with any of this — as a leader, a practitioner, or a job seeker — subscribe and share with one person who should be in this conversation. The more people asking the right questions, the better outcomes for everyone.
The best AI-powered hiring decisions haven't been made yet. That work is ahead of us — and it starts with getting the foundation right. I'm glad you're here for it.
