Better Hiring: From Instinct to Data

A Conversation with Shiran Danoch, CEO & Founder of Informed Decisions

Bias in hiring is as old as the job interview itself. Whether it’s the “halo effect” favoring candidates from prestigious backgrounds or unconscious bias filtering out top talent, traditional hiring processes have long relied on subjective judgment rather than objective skills assessment.

As an organizational psychologist and CEO of Informed Decisions , Shiran Danoch, PhD is building An AI-powered Interview Intelligence Platform to help organizations make data-driven hiring decisions that are fairer, faster, and more predictive of success.

In this episode of “Weekly innovations from Israel”, we explore the challenges of traditional hiring, the dangers of bias, and how AI is reshaping the future of work.

Aron: Shiran, your journey into hiring innovation began with a firsthand experience of bias in the hiring process. Can you share that story and how it shaped your vision for Informed Decisions?

Shiran: Sure, early in my career, I was the manager of measurement and evaluation at an NGO. I interviewed candidates for a research assistant position and presented my finalist to the CEO. Five minutes into meeting her, he asked her to step out of his office, called me in, and said, "Why did you bring her here? She's not one of ours." I had no clue what he was referring to, but suddenly, I looked around and realized that everyone I worked with was a Mizrahi Jew, while the candidate was of Ashkenazi origin. I was shocked and resigned a few days later.

This experience hit me hard. I decided that I wanted my work to focus on fighting workplace bias and making work better for everyone. That’s exactly what we do at Informed Decisions - helping organizations make more accurate, fair, and efficient hiring decisions with data.

Aron: Speaking of fairness, many hiring managers fall into the trap of overvaluing prestigious backgrounds. Why do impressive education and past employers often overshadow skills, and how can we fix that?

Shiran: Because it’s easy, and as humans, we rely on mental shortcuts (called heuristics) to relieve cognitive overload. It’s much easier to trust credentials like attending Harvard or working at Google. This essentially means you’re relying more on someone else's judgment than your own.

At Informed Decisions, we tackle this by shifting from simply raising awareness (like bias training) to driving real behavioral change. We provide interviewers with actionable feedback on their biases and equip them with the infrastructure, knowledge, and tools to assess job-relevant skills and gain an in-depth understanding of candidates.

Aron: So, you argue that hiring should be data-driven, not instinct-driven, and given our biases, I totally agree. What role does AI play in ensuring companies hire based on skills rather than subjective impressions?

Shiran: There are multiple ways AI can assist in reducing bias in the hiring process:

1. Providing AI-generated, skills-based questions – with a strong disclaimer: if your AI model is trained on public data, you’ll likely end up with low-quality, worn-out, and predictable questions. At Informed Decisions, our psychometricians collaborate closely with data scientists to ensure that the interview questions generated are insightful, valid, and predictive of candidate success.
2. Aggregating data from thousands of interviews (scores, transcripts, notes) to offer hiring teams actionable insights, such as: which skills actually predict performance and which don’t - allowing companies to remove irrelevant criteria; identifying which interviewers are the best at hiring top talent and uncovering their tactics to share with the broader team; and spotting the most prevalent biases in the hiring process and what steps can be taken to overcome them.
3. Continuous improvement and adaptability – Hiring processes today are often static. Many companies continue to use the same assessments, interview questions, and tasks for years, despite the evolving world of work and the rapid change in required skills. AI allows hiring processes to become adaptive and ever-improving based on data. For example - since we are constantly researching and benchmarking dominant skills across roles and industries, our AI can proactively recommend which emerging skills to assess, helping clients stay ahead as their importance grows.

Alongside being a huge advocate for utilizing AI in hiring, It’s also really important for me to address the hype around AI hiring. There’s a lot of snake oil out there. I strongly recommend that companies considering AI implementation ensure it is used ethically and transparently. AI should never replace human judgment but rather support and enhance it.

Aron: This sounds promising, but critics of AI in hiring worry about algorithms actually reinforcing biases rather than eliminating them. How do you ensure fairness?

Shiran: I completely agree with the critics. If your AI is trained on past human decisions, it will inevitably replicate the biases embedded in those decisions. At Informed Decisions, we take a different approach: we focus on interviewers as the most important hiring tool a company has and provide them with actionable feedback to help reduce their biases.

Our algorithms enhance the weight of skills that are proven to be predictive of performance and reduce the weight of those that are less predictive. We also continuously monitor our interview questions for group differences to ensure they are not biased against any specific population.

In a nutshell, we amplify what works and is unbiased while eliminating the rest.

Aron: Very interesting. To wrap up, if you could give hiring managers one key piece of advice to improve their decision-making today, what would it be?

Shiran: Don’t rely on intuition. Create a structured hiring process supported by data, and utilize multiple tools and perspectives to make decisions. Remember: There isn’t a single area in business today that isn’t relying on data to make decisions (sales, marketing, finance, manufacturing, etc.). Isn’t it absurd that when it comes to the most important resource an organization has, we are still relying on feelings and impressions?

Closing Note: Shiran is on a mission to fix the hiring process - not just for companies, but for the millions of job seekers overlooked due to flawed selection methods. To me, it’s exciting to see how data isn’t replacing people but empowering us to build high-performing teams of people while ensuring we don’t overlook the less obvious yet highly qualified candidates.

Thank you for reading. If you've made it this far, you might find this interesting as well: