Trial & Error & Error Podcast

36. Why are Interviews so Complicated?

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🎙️ Ever wondered why landing a job feels like running a marathon through an obstacle course? In this episode of Trial & Error & Error, we dive deep into the increasingly complicated world of job interviews. From endless interview rounds to AI-powered screening tools, we explore why the hiring process has become so complex — and what the science actually says about it all.

Join us as we unpack:

  • ⏰ Why interview processes now stretch far beyond the ideal 21-day timeline
  • 🔄 The explosion of multiple interview stages and what that means for candidates
  • 🔬 What research reveals about structured vs. unstructured interviews
  • ⚖️ How organisations' attempts at fairness sometimes backfire
  • 🤖 The role of AI and technology in making things more complicated (not simpler!)
  • 💬 The human psychology behind interview anxiety and uncertainty

    • Whether you're a job seeker frustrated by the process or an employer trying to hire better, this episode offers eye-opening insights backed by research and real-world examples.

    💡 Spoiler alert: The solution isn't more steps — it's smarter structure and clearer communication.

    🎧 Subscribe, share, and don't forget to leave us a review! Follow us @tee.podcast on Instagram and send us your hiring horror stories.

    📚 Resources & References

    Academic Research:

    • Smirnov, I., Lemmerich, F., & Strohmaier, M. (2021). Quota-based debiasing can decrease representation of the most under-represented groups. Royal Society Open Science, 8(9), 210821. https://doi.org/10.1098/rsos.210821

      • News Articles:

      • Smith, R. A. (2025, August 12). AI Is Forcing the Return of the In-Person Job Interview. The Wall Street Journal. https://www.wsj.com/lifestyle/careers/ai-job-interview-virtual-in-person-305f9fd0

        • Additional Sources Mentioned:

        • 2023 Candidate Experience Survey — Austrian Employee Union
        • Meta-analyses on interview validity and structure (general research literature)
        • Research on contrast effects in interviewing
        • Studies on algorithmic fairness tools in hiring

          • ...more
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