{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "Does AI eliminate hiring bias entirely?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "No. AI can reduce certain human biases by standardising processes and removing identifiers, but it can introduce new biases if training data or features act as proxies for protected characteristics. Continuous audits and human oversight are essential."
      }
    },
    {
      "@type": "Question",
      "name": "How should we measure whether AI is improving diversity?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Track conversion rates, time to hire, offer acceptance and retention by demographic group. Also measure candidate satisfaction and compare performance of hires sourced via AI versus other channels."
      }
    },
    {
      "@type": "Question",
      "name": "Are anonymised CVs effective?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Yes. Anonymisation removes obvious triggers for affinity bias and encourages focus on skills. It should be combined with structured evaluation to be most effective."
      }
    },
    {
      "@type": "Question",
      "name": "Can vendors be trusted to provide fair AI?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Some vendors provide robust fairness documentation and support audits. Demand transparency, require fairness metrics and, where possible, audit vendor models using your own data."
      }
    },
    {
      "@type": "Question",
      "name": "What should we tell candidates about AI use?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Be transparent. Explain what the AI evaluates, how it influences decisions and how candidates can request human review or further information."
      }
    },
    {
      "@type": "Question",
      "name": "How often should we audit AI systems?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Audit before deployment, then at regular intervals and whenever you see unexpected changes in hiring patterns. Frequency depends on volume and impact, but quarterly reviews are a good starting point for many organisations."
      }
    },
    {
      "@type": "Question",
      "name": "Where can I start if my team has no AI experience?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Begin with a clear problem statement, run a pilot on a single use case, choose a vendor offering transparency and involve legal, data and diversity leads from the start. Use simple models and build governance as you scale."
      }
    }
  ]
}