When Deloitte agreed to refund the Australian government for a report that contained AI-generated errors, it raised a question that goes far beyond one consultancy or one tool.
The report: which included fabricated citations, false quotes, and references to studies that didn’t exist was meant to guide public decisions. Instead, it became a reminder of how easily trust can be lost when technology replaces verification.
The tool used? A generative AI system.
The outcome? Embarrassment, reputational damage, and financial restitution.
But more importantly — a wake-up call for everyone who uses AI in professional work.
⚖️ Accountability Doesn’t Disappear in the Cloud
Whether in law, communications, or HR, the question remains the same:
👉 Who’s accountable when AI gets it wrong — the algorithm, or the human behind it?
Although Deloitte’s case has nothing to do with HR or workplace fairness, the core issue is the same.
👉 When AI is used in professional judgment or reporting, who answers when it goes wrong?
That question mirrors the reality of HR and workplace decisions today: AI-generated hiring assessments, performance evaluations, or employee analytics may look legitimate but can just as easily contain fabricated, biased, or incomplete outputs — just like Deloitte’s AI-generated citations.
Both situations reveal the same risk: trusting AI output without human verification.
The truth is simple. AI doesn’t stand in court, respond to regulators, or explain itself to a client. We do.
Technology may make our work faster, but it doesn’t replace our duty of care, accuracy, or ethical judgment.
🧩 The Same Risk in People-Driven Decisions
In the HR and workplace context, we’re facing similar challenges.AI now helps draft job ads, screen resumes, assess performance, and even flag employee concerns.
But when those systems are left unchecked, they can just as easily fabricate, misjudge, or discriminate without anyone noticing until it’s too late. And when that happens, it’s not the system that faces scrutiny; it’s the people and policies behind it.
🚨 Why This Matters More Than Ever
With Singapore’s upcoming Workplace Fairness Legislation (WFL), every employment decision, from hiring to grievance handling, must be justified, documented, and explainable.
If AI plays a role in those decisions, the responsibility for fairness and accuracy remains with the employer. As Deloitte’s case shows, “the AI made the mistake” is not an acceptable defense.
🧭 Where We Draw the Line
At REL Alliance, we believe technology should empower, not replace, human judgment.
🧠 Our upcoming course: “When AI Intersects Workplace Fairness: Where Do We Draw the Line?”
👉 Explores how organizations can balance innovation with accountability.
Led by a legal practitioner with deep experience in employment law and workplace disputes, this session helps HR and business leaders:
✅ Understand the legal and ethical boundaries of AI use
✅ Recognize how AI bias or misuse can lead to unfair or discriminatory outcomes
✅Apply practical frameworks to ensure workplace decisions remain fair, explainable, and legally defensible
💬 A Thought to Leave You With
AI may assist your decisions.
👉 But it’s still humans — you, me, us — who must be able to explain and defend them.
Before you rely on an algorithm’s recommendation, ask yourself:
👉 “If an employee raised a complaint and we were questioned by MOM, could we clearly explain
how that decision was made?”
🚫 If the answer is no, that’s where you draw the line.
🧠 Learn More
Join us for “When AI Intersects Workplace Fairness: Where Do We Draw the Line?”
A practitioner-led course that helps organizations use AI responsibly, fairly, and in line with Singapore’s evolving workplace laws.
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