AI Governance and Compliance for HR and People Operations

Even the most advanced AI tools can fall short when they inherit bias from the data or processes they’re trained on. And when that bias seeps into hiring decisions, the consequences can be costly—for individuals, for diversity, and for your company’s reputation. This lecture breaks down how bias shows up, why it happens, and what you can do to detect and mitigate it early.
You’ll learn:

• How AI bias emerges from historical data, system design, and hidden proxies

• Real-world examples of biased AI decisions and what they cost organizations

• The legal standards used to measure bias, like the four-fifths rule

• What new regulations (like NYC’s Law 144 and the EU AI Act) mean for your hiring tools

• Four practical strategies to make your AI systems fairer, including audits and human review

AI needs data to work—but in HR, that data is often deeply personal. And when it’s not handled with care, what starts as innovation can quickly turn into a breach of trust. In this lecture, you’ll explore how to responsibly manage the sensitive employee information that fuels AI tools, without crossing ethical or legal lines.
You’ll learn:

• What kinds of personal data AI tools collect in HR and why it matters

• How major privacy laws like GDPR and CCPA apply to AI-driven HR practices

• Key principles for responsible data handling: minimization, security, and transparency

• Why HR—not just IT or legal—must lead on ethical data stewardship

• How to balance powerful insights with employee privacy and consent

As AI tools become more embedded in hiring, promotion, and performance decisions, regulators are starting to catch up—and they’re not pulling any punches. From class-action lawsuits in the U.S. to sweeping AI legislation in Europe, the legal landscape is evolving fast. In this lecture, you’ll learn how to stay compliant and proactive, whether your company builds its own tools or buys them off the shelf.
You’ll learn:

• How existing laws like Title VII, the ADA, and GDPR already apply to AI in HR

• What the EU AI Act means for “high-risk” systems used in hiring and evaluation

• Key U.S. laws including NYC’s Local Law 144 and Illinois’ AI Video Interview Act

• What the White House’s AI Bill of Rights signals about future federal enforcement

• Practical compliance steps HR can take to stay ahead of legal and reputational risks

Having the right AI tool is only half the battle—governing how it's used is where the real work begins. As AI becomes more embedded in HR decisions, organizations must move beyond intent and put real systems in place to manage risk, ensure fairness, and protect employees. This lecture explores what effective AI governance actually looks like on the ground—and how HR teams can lead the charge.
You’ll learn:

• What AI governance frameworks like NIST’s “Map, Measure, Manage, Govern” model offer HR teams

• How to create internal AI policies that go beyond slogans to guide real-world decisions

• The role of HR-led ethics charters, cross-functional oversight groups, and approval workflows

• Why companies like Unilever are putting humans back in the loop—and how you can do the same

• Practical ways to embed governance into HR operations, from procurement to performance tracking

Even well-intentioned AI can go off course—and many organizations don’t catch it until it’s already done damage. In fact, over a third of employers say they’ve discovered bias in their AI tools only after deployment. This lecture focuses on how to stay ahead of those risks through continuous auditing, smart monitoring, and a culture of transparency.
You’ll learn:

• What a bias audit involves, and how to run one using techniques like subgroup testing and disparate impact analysis

• How to choose the right fairness metrics and leverage tools like AI Fairness 360 or Google’s What‑If Tool

• What model drift is, why it matters, and how to spot it before it affects your people decisions

• How to use model cards and documentation to build trust and accountability

• Why auditing isn’t just about compliance—it’s about protecting people, reputations, and long-term outcomes

Most HR teams don’t build their own AI—they buy it. But that doesn’t mean the accountability stops with the vendor. In this lecture, you’ll learn how to take control of the AI tools you source, use, and rely on from third-party providers. From pre-purchase vetting to long-term monitoring, we’ll show you how to stay in the driver’s seat.
You’ll learn:

• How to vet AI vendors before adoption, including key questions to ask about training data, model fairness, and explainability

• What to include in contracts to ensure legal compliance, data privacy, and the right to audit or exit if needed

• How to track vendor performance over time and catch issues like model drift or biased outcomes early

• Why vendor management is a legal responsibility under new AI regulations, not just a procurement detail

What happens when a global company throws out traditional hiring methods and builds an AI-powered system from scratch? In this lecture, we examine how Unilever transformed its recruitment process using neuroscience games, AI video interviews, and human-in-the-loop decision-making—at a scale of hundreds of thousands of applicants per year.
You’ll learn:

• How Unilever designed a high-volume, fairness-focused hiring process using AI tools like Pymetrics and HireVue

• The measurable impact on time-to-hire, recruiter workload, and candidate diversity

• What transparency and ethical oversight looked like in practice, including how Unilever responded to public concerns

• Key lessons HR professionals can take away about scaling AI responsibly without sacrificing trust or inclusion

AI in HR isn’t a someday scenario—it’s happening right now, and evolving fast. From generative AI reshaping communication to sweeping new laws like the EU AI Act, the rules of the game are shifting beneath our feet. In this lecture, we look at what’s next and how HR professionals can stay ahead of the curve by taking a leadership role in governance.
You’ll learn:

• How generative AI is changing everyday HR tasks—and what policies are needed to use it responsibly

• The newest U.S. and EU regulations you need to prepare for (including bias audits and “high-risk” classifications)

• What employees and candidates expect from AI—and how HR can meet rising demands for transparency

• How HR roles are expanding to include AI governance, vendor accountability, and ethical oversight

You’ve made it to the final lecture — now it’s time to connect the dots. This session brings together everything we’ve covered, turning insight into action and theory into practice. Whether you're just getting started or ready to lead the charge on AI governance, this wrap-up will help you build momentum and take confident next steps.
You’ll learn:

• The key lessons from each section of the course — from ethical principles to compliance, oversight, and vendor strategy

• A practical action plan with short-, medium-, and long-term steps for HR professionals

• Where to find the best frameworks, toolkits, and communities for ongoing learning

• Why ethical AI in HR is about more than risk — it’s about trust, leadership, and shaping the culture of tomorrow