If an algorithm rejects you before a human ever reads your name, who is accountable for the decision — the employer, or the software vendor?
Human Resource Management (Oracle, 2024) is the strategic work of hiring, supporting and motivating people to meet business goals. The course says AI lands in three places first — recruiting, performance management, employee engagement. This case is the front door: recruiting. It is also where the first lawsuits landed.
HRM (Oracle, 2024): recruiting, hiring, training, compensating and developing people to meet organisational goals. AI's three most prominent HR application areas are recruiting, performance management and employee engagement.
The course's benefit list (IBM n.d.; IMD 2025): enhanced recruitment, improved employee experience, increased efficiency and administrative productivity, better decision-making, reduced errors, improved engagement, personalised learning & development, enhanced workforce planning, and better talent retention.
Three areas: recruiting, performance, engagement. Name the platforms — Workday, HireVue, Eightfold — and remember AI's first HR job is screening people.
The deck shows the vendors; it does not show the lawsuits. Mobley v. Workday (N.D. Cal., No. 3:23-cv-00770) is a class action alleging Workday's AI screening tools discriminated by age, race and disability. In 2024 the court let it proceed — and crucially allowed the theory that a software vendor can be liable as an employer's agent. In May 2025 it was allowed to advance as a nationwide age-discrimination collective action.
EEOC v. iTutorGroup (2023): a $365,000 settlement after recruiting software was set to auto-reject female applicants 55+ and male applicants 60+. And Amazon scrapped its own experimental recruiting engine in 2018 (Reuters) after it taught itself to downgrade CVs containing the word "women's".
The defence employers reach for is that the algorithm decided. The through-line of this module rejects that: accountability cannot be delegated to a model. Someone chose to buy the tool, chose the training data, and chose not to keep a human in the loop. The Mobley agent theory is the law catching up to that idea.
The practical fix is not a smarter model but governance: bias audits before deployment (New York City's Local Law 144 now mandates them for automated hiring tools), disclosure to candidates, and a human who can be named as responsible for the outcome.
The question is never "was the AI accurate?" It is "who is accountable when it is wrong?" — and the answer is always a person.
Name the three HR areas AI enters first, and two of the platforms the course names.
What made Mobley v. Workday legally significant?
Why does a hiring model trained on past hires reproduce bias?