Technology & AI · ML & AI

AlgoFair: Algorithmic Fairness in HR & Lending

Simulation where participants navigate algorithmic fairness trade-offs as Head of AI at Equitas Financial, a Latin American lending company.

5 rounds Executive English, Español

Preview

About this simulation

Simulation where participants navigate algorithmic fairness trade-offs as Head of AI at Equitas Financial, a Latin American lending company. Across 5 rounds, learners audit bias, select fairness metrics, manage unintended consequences, defend regulatory investigations, and design governance frameworks — confronting the impossibility of achieving all fairness definitions simultaneously.

Who it is for

An advanced simulation for participants used to working with the main frameworks and trade-offs of the subject, designed for executive education and experienced professionals.

How a session runs

  1. The instructor creates a session from the Eureka dashboard and invites the participants.
  2. Participants play 5 rounds. In each one they submit their decisions and the simulation calculates the results. The first round opens with: Fairness Audit.
  3. The simulation can be run in English, Español.
  4. The instructor follows each participant's progress and results from the dashboard, and uses the class results for the debrief.

Subjects covered

Designed for courses in ML & AI.

  • Responsible AI & Algorithmic Fairness
  • Ethics in AI & Data Use
  • HR Analytics & People Data

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