A Deep Dive into Bias Detection & Mitigation
Bias can surface through outputs, model behavior, and use case design, often in subtle ways that evade casual review. This workshop focuses on making bias detectable, measurable, and addressable through concrete engineering and evaluation practices.
To win, your GenAI solutions must systematically detect, measure, and mitigate bias while clearly communicating risk and tradeoffs.
When bias detection and mitigation are ad hoc or informal, teams struggle to manage risk responsibly.
- Hidden bias: Outputs and behaviors exhibit bias that is difficult to detect without structured analysis.
- Unclear fairness signals: Teams lack reliable ways to measure representational fairness and equity.
- Poor accountability: Mitigation decisions are not clearly documented or communicated to stakeholders.
These gaps increase reputational risk, regulatory exposure, and loss of user trust.
In this hands-on workshop, your team applies practical methods to detect, measure, and mitigate bias through guided exercises and scenario analysis.
- Detect bias in model outputs and behaviors using structured review techniques.
- Measure representational fairness and equity with targeted datasets and metrics.
- Apply debiasing techniques to prompts and models within realistic constraints.
- Review use case risk profiles to prioritize mitigation efforts appropriately.
- Communicate bias findings and mitigation strategies clearly to stakeholders.
- Detecting Bias in Outputs and Model Behavior
- Measuring Representational Fairness and Equity
- Applying Debiasing Techniques to Prompts and Models
- Reviewing Use Case Risk Profiles
- Communicating Bias Mitigation to Stakeholders
- Identify bias patterns in GenAI outputs and system behavior.
- Apply fairness and equity metrics to evaluate representational impact.
- Implement debiasing techniques at the prompt and model interaction level.
- Assess bias risk across different use cases and deployment contexts.
- Communicate mitigation decisions and limitations with clarity and confidence.
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
4 hours
Intermediate
Bias evaluation datasets, prompt analysis exercises, and mitigation frameworks