my research direction

When done well, XAI should help answer questions such as:

  • “Why did the AI output this result for a given input?”

  • “Which input features or factors contributed the most to this decision?”

  • “Under what conditions is the AI reliable (or unreliable)?”

  • “What are the limitations, biases, or risks of using this model in production?”

  • “How can we debug, audit, or improve the model behavior (especially for fairness / safety)?”

Close-up of a researcher analyzing AI model data on multiple screens.
Close-up of a researcher analyzing AI model data on multiple screens.
Model Audit

Examining AI behaviors for hidden risks.

Visualization of AI decision pathways highlighting safety checkpoints.
Visualization of AI decision pathways highlighting safety checkpoints.
Safety Checks

Custom tests to ensure model reliability.

Team meeting discussing reconnaissance techniques around a table.
Team meeting discussing reconnaissance techniques around a table.
Graphs and charts showing AI model vulnerability assessments.
Graphs and charts showing AI model vulnerability assessments.
Recon Tools

Developing tools to probe AI safely.

Risk Analysis

Identifying and mitigating AI threats.