Multi-Agent Ad Policy Auditor
Develop an advanced multi-agent system using AutoGen to autonomously audit proposed advertising strategies against simulated user conversation data. This system will focus on ensuring compliance with privacy policies and verifying ad claims before deployment. Agents will collaborate to extract topics, propose ad targeting, review privacy implications, and fact-check promotional content, providing explainable insights into their decisions. The challenge emphasizes building robust, privacy-aware AI systems that can operate with human oversight where needed.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop an advanced multi-agent system using AutoGen to autonomously audit proposed advertising strategies against simulated user conversation data. This system will focus on ensuring compliance with privacy policies and verifying ad claims before deployment. Agents will collaborate to extract topics, propose ad targeting, review privacy implications, and fact-check promotional content, providing explainable insights into their decisions. The challenge emphasizes building robust, privacy-aware AI systems that can operate with human oversight where needed.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master AutoGen for orchestrating complex, conversational agent workflows with custom roles, message passing, and human-in-the-loop capabilities.
Implement data simulation strategies to generate realistic user conversation topics and personalization data, serving as input for ad targeting analysis.
Integrate Gemini 2.5 Flash as a specialized agent within the AutoGen system for rapid and cost-effective topic extraction and initial ad strategy generation.
Utilize LIME (Local Interpretable Model-agnostic Explanations) to generate post-hoc explanations for agent decisions, particularly regarding which user data features influence ad targeting or privacy violation flags.
Design a dedicated 'Privacy Auditor' agent within AutoGen to apply simulated privacy policies, identify potential data misuse, and flag non-compliant ad strategies.
Orchestrate the AutoGen agent interactions using Capably to monitor workflow execution, manage task distribution, and trigger alerts or generate compliance summaries.
Develop robust evaluation metrics and a testing harness to assess the accuracy, safety, and explainability of generated ad strategies and audit reports.
[ok] Wrote CHALLENGE.md
[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
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