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Challenge

Responsible AI Mental Health Impact Assessment

OpenAI's focus on the 'potential impact of models on mental health' signals a critical area for responsible AI development. This challenge tasks developers with creating a multi-agent system using CrewAI to proactively identify, assess, and propose mitigation strategies for the mental health impacts of generative AI models. The system will orchestrate a team of specialized agents, powered by GPT-5, to conduct research, synthesize findings, and formulate policy recommendations. Emphasis will be placed on advanced RAG techniques, extended thinking, adaptive reasoning budgets, and MCP tool integration for comprehensive societal data analysis.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Orchestrate a role-based multi-agent team using CrewAI and GPT-5 for a comprehensive assessment and mitigation strategy of AI's mental health impacts, integrating MCP tools and advanced RAG.

Delivery guide

How work is evaluated

Evaluation

Evaluation will assess the quality and comprehensiveness of the multi-agent system's mental health impact assessment, the ethical soundness of proposed mitigation strategies, and the overall collaborative effectiveness of the CrewAI team. The use of RAG, extended thinking, and MCP tools will be closely examined.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

Learning goals

What you should walk away with

  • Design MCP-enabled tool integration for accessing simulated social sentiment and research databases.

  • Implement advanced RAG pipelines with GPT-5 for synthesizing complex research.

  • Develop extended thinking modules and adaptive thinking budgets for nuanced ethical analysis.

  • Master CrewAI for orchestrating specialized, role-based agent teams.

Resources and assets

Reference links and supporting material

Dataset notes

Sample data for 2 tasks

Challenge setup

Evaluation will assess the quality and comprehensiveness of the multi-agent system's mental health impact assessment, the ethical soundness of proposed mitigation strategies, and the overall collaborative effectivenes...

Challenge input

{'ai_application_description': 'Description of the AI model/application', 'focus_areas': ['anxiety', 'social_comparison', 'information_overload']}

Agent execution

No agent tool is listed for this challenge.

Evaluated output

{'report': {'executive_summary': '...', 'identified_impacts': [{'impact': '...', 'mechanisms': '...', 'severity': '...', 'evidence_sources': ['...'...

Evaluation checks
  • Identifies a minimum number of distinct mental health impacts.
  • Evidence of MCP tool calls for data retrieval or analysis in the report's evidence sources or mitigation st...
Configured evaluation evidence
  • ReportCohesionAndClarity target: 4
Configured runtime
  • Python execution harness

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

No tool records are attached.

Evaluation contract

  • Identifies a minimum number of distinct mental health impacts.
  • Evidence of MCP tool calls for data retrieval or analysis in the report's evidence sources or mitigation strategies.

Metrics

  • ReportCohesionAndClarity · Target 4
  • PolicyRecommendationQuality · Target 4

Workflow tasks

  1. Task 1

    Input: {'ai_application_description': 'Description of the AI model/application', 'focus_areas': ['anxiety', 'social_comparison', 'information_overload']}

    Output: {'report': {'executive_summary': '...', 'identified_impacts': [{'impact': '...', 'mechanisms': '...', 'severity': '...', 'evidence_sources': ['...']}], 'mitigation_strategies': [{'strategy': '...', 'responsible_agent': '...', 'tools_used': ['...']}], 'ethical_considerations': ['...']}}

    Execution harness: Python

  2. Task 2

    Input: {'impact_assessment_report': {...}, 'relevant_policies_db_access': 'MCP_PolicyDB_API'}

    Output: {'policy_recommendations': [{'area': 'regulation', 'recommendation': '...', 'justification': '...', 'agents_involved': ['...']}]}

    Execution harness: Python

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about Responsible AI Mental Health Impact Assessment