import gradio as gr import json def analyze_ai_scenario(scenario, role): """ Analyze an AI-in-education scenario from different stakeholder perspectives """ # Base analysis framework base_benefits = [ "Increased efficiency in routine tasks", "Personalized learning experiences", "Enhanced accessibility for diverse learners", "Data-driven insights for improvement", "24/7 availability for support" ] base_risks = [ "Over-dependence on technology", "Privacy and data security concerns", "Potential for academic dishonesty", "Bias in AI algorithms", "Job displacement concerns", "Digital divide implications" ] base_ethics = [ "Transparency in AI decision-making", "Consent and data ownership", "Equity and fairness in access", "Human oversight and accountability", "Long-term impact on learning" ] # Role-specific perspectives role_perspectives = { "Teacher": { "focus": "classroom implementation and pedagogical impact", "specific_benefits": [ "Reduced grading time for objective assessments", "Real-time feedback capabilities", "Differentiated instruction support", "Professional development insights" ], "specific_risks": [ "Loss of human connection with students", "Skill atrophy in manual assessment", "Increased workload for AI management", "Student over-reliance on AI assistance" ], "specific_ethics": [ "Maintaining authentic teacher-student relationships", "Balancing AI assistance with human judgment", "Ensuring pedagogical integrity", "Protecting student learning autonomy" ] }, "Student": { "focus": "learning experience and academic development", "specific_benefits": [ "Immediate feedback and support", "Customized learning pace", "Enhanced creativity tools", "Better organization and planning" ], "specific_risks": [ "Reduced critical thinking development", "Academic integrity violations", "Decreased peer collaboration", "Dependence on AI for problem-solving" ], "specific_ethics": [ "Honest representation of own work", "Understanding AI limitations", "Respecting intellectual property", "Developing authentic skills" ] }, "Administrator": { "focus": "institutional policy and resource management", "specific_benefits": [ "Cost reduction in operations", "Improved resource allocation", "Enhanced decision-making data", "Streamlined administrative processes" ], "specific_risks": [ "High implementation and maintenance costs", "Legal and compliance challenges", "Staff resistance and training needs", "Technology infrastructure requirements" ], "specific_ethics": [ "Equitable access across student populations", "Transparent policy development", "Responsible data governance", "Long-term institutional integrity" ] } } # Get role-specific information role_info = role_perspectives.get(role, role_perspectives["Teacher"]) # Combine base and role-specific insights all_benefits = base_benefits + role_info["specific_benefits"] all_risks = base_risks + role_info["specific_risks"] all_ethics = base_ethics + role_info["specific_ethics"] # Create formatted response response = f""" ## Analysis for: "{scenario}" ### Perspective: {role} ({role_info['focus']}) ### 🌟 **Potential Benefits** """ for i, benefit in enumerate(all_benefits[:6], 1): response += f"{i}. {benefit}\n" response += "\n### ⚠️ **Potential Risks**\n" for i, risk in enumerate(all_risks[:6], 1): response += f"{i}. {risk}\n" response += "\n### 🤔 **Ethical Considerations**\n" for i, ethic in enumerate(all_ethics[:5], 1): response += f"{i}. {ethic}\n" response += f""" ### 💡 **Key Questions for {role}s to Consider** - How can we maximize benefits while minimizing risks? - What safeguards need to be in place? - How do we maintain human agency and oversight? - What training or preparation is needed? - How do we measure success and impact? """ return response def create_demo(): """Create and return the Gradio interface""" # Example scenarios for users example_scenarios = [ ["AI writing essays for grade 9 students", "Teacher"], ["Chatbot tutoring for mathematics", "Student"], ["AI-powered plagiarism detection system", "Administrator"], ["Automated grading of multiple choice tests", "Teacher"], ["AI language translation for ESL students", "Student"], ["Predictive analytics for student performance", "Administrator"] ] with gr.Blocks( title="AI-in-Education Risk Simulator", theme=gr.themes.Soft(), css=""" .container { max-width: 900px; margin: auto; } .header { text-align: center; margin-bottom: 2rem; } .scenario-input { font-size: 16px; } """ ) as demo: gr.HTML("""

🎓 AI-in-Education Risk Simulator

Explore the benefits, risks, and ethical considerations of AI integration in educational settings

""") with gr.Row(): with gr.Column(scale=2): scenario_input = gr.Textbox( label="AI Scenario Description", placeholder="e.g., AI writing essays for grade 9 students", lines=2, elem_classes=["scenario-input"] ) role_dropdown = gr.Dropdown( choices=["Teacher", "Student", "Administrator"], value="Teacher", label="Your Role/Perspective", info="Select your role to get a tailored analysis" ) analyze_btn = gr.Button( "🔍 Analyze Scenario", variant="primary", size="lg" ) with gr.Row(): output = gr.Markdown( label="Analysis Results", elem_classes=["output-container"] ) # Set up the interaction analyze_btn.click( fn=analyze_ai_scenario, inputs=[scenario_input, role_dropdown], outputs=output ) # Also trigger on Enter key scenario_input.submit( fn=analyze_ai_scenario, inputs=[scenario_input, role_dropdown], outputs=output ) # Add examples section gr.HTML("

📚 Try These Example Scenarios

") gr.Examples( examples=example_scenarios, inputs=[scenario_input, role_dropdown], outputs=output, fn=analyze_ai_scenario, cache_examples=True ) # Add footer with instructions gr.HTML("""

How to Use:

  1. Describe an AI scenario in education (be specific!)
  2. Select your role perspective
  3. Click "Analyze Scenario" to get tailored insights
  4. Use the analysis to inform discussions and decision-making
""") return demo # Create and launch the app if __name__ == "__main__": demo = create_demo() demo.launch( server_name="0.0.0.0", # Allow external access server_port=7860, # Default Gradio port share=True, # Create public link debug=True # Enable debug mode )