# data[].attributes.body
Students analyze a case where an AI system makes a different diagnosis than a human doctor. The case involves a patient with complex symptoms where the AI suggests a rare condition while the experienced physician believes it's a more common ailment. Students must discuss:
- The weight given to AI vs. human expertise
- Legal and ethical implications of following/not following AI recommendations
- Patient autonomy in AI-assisted decisions
- Documentation and liability concerns

# data[].attributes.body
Split the class into groups to analyze a dataset used to train an AI system for patient triage. The dataset shows disparities in how different demographic groups are represented. Students must:
1. Identify potential biases in the training data
2. Discuss implications for healthcare equality
3. Propose solutions to mitigate bias
4. Present findings and debate ethical solutions

# data[].attributes.body
Students take on roles of different stakeholders in a scenario where a hospital is considering implementing a new AI system that requires access to extensive patient data. Roles include:
- Privacy Officer
- Hospital Administrator
- AI Developer
- Patient Advocate
- Insurance Representative
- Ethics Committee Member
Each must argue their position and work toward a consensus.

# data[].attributes.body
Students examine a case where an AI system's decision-making process isn't clearly explainable to patients. They must:
1. Review the 'black box' problem in healthcare AI
2. Develop patient communication strategies
3. Create guidelines for when AI systems must be explainable
4. Consider legal and ethical implications of unexplainable AI decisions

# data[].attributes.body
Students work through a scenario where an AI system crashes during critical patient care. They must:
1. Develop emergency protocols
2. Consider backup systems and redundancies
3. Address liability issues
4. Create patient safety guidelines
5. Design communication procedures

# data[].attributes.body
Students analyze how AI healthcare systems might need to be adapted for different cultural contexts. They examine:
- Cultural variations in medical decision-making
- Religious considerations
- Family involvement in different cultures
- Privacy expectations across cultures
- Ethical frameworks in different societies

# data[].attributes.body
Students tackle a case where an AI system is used to prioritize patient care and resource allocation during a crisis. They must:
1. Evaluate the ethical principles used in the algorithm
2. Consider fairness and equality
3. Develop criteria for emergency situations
4. Address potential discrimination
5. Create appeals processes

# data[].attributes.body
Students develop an ethical framework for using AI predictive analytics in preventive care. Consider:
- Patient notification requirements
- Insurance implications
- Privacy concerns
- Right to know vs. right not to know
- Psychological impact on patients

# data[].attributes.body
Students design informed consent documents for AI-assisted medical procedures. They must address:
1. Explanation of AI's role
2. Risks and benefits
3. Alternatives to AI-assisted care
4. Data usage and privacy
5. Patient rights and options

# data[].attributes.body
Students work in groups to develop comprehensive AI ethics policies for a fictional healthcare institution. They must include:
- Data protection protocols
- Patient rights and autonomy
- Professional responsibilities
- Quality assurance measures
- Incident reporting procedures
- Regular ethics review requirements

# data[].attributes.body
Students analyze a case where an AI system makes a significant error in patient care. They must:
1. Develop error reporting procedures
2. Create patient communication strategies
3. Design investigation protocols
4. Address liability issues
5. Propose system improvements
6. Consider ethical implications of continued use