🧠 Topic Summary
Exploring the ethical implications of Artificial Intelligence (AI) in medicine doesn't always require a computer! An "unplugged activity" means we use real-world scenarios, discussions, and role-playing to understand complex concepts without relying on digital tools. For AI in medicine, this could involve simulating patient-doctor interactions with AI assistance, debating data privacy concerns, or designing ethical guidelines using physical props like sticky notes or index cards. It's about making abstract ethical dilemmas tangible and fostering critical thinking through collaborative, hands-on engagement.
These activities help us grapple with vital questions: How do we ensure fairness when AI makes diagnostic recommendations? Who is responsible if an AI makes a mistake? How do we maintain patient trust and autonomy in an increasingly AI-driven healthcare system? By "unplugging," we strip away the technical complexity to focus purely on the human, moral, and societal impact of AI in healthcare.
📚 Part A: Vocabulary
Match the term to its correct definition below:
- 1️⃣ AI Ethics
- 2️⃣ Bias
- 3️⃣ Transparency
- 4️⃣ Accountability
- 5️⃣ Patient Autonomy
Definitions:
- 💡 The ability to understand how an AI system arrives at its decisions, making its processes clear and explainable.
- ⚖️ A predisposition or prejudice, often unintentional, that can lead an AI system to make unfair or inaccurate decisions.
- 🤝 The obligation of individuals or organizations to accept responsibility for their actions and decisions, especially with AI.
- 🧍♀️ The right of a patient to make informed decisions about their own medical care, free from coercion.
- 🌍 The principles that guide the design, development, and use of AI systems to ensure fairness, privacy, and safety.
✍️ Part B: Fill in the Blanks
Complete the following paragraph using the most appropriate words from the list below:
(Words: ethics, bias, transparency, consent, accountability)
Artificial Intelligence (AI) is transforming medicine, offering powerful tools for diagnosis and treatment. However, its integration raises significant ___________ concerns. For instance, ___________ in training data can lead to unfair treatment for certain patient groups. Ensuring ___________ in AI decision-making is crucial so that healthcare providers understand how recommendations are generated. Furthermore, obtaining informed ___________ from patients for AI-driven interventions is paramount, and maintaining robust ___________ remains essential to prevent errors and ensure patient safety.
🤔 Part C: Critical Thinking
- 🌐 Imagine an AI system designed to triage emergency room patients. It learns from historical data, which shows that patients from lower-income neighborhoods often wait longer due to resource allocation challenges. How might this AI system inadvertently perpetuate or even worsen existing healthcare inequities? What "unplugged" activity could you design to explore this specific ethical dilemma with a group of students or healthcare professionals?