Areas of application for AI in the workplace
Objective: The worksheet aims to educate learners about the use of artificial intelligence in medical diagnostics. Learners should understand how AI systems support professionals, increase efficiency, and what ethical questions arise regarding responsibility and trust.
Contents and methods: The content includes an introduction to AI-supported imaging based on informational texts, analysis tables on areas of application, a practical case study, and an overview of the pros and cons of opportunities and risks. Methodologically, the content is taught through a combination of technical text work, structured analysis, case studies, and reflective exchange formats such as opinion rounds and evaluation surveys.
Competencies:
- Technical competence: Understanding how AI works in medical imaging and diagnostics.
- Ethical reflection competence: Critical examination of the question of who bears ultimate responsibility for AI-supported wrong decisions.
- Assessment competence: Weighing up the opportunities and challenges of technological innovations.
Target group and level: From grade 10 onwards.
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Target group and level
Grade 10
Subjects
Areas of application for AI in the workplace
Assignment
Read the following information text and fill in the table with the information provided.
- For each activity you choose, explain why AI support offers added value in this case.
AI Applications in Healthcare
Artificial Intelligence (AI) is reshaping healthcare by revolutionizing the roles of doctors, particularly in medical diagnostics and personalized medicine. AI is utilized to enhance accuracy and efficiency in diagnosing diseases, where machine learning algorithms analyze vast amounts of medical data, including imaging results, patient histories, and genetic information. This technology identifies patterns and anomalies often missed by human eyes, particularly in radiology, where AI tools examine CT scans, x-rays, MRIs, and other imaging types for diseases like cancer. AI systems can detect lesions or abnormalities with remarkable precision, often offering faster and more reliable results than traditional methods. Furthermore, AI predicts disease outbreaks and monitors patient health through wearable devices and electronic health records, enabling healthcare providers to take preventative measures and improve patient outcomes.
In personalized medicine, AI tailors treatments to individual patients based on their unique genetic makeup and health data. AI systems process complex datasets to recommend personalized treatment plans that maximize efficacy and minimize side effects. For example, AI assists oncologists in selecting the most appropriate chemotherapy drugs by analyzing the genetic profile of a tumor, ensuring patients receive the most effective treatment and improving survival rates. Additionally, AI-powered platforms help doctors manage chronic conditions like diabetes and hypertension by continually analyzing patient data to optimize medication dosages and lifestyle recommendations, leading to better adherence and health improvement.
AI integration in healthcare enhances doctors' capabilities and alters their roles by automating routine tasks and providing data-driven insights, allowing more time for complex decision-making and patient interaction. As AI evolves, its applications will continue to expand, offering new possibilities for improving patient care and redefining the future of medicine. However, challenges such as data privacy, ethical considerations, and the need for continuous oversight must be addressed to ensure AI's responsible and effective use in healthcare. The advantages include improved diagnostic accuracy, personalized treatment plans, and efficient chronic disease management, while disadvantages involve data privacy concerns and ethical considerations.
| Where could AI provide meaningful support to doctors? | ✅ | Reason |
|---|---|---|
| Diagnosis of diseases | ||
| Personal conversations with patients | ||
| Evaluation of MRI or X-ray images | ||
| Decision about people's feelings |
Assignment
- Read through the following case study.
- Analyze how a specialist and an AI system interact and then answer the question.
- Discuss in your study group the extent to which specialists should rely on AI statements and who bears ultimate responsibility in the event of an error.
AI-Assisted Chemotherapy Selection
An oncologist uses an AI platform to analyze a patient's tumor genetic profile, leading to a recommendation for a personalized chemotherapy plan. The AI's suggestion results in a significant improvement in the patient's recovery time and reduces severe side effects commonly associated with standard treatments. However, the patient's personal data privacy becomes a concern as the AI system requires access to sensitive genetic information. The oncologist also faces ethical considerations in relying heavily on AI recommendations without independent verification. Despite these challenges, the patient experiences a higher quality of life due to the tailored treatment approach.
Assignment
Complete the table using the knowledge you have learned.
- Create an overview of the advantages (e.g., speed, accuracy) that AI brings to everyday work.
- Consider the dangers, such as technical bias or the risk of wrong decisions.
Reflection
- Reflect on how AI could change the role model and daily tasks in the profession in the long term.
- Describe the possible emotional state of a specialist (e.g. between relief and scepticism) when an AI system provides significant support in complex analyses.
Traffic-light query
Read each statement and decide:
🔴 = Disagree 🟡 = Partially agree 🟢 = Fully agree
Mark one color per line and justify one of your decisions in 1–2 sentences.
Answer key for teachers
| Where could AI provide meaningful support to doctors? | ✅ | Reason |
|---|---|---|
| Diagnosis of diseases | ✅ | AI can quickly analyze large amounts of data and help doctors identify patterns. |
| Personal conversations with patients | Interpersonal communication requires empathy and genuine understanding, which AI can only provide to a limited extent. | |
| Evaluation of MRI or X-ray images | ✅ | AI can evaluate images very precisely and detect abnormalities faster than humans. |
| Decisions about human emotions | Emotions are subjective and complex; AI cannot assess them reliably. |
| Topic | Student notes |
|---|---|
| Advantages of AI in medicine | Improved diagnostic accuracy through pattern recognition in medical data. |
| Personalized treatment plans tailored to individual genetic profiles. | |
| Efficient management of chronic diseases through continuous data analysis. | |
| Risks of AI in medicine | Data privacy concerns due to the handling of sensitive patient information. |
| Ethical considerations in the deployment and use of AI technologies. | |
| Need for continuous oversight to ensure responsible and effective use. |
| Statement | 🔴 | 🟡 | 🟢 | Justification |
|---|---|---|---|---|
| AI can detect lesions or abnormalities faster and with more precision than traditional methods. | ✔ | AI's capabilities in analyzing imaging data enhance speed and accuracy compared to human analysis. | ||
| AI enhances diagnostic accuracy in healthcare. | ✔ | AI improves the precision of diagnoses by identifying patterns missed by humans. | ||
| AI can replace doctors in diagnosing diseases. | ✔ | AI supports but does not replace doctors; human oversight is crucial. | ||
| Data privacy concerns are a disadvantage of AI in healthcare. | ✔ | Handling sensitive patient data poses privacy challenges. | ||
| AI systems can recommend personalized treatment plans. | ✔ | AI analyzes genetic and health data to tailor treatments to individuals. | ||
| Ethical considerations are not a concern with AI in healthcare. | ✔ | Ethical issues, such as biases and decision-making processes, must be addressed. |