The student analyzes ethical considerations related to the use of AI, including bias, transparency, data privacy, and misinformation (level 2).
Contributing Skills
- RSD 1: Data Ethics and Privacy Concerns in AI Applications Analysis: Analyze data ethics and privacy concerns in artificial intelligence (AI) applications.
- RSD 2: Ethical Considerations and Implications in AI: Evaluate ethical considerations and implications in artificial intelligence (AI), including bias, fairness, and transparency.
- RSD 3: Ethical Issues in AI Description: Describe ethical issues related to AI, such as privacy violations, misinformation, and more.
Evidence Statement
- ES 1: Given an AI use case, the student identifies potential ethical concerns relating to bias (level 1).
- ES 2: Given an AI use case, the student explains potential implications of bias (level 2).
- ES 3: Given an AI use case, the student identifies potential ethical concerns relating to transparency (level 1).
- ES 4: Given an AI use case, the student explains potential implications of lack of transparency (level 2).
- ES 5: Given an AI use case, the student identifies potential ethical concerns relating to data privacy (level 1).
- ES 6: Given an AI use case, the student explains potential implications regarding data privacy (level 2).
- ES 7: Given an AI use case, the student identifies potential ethical concerns relating to misinformation (level 1).
- ES 8: Given an AI use case, the student explains potential implications of misinformation (level 2).
Associated Learning Resources and Student Activities
Forthcoming.
Associated AI Literacy Competency Framework for Educators
#3: Critical Thinking and Fact checking
- Describe the context in which AI information is presented and the reliability of the sources (level 1).
- Recognize potential logical fallacies, misinformation, made-up facts, over-generalizations, and bias (level 1).
- Identify historical instances where factual information was either leveraged accurately or distorted for propagandistic purposes from various media (level 1).
#5: AI Ethics
- Identify and categorize various types of risks, both perceived and real, associated with AI applications. This includes understanding biases in algorithms, privacy concerns, the spread of misinformation, and the potential for job displacements (level 1).
- Define and explain fundamental ethical principles related to AI, such as fairness, transparency, accountability, and privacy (level 1).
- Recognize and describe common ethical dilemmas that arise in AI, such as decision-making in autonomous vehicles or AI in surveillance (level 1).
- Assess the level and nature of risks associated with specific AI implementations. This involves evaluating both immediate and long-term implications (level 2).