π Topic Summary
Unplugged activities for AI bias detection and mitigation involve exploring AI concepts and biases using physical activities and discussions, without relying on computers. These activities help individuals understand how biases can be unintentionally introduced into algorithms and data, leading to unfair or discriminatory outcomes. By stepping away from the screen, participants can engage in collaborative problem-solving and critical thinking, fostering a deeper understanding of fairness and ethical considerations in AI.
The goal is to develop strategies for identifying and mitigating biases in datasets and algorithms, ensuring that AI systems are fair, transparent, and accountable. Unplugged activities make complex AI ethics concepts accessible and engaging for learners of all backgrounds, promoting responsible AI development and deployment.
π€ Part A: Vocabulary
Match the term with its definition:
| Term |
Definition |
| 1. Bias |
a. A simplified representation of data, often used for prediction. |
| 2. Algorithm |
b. Unfair prejudice for or against someone or something. |
| 3. Data Set |
c. A set of instructions for solving a problem or completing a task. |
| 4. Mitigation |
d. A collection of related sets of information that is composed of separate elements but can be manipulated as a unit by a computer. |
| 5. Model |
e. The action of reducing the severity, seriousness, or painfulness of something. |
βοΈ Part B: Fill in the Blanks
Complete the following paragraph using the words: bias, fairness, data, algorithms, and outcomes.
AI systems learn from ________. If this _______ contains ________, the _______ might produce unfair ________. Ensuring ______ in AI requires careful examination of ______ and ________.
π€ Part C: Critical Thinking
Imagine you are designing an AI system to recommend job applicants to companies. What steps would you take to ensure that the system does not discriminate based on gender, race, or other protected characteristics?