Practice Algorithmic Bias in Automation - 34.5.1 | 34. Ethical Considerations in the Use of Automation | Robotics and Automation - Vol 3
Students

Academic Programs

AI-powered learning for grades 8-12, aligned with major curricula

Professional

Professional Courses

Industry-relevant training in Business, Technology, and Design

Games

Interactive Games

Fun games to boost memory, math, typing, and English skills

Algorithmic Bias in Automation

34.5.1 - Algorithmic Bias in Automation

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is algorithmic bias?

💡 Hint: Think about how data can influence outcomes.

Question 2 Easy

Why is diversity in datasets important?

💡 Hint: What happens if the dataset is only one type of data?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main cause of algorithmic bias?

A) Poor AI design
B) Biased training data
C) Lack of funding

💡 Hint: Think about what the AI learns from.

Question 2

True or False: Algorithmic bias can result in discriminatory outcomes.

True
False

💡 Hint: Consider the implications of AI making decisions.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Analyze a case where biased algorithmic decisions led to negative outcomes. Discuss the implications for ethical AI development.

💡 Hint: Look for recent news stories or academic papers discussing bias in algorithms.

Challenge 2 Hard

Propose a strategy to audit AI systems for bias and discuss how transparency would improve public trust.

💡 Hint: Consider how existing companies handle transparency and what practices they follow.

Get performance evaluation

Reference links

Supplementary resources to enhance your learning experience.