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AI Fundamentals

An overview and instructions for the course.

About This Course

An introduction to different sources of bias, including issues in data sets, algorithmic design, and human interaction with AI systems.

Common Sources of Bias in AI-Powered Tools

An exploration of the potential negative impacts on decision-making, equity and inclusion, and trust in AI tools resulting from biases in AI-powered tools.

Potential Consequences of Biases

Potential Consequences of Biases in AI Tools

A series of examples showcasing real-life instances where AI tools in education were found to be biased. 

Examples of Bias in Education

Examples of Bias in AI-Powered Education Tools

This chapter delves into the complexities, challenges, and inherent constraints that hinder the effective identification and mitigation of AI biases.

Limitations of Bias Testing

This chapter outlines actionable solutions to mitigate and address AI biases in education.

Solutions to Address Biases

Focus is given on how to train educators to spot and address biases in educational AI tools, along with practical tools and resources.

Training Educators

Additional Resources

Activity: Designing an AI Bias Workshop

References

Pass the knowledge quiz with a score of 100% to earn the course completion certificate.  

Course Completion Quiz

The advent of artificial intelligence (AI) in education brings limitless potential to customize and enhance learning experiences. However, these advancements also carry the risk of inheriting and amplifying human biases. This course offers participants—who include educators, developers, and policymakers—a comprehensive look into the challenges posed by biases in AI-powered educational tools. We will explore the root causes of bias in AI, study examples that have affected the educational landscape, and examine strategies to address and reduce these biases.Upon completing this course, participants will have gained an awareness of the complexities of biases in AI educational tools and the necessary tools and strategies for creating a fair and equitable learning environment through rigorous testing, continual reassessment, and dedicated educator training.This course is asynchronous, allowing participants to engage with course materials at their own pace and according to their schedules. If you have any questions or comments about this course, we encourage you to post them in the <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.eduvators.net/community/eduvators-network-1298">Eduvators Network Community</a> # Discussion channel.

This course offers participants—including educators, developers, and policymakers—a comprehensive look into the challenges posed by biases in AI-powered educational tools. 

Understanding and Addressing Bias in AI-Powered Educational Tools

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What you will learn

Understand the nature and origins of bias in AI-powered educational tools.

Recognize and critically assess the implications of biased AI in educational settings.

Develop a list of strategies and best practices to mitigate and address bias.

Foster continuous improvement and due diligence in using AI tools in education.

Course content

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