Recognizing biases in AI algorithms

1.2.9 Recognise that AI algorithms might not be configured to provide only the information that the user wants; they might also embody a commercial or political message

Topics:

AI generated content

Summary

Microcredential
1.2.A.4 Misinformation, Disinformation and Bias in AI generated content

1.2.A.4 Misinformation, Disinformation and Bias in AI generated content

Information and Data Literacy
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1.2.A.1 Misinformation and Disinformation: WHAT, HOW AND WHY

1.2.A.1 Misinformation and Disinformation: WHAT, HOW AND WHY

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1.2.A.2 Credibility of Online Sources – Elements that support/not support online sources credibility

1.2.A.2 Credibility of Online Sources – Elements that support/not support online sources credibility

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1.2.A.4 Misinformation, Disinformation and Bias in AI generated content

1.2.A.4 Misinformation, Disinformation and Bias in AI generated content

Information and Data Literacy

About this course

Competence Area

Information and Data Literacy

Competence

1.2 Evaluating data, information and digital content

Content Type

Youtubecourse

Last Updated

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Instructor

EDITC

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What you'll learn

In this video, we explore how AI algorithms shape online content by prioritizing engagement over accuracy, often promoting commercial or political messages. Learn how filter bubbles reinforce existing beliefs, how sponsored content blends with organic results, and how AI-driven personalization can limit diverse perspectives or manipulate consumer behavior. Discover tips to navigate these influences: seek alternative viewpoints, identify sponsored posts, and verify information with fact-checking sources to ensure a balanced, informed digital experience.

Learning outcome

1.2.9 Recognise that AI algorithms might not be configured to provide only the information that the user wants; they might also embody a commercial or political message

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