Name
When AI Gets Too Clever: Unmasking Dark Patterns in EdTech Platforms
Description

EdTech is undergoing a rapid transformation, with artificial intelligence powering everything from personalized learning journeys to automated grading, engagement tracking, and recommendation engines. While these technologies offer tremendous potential to improve education, they also open the door to new risks particularly when persuasive design, data-driven algorithms, and user psychology converge to create dark patterns.

This session takes a deep dive into how seemingly well-intended AI features can unintentionally manipulate user behavior in educational settings. From “recommended” content that narrows learning pathways to retention-focused nudges that favor screen time over student well-being, we’ll explore how subtle design decisions can have outsized effects on student autonomy and educator trust.

We’ll examine real-world case studies where AI-driven EdTech systems influenced decision-making, compromised data transparency, or undermined equitable access to learning resources often without users’ awareness. Special attention will be given to compliance with GDPR and ethical standards in design, particularly around consent, profiling, and the right to explanation.

Participants will walk away with:

1. A clear understanding of what constitutes a dark pattern in AI-powered education tools
2. Insights into how these patterns can erode trust and fairness in assessment
3. A practical framework for evaluating and improving the design of EdTech platforms
4. Tools to align product choices with the European vision for accessible, transparent, and ethical assessment for all

This session is designed for non-technical education leaders, policymakers, product owners, and assessment professionals who are responsible for choosing, implementing, or evaluating digital learning and assessment solutions. Whether you're in the process of deploying AI in your ecosystem or simply curious about emerging risks, this session will provide both insight and guidance to ensure that your approach to innovation is responsible, inclusive, and future-ready.

Session Type
Presentation
Session Area
Education, Security
Primary Topic
Candidate Experience