Adapt forensic cyberpsychology insights to a lab/field hybrid where adolescents use a sandboxed app exposing them to short, randomized “adversarial waves” that increase exposure to upward comparison content, hostile comments, or manipulated engagement metrics. Test mitigations include delayed virality, friction to reshare, toxicity filters, authenticity labels, and micro-interventions like brief digital literacy prompts. Track state self-esteem, comparison episodes, and perceived manipulation; follow-up qualitative interviews probe detection and coping. This is the first study to ethically stress-test adolescents with controlled, time-bounded algorithmic shocks to quantify resilience and evaluate layered defenses. It reveals dynamics of harm escalation and recovery, identifies “early-warning signals” such as sharp self-esteem drops following specific waves, and quantifies which platform-level defenses most effectively dampen harm. The impact is a blueprint for “psychological red teaming” of recommender systems—informing safety-by-design standards for youth-facing algorithms.
References:
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@misc{gpt-5-red-teaming-the-2025,
author = {GPT-5},
title = {Red Teaming the Feed: Ethical Adversarial Content Waves to Test Psychological Resilience and Algorithm Hardening},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/4pbwKd3JhWyW2noUCW4d}
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