https://speakerdeck.com/anike 2026-09-11 15:31:20 -0400 AI detection is increasingly used in education, publishing, research, and professional writing, but an AI score is not direct proof of authorship. This research presentation examines AI detection accuracy in 2026, including false positives, false negatives, AI-score interpretation, classification thresholds, multilingual detection, human–AI hybrid writing, and the reasons different AI detectors can produce different results from identical text. The presentation also explains why headline accuracy alone can be misleading, how precision and recall affect detector performance, and why high-stakes decisions should combine automated detection with contextual evidence and human review. AI detection is increasingly used in education, publishing, research, and professional writing, but an AI score is not direct proof of authorship. This research presentation examines AI detection accuracy in 2026, including false positives, false negatives, AI-score interpretation, classification thresholds, multilingual detection, human–AI hybrid writing, and the reasons different AI detectors can produce different results from identical text. The presentation also explains why headline accuracy alone can be misleading, how precision and recall affect detector performance, and why high-stakes decisions should combine automated detection with contextual evidence and human review. Fri, 11 Sep 2026 00:00:00 -0400 https://speakerdeck.com/anike/ai-detection-accuracy-in-2026-false-positives-ai-scores-and-the-human-ai-classification-problem https://speakerdeck.com/anike/ai-detection-accuracy-in-2026-false-positives-ai-scores-and-the-human-ai-classification-problem