BY ELENA COX, eCampus News
Artificial intelligence’s potential to reduce human error and to scale human expertise is worth understanding. We can also measure inspired ideas and expertise by administration, faculty, advisors, coaches, and others for correlation to individual success and evidence of performance at scale. We have found variables in the output that are low- to no-cost to test in control trials and then at scale. This combination of actionable data, extracted with precision, and affordable practices that work at scale is the powerful promise of AI to education. Realizing this promise depends on human intelligence and discipline around data practices. With dialogue about AI and ML becoming pervasive, and often surrounded by excitement, it is important that everyone in this sector gain a basic understanding and language on this subject. Otherwise, this dialogue can become another hyperbole.
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