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Table 6 Summary of the boundaries beyond which AI systems are perceived as invasive, and their potential solutions

From: The impact of artificial intelligence on learner–instructor interaction in online learning

Factor of learner–instructor interaction Boundary beyond which AI systems are perceived as invasive Potential solution
Communication Responsibility issues that could arise when AI driven decisions lead to negative consequences Human-understandable justifications for the AI’s output or procedures (i.e., explainability)
Support Over-standardizing the learning process by prescribing how an engaged student should act Bring students and instructors into the decision-making loop and try to inform them of the decision-making context (i.e., human-in-the-loop); make decisions flexible, support multiple paths to success; be more careful about high-stakes decisions
Presence Uncomfortable with the measurement of their unconscious behavior, such as facial expression analysis or eye tracking, as it feels like surveillance Establishing clear, simple, and transparent data norms about the nature of data being collected from students and what kind of data is okay to be presented to instructors; maintain agency and provide an effective process of consent for data sharing