Education - Learning
In contrast to traditional machine learning, the impact of generative AI in the educational sector receives considerable attention in the academic literature. Next to issues stemming from difficulties to distinguish student-generated from AI-generated content, which eventuates in various opportunities to cheat in online or written exams, sources emphasize the potential benefits of generative AI in enhancing learning and teaching methods, particularly in relation to personalized learning approaches. However, some papers suggest that generative AI might lead to reduced effort or laziness among learners. Additionally, a significant focus in the literature is on the promotion of literacy and education about generative AI systems themselves, such as by teaching prompt engineering techniques.
ENTITY
1 - Human
INTENT
1 - Intentional
TIMING
2 - Post-deployment
Risk ID
mit77
Domain lineage
4. Malicious Actors & Misuse
4.3 > Fraud, scams, and targeted manipulation
Mitigation strategy
1. **Establish and Enforce a Comprehensive AI Academic Integrity Framework**: Develop and clearly communicate detailed policies regarding the permissible use of generative AI tools within the curriculum and on specific assignments, requiring explicit attribution and verification. Assignments should be redesigned to be 'AI-resilient' by prioritizing higher-order cognitive tasks (e.g., analysis, evaluation, creation) and requiring authentic, personalized, or oral defenses of submitted work to mitigate opportunities for cheating and submission of unverified AI-generated content. 2. **Integrate Pedagogical Safeguards to Preserve Learning and Mitigate Over-Reliance**: Employ instructional scaffolding and iterative learning design to break down complex tasks, providing regular, constructive feedback throughout the process. When AI tools are integrated, implement protective guardrails, such as configuring AI tutors to provide only teacher-designed hints rather than direct answers, thereby fostering intrinsic motivation and preventing students from using the technology as a crutch during critical skill-building phases. 3. **Cultivate Generative AI Literacy and Responsible Use Capacity**: Introduce formal education for all stakeholders on the capabilities, limitations, and ethical considerations of generative AI systems. This should include training in prompt engineering techniques to equip both educators and students with the ability to effectively and responsibly utilize LLMs to enhance learning, personalize content, and automate administrative tasks in service of educational goals.