Distinguish between automation of lower-order tasks and augmentation of critical thinking, while learning to identify student work demonstrating human agency versus AI dependency. 

Key Topics:  

1. Differentiating automation of lower-order academic tasks from augmentation of higher-order skills. 
2. Classifying student work: human agency versus sole reliance on GenAI output. 
3. Evaluating critical thinking demonstrated in student assignments. 
4. Core ethical principle of Human Agency in GenAI course integration. 
5. Preserving human agency when designing GenAI-integrated syllabi. 

Address bias, cultural integrity, and digital equity concerns when implementing GenAI in diverse educational contexts, particularly for Arabic language support. 

Key Topics: 

1. Determining which GenAI applications pose greatest risk for perpetuating bias.
2. Understanding bias against marginalized knowledge systems in AI outputs. 
3. Selecting effective faculty actions to promote cultural integrity of Arabic content. 
4. Addressing linguistic diversity in GenAI-generated educational materials. 
5. Matching digital poverty concerns to specific GenAI features (paywalls, hardware requirements). 

Examine UNESCO-recommended protection requirements and clarify stakeholder responsibilities for ethical GenAI adoption in Middle Eastern university contexts. 

Key Topics: 

1. Identifying three mandatory protection requirements for GenAI adoption (UNESCO recommendations). 
2. Understanding data privacy and ethical review requirements. 
3. Classifying institutional versus faculty responsibilities regarding GenAI. 
4. Distinguishing roles in policy development and curriculum integration. 
5. Determining urgent policy areas for Middle Eastern university contexts (Academic Integrity, Data Privacy, IT Infrastructure).