### Q1: What is one easy way to identify bias in AI systems used within AEC projects?  
### Q2: How can you assess the transparency of AI-generated recommendations in your construction projects?  
### Q3: What is a complex method to ensure accountability for AI-driven decisions in the AEC sector?  
### Q4: How can low-code platforms help in mitigating bias when developing AI solutions in architecture?  
### Q5: What are the business implications of promoting transparency in AI technologies for client trust in the AEC industry?  
### Q6: How can mixed approaches in AI deployment address accountability issues in construction projects?  
### Q7: Why is it important to communicate the potential biases present in AI systems to stakeholders?  
### Q8: How can effective communication enhance transparency in the use of AI technologies among AEC professionals?  
### Q9: What are some challenges of communicating accountability measures for AI-driven decisions to your team?