I kind of feel like I haven't learned a lot - it's about careful judgement, which we already need and use in everyday teaching. It is interesting to see where the program leans on teachers to use AI in their classrooms, but reminds them that the liability for that use falls upon the person, not the program. I wonder how many individual teachers get to choose the system that the district uses for their program?

In short, I learned that AI cannot replace what a human teacher is able to do. We must continually assess and address AI output.

I understood the importance of when and how to disclose the use of AI. It's important to disclose that it was used as a tool and not a crutch.

I have learned to always be proactive in detecting bias whether the tell, team, or trust approach is being used.

It is important to model properly using AI as a tool to assist with your work and not a source of truth.

Fairness, accountability, transparency, and privacy must be purposefully incorporated into the use of AI technologies in professional and educational contexts in order to implement ethical AI practices. The first step is to critically assess AI-generated information to make sure it is accurate, free of prejudice, and compliant with industry standards. Before using any output, educators should make sure it is safe and compliant, particularly in technological fields. Additionally, transparency is crucial, which means that when and how AI is utilized to enhance instructional materials or decision-making, educators should correctly disclose. Additionally, a crucial ethical duty is to safeguard student data… >>>

I learned how important it is to understand disclosure levels and know when to reveal the use of AI in various educational and professional settings. Differentiating between direct content creation, collaborative use, and behind-the-scenes help is crucial since not all AI involvement calls for the same amount of explanation. While complete transparency is required in certain situations to uphold trust, academic integrity, and professional reputation, in others a brief acknowledgment of AI aid is acceptable. Additionally, I discovered that transparent disclosure guarantees that students and colleagues may critically assess the resources being used and helps avoid misunderstandings regarding authorship. In… >>>

I've discovered that bias must be identified and addressed because AI can be employed in manners that differ from its intended objective. AI systems may inadvertently reflect and magnify societal prejudices in their outputs since they learn from current data, particularly when producing recommendations or content.

Additionally, I've come to understand that not everyone has equal access to AI, which may contribute to educational and opportunity gaps and increase the impact of bias on students with little resources. In order to address these problems, AI outputs must be carefully assessed, patterns that might exclude or misrepresent particular groups must be… >>>

Main ethical concerns in AI include fairness, privacy, safety and accountability, & trust. 

Fairness is one of the main issues. AI systems may produce unfair or discriminating results if they reflect bias from the data they are trained on. These risks are lessened by ethical behavior.

Another important concern is privacy. Strong ethical norms are necessary to stop misuse and safeguard sensitive data because AI frequently uses vast volumes of personal data.

Safety and responsibility are also guaranteed by ethics. It is crucial to establish responsibility and create systems that put human welfare first because AI systems have the potential… >>>