Machine bots work based on a system of data input, practice with the data, and then exposure to new data. This new data is evaluated to make designs or predictions based on the AI’s training with the original data. If we want the bot to be more precise or advanced, there must be more data for the bot to work with. Since humans are inputting the original data for a bot, there is a chance for bias within the tool. Individuals working with AI must be thoughtful in their approach and outcomes, deciding if more data needs to be provided, or if the wrong data is contributing to unintended bias in the AI results.
I am amazed by the ease and time-saving abilities of Khanmigo. I had already explored a little bit of the tool after being introduced to it in the previous videos of this series. Diving into class snapshot, I can immediately see the benefits. Immediate data, individualized reports on students, and the ability to communicate swiftly with parents are just a few of the benefits Khanmigo provides. I have no doubt that AI assistance and AI tutors in the classroom will help close the learning gap in education and decrease teacher burnout!
I am amazed by the ease and time-saving abilities of Khanmigo. I had already explored a little bit of the tool after being introduced to it in the previous videos of this series. Diving into class snapshot, I can immediately see the benefits. Immediate data, individualized reports on students, and the ability to communicate swiftly with parents are just a few of the benefits Khanmigo provides. I have no doubt that AI assistance and AI tutors in the classroom will help close the learning gap in education and decrease teacher burnout!