1. What are AI Fictions?...
Sometimes AI systems can confidently produce text that sounds very real but is actually not true. AI systems don't have a true understanding of what they're saying like humans do. So they often can't tell when they're making a mistake. They're certain that their responses are right, even if they're wrong! So again, it's important to communicate this to students that AI isn't always correct. They were designed to be large language models, not knowledge models. This reminds me in how we used to communicate this to our students about Wikipedia. We need to teach our students how to be critical and skeptical thinkers and NOT to believe everything that they ask for and read from AI sources like ChatGPT. Healthy skepticism is a great mindset for our students to practice as they encounter more and more information on the Internet in school and at home, etc.
2. What is Algorithmic Bias?...
This refers to the systemic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. Some teaching strategies and practices that we can use to combat these biases and misinformation are the following... Like stated above, we can teach our students to exercise healthy skepticism and to be cautious when asking AI to generate information for them; to re-prompt AI when necessary if something sounds off, to reevaluate by asking if it's sure about the selected topic/subject; emphasizing and teaching digital literacy skills to our students, such as corroborating information, checking for bias, and evaluating the credibility (reliability- which we do with our SEQ's- we discuss audience, purpose, bias, and POV and how it affects the document's use as a reliable source of evidence) of their sources, etc.; getting more creative with assignments (more critical thinking assignments); and by using a variety of tools (different search engines)... Once again, it's all about having open and honest dialogue in our classes with our students; earlier in the year than later.
Sometimes AI systems can confidently produce text that sounds very real but is actually not true. AI systems don't have a true understanding of what they're saying like humans do. So they often can't tell when they're making a mistake. They're certain that their responses are right, even if they're wrong! So again, it's important to communicate this to students that AI isn't always correct. They were designed to be large language models, not knowledge models. This reminds me in how we used to communicate this to our students about Wikipedia. We need to teach our students how to be critical and skeptical thinkers and NOT to believe everything that they ask for and read from AI sources like ChatGPT. Healthy skepticism is a great mindset for our students to practice as they encounter more and more information on the Internet in school and at home, etc.
2. What is Algorithmic Bias?...
This refers to the systemic and repeatable errors in a computer system that create unfair outcomes, such as privileging one arbitrary group of users over others. Some teaching strategies and practices that we can use to combat these biases and misinformation are the following... Like stated above, we can teach our students to exercise healthy skepticism and to be cautious when asking AI to generate information for them; to re-prompt AI when necessary if something sounds off, to reevaluate by asking if it's sure about the selected topic/subject; emphasizing and teaching digital literacy skills to our students, such as corroborating information, checking for bias, and evaluating the credibility (reliability- which we do with our SEQ's- we discuss audience, purpose, bias, and POV and how it affects the document's use as a reliable source of evidence) of their sources, etc.; getting more creative with assignments (more critical thinking assignments); and by using a variety of tools (different search engines)... Once again, it's all about having open and honest dialogue in our classes with our students; earlier in the year than later.