The increasing popularity of generative AI models has brought many ethical concerns along with it. Bias, reliability, environmental impact, intellectual effects, and humanitarian impacts are important considerations for ethical AI use.
Check out the tabs above for open access articles and resources related to specific ethical concerns.
Other AI ethics resources:
Output generated by AI tools is inevitably biased in nature because the content that AI models are trained on is biased. Bias may be explicit or implicit, and can focus on gender, racial, socioeconomic, or other biases or outdated stereotypes.
Below are some open access articles regarding bias in AI:
We know that AI models are trained on existing materials, but where exactly did this output come from? Can you tell? It's often not clear where information comes from, and provided citations are frequently incorrect in a number of ways.
Below are some open access articles related to AI reliability:
Is it safe to use generative AI for your assignment? The flowchart below is a good start to thinking through whether using AI is safe:
Safe to Use Generative AI figure by L. Schmidt. Adapted from "Is it safe to use ChatGPT for your task?" by Aleksandr Tiulkanov. CC-BY.
The environmental impact of AI models is significant, this resource-intensive technology is one that is ever-updating. Substantial power and water requirements, carbon-dioxide emissions, and a growing carbon footprint are all ongoing concerns.
Below are some open access articles regarding AI's environmental impact:
Does using AI harm our ability to think critically? In addition to concerns about bias, reliability, and environmental impact, scholars are also considering the impact AI is having on humans at personal, intellectual, and societal levels.
Below are some open access articles related to intellectual, humanitarian, and other ethical concerns:
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