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Ethical Considerations

Ethical considerations with AI include issues like bias, data mining, plagiarism, or environmental issues.

 

Researching the ethical issues or asking critical questions of yourself or the AI platform before and while engaging with AI is crucial. For example: 

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  • To check for bias: You can ask AI models to give you statements from another perspective, and checking external sources can help illuminate misinformation.

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  • To check where the AI gathers its information: You should consider the sources it was trained on. Can you find details about how the AI has been taught, or if it can credit original authors?

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  • To check for corporate influence: What is the funding structure of the company that created the AI? What are their goals?

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Examples of Ethical Concerns

​Each example has a link to a source explaining more. However, further research is recommended for these issues and the many other potential concerns. 

 

Forming one's own opinion of these ethical concerns is essential for the critical consumption of AI.

Trees and Mountains
People Walking
Image by Chris Yang

AI Glossary

Understanding the terminology and functions of AI is essential to building and expanding your knowledge of artificial intelligence technologies and platforms.

 

Please check out this glossary for more information: 

Have questions? Found more recent ethical concerns or sources? 

Send us an email! 

As AI platforms continue to develop rapidly, the ethical considerations of these platforms will change.

 

We are committed to maintaining this resource by including relevant information and examples. We would appreciate suggestions for the upkeep of relevant ethical considerations.

Please fill out this contact us form or reach us at: criticalconsumptionresource@gmail.com

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