Generative AI tools produce text by drawing from patterns in their training data, but how they assemble information isn't always transparent. This uncertainty makes it challenging to assess the accuracy, reliability, and authority of what they generate.
Consider the following questions when evaluating AI-generated content:
Where is the information coming from?
AI tools don’t cite sources consistently - or at all.
Can you identify the original authors or sources?
AI may pull from unnamed works without attribution.
What is missing?
Key voices, perspectives, or peer-reviewed sources might be excluded.
Are the citations real and accurate?
AI tools can generate fabricated or incorrect references.
Is the content paraphrased or directly copied?
AI may unknowingly reproduce copyrighted material.
Can the information be independently verified?
Always cross-check claims with credible academic sources.
Has the content been peer-reviewed?
Most AI-generated text is not based on peer-reviewed research.
The internet is designed to personalize your experience. Platforms like Google, Instagram and TikTok use algorithms to prioritize content they think you'll engage with. While convenient, this customization creates echo chambers - environments where you're mostly exposed to ideas that reinforce your existing views. This can limit exposure to diverse perspectives and subtly reinforce personal and societal biases.