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Reframing Our Relationship with Language Models
The core utility of an LLM lies in its ability to generate language quickly and in context. It excels at tasks like drafting outlines, rephrasing sentences, or proposing different ways to frame a question. But the output should always be seen as a first step—never the final word.
In the Shadow of the Machine: Large Language Models and the Future of Human Thought
Large Language Models (LLMs), which now support a broad range of tasks from automated writing and analysis to education and creative ideation. These tools, once experimental, are now embedded in workflows across sectors. Their influence is undeniable. But their role must be critically examined.
The Misinformation Mirror: How AI Amplifies What We Already Believe
We see a similar pattern outside of science. In education, hiring, healthcare, and media. Algorithms are constantly trained to reward engagement, not accuracy. They learn which ideas get clicks, which phrases get shared, which language feels persuasive. Over time, those patterns become predictive rules.
That is how bias becomes baseline.
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