“Deep Research”: A Research Paradigm Shift
While keeping pace with the new developments in generative AI and LLM reasoning models is in itself a challenge, new ‘deep research’ agents are beginning to surface at a remarkably rapid rate.
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While keeping pace with the new developments in generative AI and LLM reasoning models is in itself a challenge, new ‘deep research’ agents are beginning to surface at a remarkably rapid rate.
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One of the concerns is that Generative AI’s output in response to user prompts often draws from copyrighted works, eliciting a question nowadays: Can the content created by Generative AI qualify for copyright protection itself? Here, we strive to extend our insights into the question.
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The emergence of generative AI and Large Language Models (LLMs) has sparked heated discussions around their ethical usage. The stakes are higher when it comes to the ethical use of generative AI in high schools. High schoolers are the next generation’s decision-makers, and educating them on ethical generative AI use in academia is crucial.
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Information science is well-positioned to lead and critically inform the development of theoretical and technological frameworks that support information integrity and academic integrity. If we agree with the argument that generative AI tools and technologies share such high-level facets as people, information, data, technology, and their interaction with information science, then it is our responsibility to embrace the opportunities and address the emerging informational, social, ethical, and cultural challenges.
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