用于研究的生成人工智能
Generative AI is rapidly transforming the landscape of academic research, creating new opportunities for discovery and innovation. 然而, as we leverage cutting-edge technology for research, it is crucial to remain mindful of ethical considerations, 隐私问题, and authorship issues associated with Generative AI. 在这一页, we collect 信息 about Generative AI 工具 for research, 包括用例, 限制, 使用指南, 工具, 和更多的.
The use cases for AI in research include:
- 头脑风暴的想法
Chatbots based on LLMs, such as Chat GPT, 双子座, MS Copilot, 困惑.ai, 和其他人, can help you brainstorm ideas for starting or continuing a project of any scale. 一些聊天机器人, 比如引起, are specifically trained on academic texts, and therefore may be more likely with ideas of higher scholarly value. - Building your list of references and getting started on your literature review
Tools based on neural networks such as Google Scholar, 研究Rabbit, 和其他人, can help you identify relevant papers, 文章, 和书籍. Many LLM-based chatbots (see above) can summarize the contents of pdf documents with high accuracy and answer questions about them. Do not upload documents into AI 工具 unless they are publicly available. - 学术写作
While we advise against uploading your entire pieces of work into chatbots due to authorship and 隐私问题, LLMs can help you edit specific spots in your writing that you are unsure about. Specific tasks include rephrasing awkward or ambiguous sentences, 检查语法, and brainstorming culturally sensitive ways to express an idea. - 展示你的作品
AI 工具 can help with titles, summaries, slides, and bullet points.
目前, 十大博彩推荐排名州立大学 does not have a contract with any generative AI 工具 or services. 因此, all such 工具 should be treated as third-party applications, with only Public data allowed to go into them (Data Security Classifications at Montclair)
- 幻觉. 文本的AI生成器, 图片, and video content can emulate human language, 创作, 行为非常接近. 然而,, the neural networks behind them do not have the same kind of knowledge about the world as humans have. 特别是, AI 工具 of most kinds are prone to hallucinations: they generate content that is plausible, 但事实并非如此，也不准确. Ethical use of most AI 工具 will include human verification and refining.
- 偏见. AI 工具 can inherit and amplify the biases of the real world we live in. Since content generators operate based on probabilities, they are more likely to catch content that is better represented in the public knowledge domain, and less likely to include content that is already underrepresented. When you use AI 工具 for research, be mindful of the perspectives and sources AI may have left out.
- 作者的担忧. There is no legal guidance as to who owns AI-generated content. To keep your ideas and work safe (or safer, 无论如何), do not feed your unpublished pieces into any third-party 工具. Authorship issues may be particularly worrisome when authors use text generators for editing help. While the input text still belongs to the author, the output you receive could count as open source or the intellectual property of the owner company — no matter how slight the edits.
- 隐私问题. No private data, personal or institutional, should go into any third-party 工具. See above (“What kind of data can I use with AI 工具”) for data privacy guidance.
- Variety of perspectives and AI etiquette. Scholars have vastly different perspectives on AI: while some embrace it, others feel uncertain. 如果你是研究团队的一员, it is important to obtain everyone’s consent before integrating any additional 工具 into your research.
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Third-party content is not covered under the Creative Commons license and may be subject to additional intellectual property notices, 信息, 或限制. You are solely responsible for obtaining permission to use third-party content or determining whether your use is fair use and for responding to any claims that may arise.