Using AI for Research
How to use AI for research: Practical tips for responsible use
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How to use GenAI for research (responsibly)
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How to use AI for research: Practical tips for responsible use
Hello Superstar!
By this point, you’ve probably already heard all about how GenAI is being misused in the workplace and at school: “personal” essays composed entirely by ChatGPT, AI-assisted reports with non-existent citations, CV and resumes built with Chat GPT without editing to adapt, employment emails sent without reviewing and so on. Browse your feed on any given day, and there’s likely no shortage of GenAI missteps to find, causing many to wonder whether it really is possible to incorporate this technology responsibly into the research process at all. If you follow us online, you will see how we come begging people to please use AI responsibly.
Whether you’re a student, working professional, or educator, there’s likely something for you here. So, without further ado, let’s get into it.
How to use GenAI for research (responsibly)
Research is a relatively complex process. It involves not only gathering information, but also formulating research questions and hypotheses, analyzing data, verifying sources, reviewing literature, and designing research approaches and experiments (among other things). In turn, research is an undertaking that scales in complexity in proportion to the questions you ask and seek to answer.
You can’t quite rely on LLMs to independently manage all your research tasks. Fortunately, regardless of what kind of research you’re conducting, there are many ways you can leverage GenAI to streamline and support your workflow. Here are some ways you can– responsibly–use generative AI to boost your research process:
Brainstorm and refine research questions: Due to their conversational abilities, LLMs like Microsoft Copilot and Google Gemini can be helpful sounding boards to bounce ideas off of when you’re first formulating your research questions or designing an experiment.
Surface scholarly articles: Some GenAI-powered research tools, such as Connected Papers or Research Rabbit, can map out relationships between papers, making it easier to find articles related to your research topic.
Clarify tricky concepts: Unsure if you fully understand a certain concept you’ve encountered in your research? Try asking ChatGPT to clarify it for you.
Cursory data analysis: You can use GenAI to conduct a quick, cursory analysis of your data to get a general idea of what it’s revealing. This may be particularly useful when performing a sentiment analysis on unstructured data like social media posts or product reviews.
Constructive criticism: Receiving feedback is critical to the research process. When you lack a human to review your work, though, you might consider interfacing with an LLM to identify any counterarguments, topic gaps, or opportunities for improvement.
PSA: Verify, verify, verify!⚠️
Generative AI is best when it supports your workflow rather than replaces it. This is particularly true when you’re conducting research, because while GenAI can augment many of the steps throughout the process, it can’t actually do them reliably. In fact, in some instances, GenAI may simply make up information, events, or sources that don’t even exist. Plus, in some cases, it may actually confirm certain biases rather than rigorously challenging them.
Put simply: While there’s a place for GenAI in the research process, it’s not a replacement for critical thought, so make sure to verify all of its claims thoroughly before accepting them as fact.
Generative AI is transforming how we work. Build the skills you need to support your research workflow and boost your productivity.
And that’s all we’ve got for this week, friends! Before diving back into your literature review, consider dropping a comment to let us know how you use GenAI to boost your research process. Until next time!
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