Despite massive investments and widespread hype around artificial intelligence, the technology has delivered zero financial payoff to corporate America outside of tech. Subscribe for daily updates.
when you use AI, its going to hallucinate, it might even make up results at worst, and not cite the SOURCES correctly, very important a research paper, if its summarizing from different sources, (it will be kinda hard to parse all that info). in a science paper, when you cite a source you have to do like a superscript like 1 denoting the order of the sources you got it from. it gets messy when someone calls out your paper, and they get the publisher/you to retract it.
This was true a year ago but most state of the art models are rather good at citing sources now. Haven’t had any issues with my papers so far which was not the case last year.
Only thing I have noticed now is that sometimes understanding the source is a different story. It will get the gist but lacks nuance written in the source present in the paper. But the papers exist at least when it refers to papers in my field.
Because research requires precision. To do background reading, I have to throw out everything that isn’t relevant to my particular study. My study is new, so the main driver is my concept of what I want to do. The AI is good at finding things with the same keywords, but not at excluding what isn’t relevant to my thought process.
I use Google Scholar for searching for literature. I put in some keywords, then scan through the titles. Most of them are not relevant, but I can click through hundreds of titles in a few minutes to focus my attention where it matters, then use the references/citations of those papers to build out what I need to focus on.
AI will give me a massive block of text that includes 5-6 references, with long explanations of what each is about. It is an attempt to do the same thing, but I have to throw out most or all of them, re-prompt, and then get another similar answer. Sometimes it throws things out that aren’t peer reviewed.
It also loses the happenstance of stumbling on something irrelevant but important. That’s why I still look at the monthly journal publication lists to see what is happening.
Writing is similar. I need to condense several peer reviewed papers to the core ideas that are relevant to what I am saying, which might mean 1-2 sentences. AI will always give paragraphs that are not really getting to what I want, so I still have to do the work myself anyway. It is just adding steps to do the same process.
Interesting this is different than my experience with it. I find that it removes the process of understanding and as such it feels empty or vapid. It has helped me finding papers that I would not have found because google offers a bubble in scholar that I cannot get removed from.
Can you elaborate on this? What does not help for research you reckon?
when you use AI, its going to hallucinate, it might even make up results at worst, and not cite the SOURCES correctly, very important a research paper, if its summarizing from different sources, (it will be kinda hard to parse all that info). in a science paper, when you cite a source you have to do like a superscript like 1 denoting the order of the sources you got it from. it gets messy when someone calls out your paper, and they get the publisher/you to retract it.
This was true a year ago but most state of the art models are rather good at citing sources now. Haven’t had any issues with my papers so far which was not the case last year.
Only thing I have noticed now is that sometimes understanding the source is a different story. It will get the gist but lacks nuance written in the source present in the paper. But the papers exist at least when it refers to papers in my field.
Because research requires precision. To do background reading, I have to throw out everything that isn’t relevant to my particular study. My study is new, so the main driver is my concept of what I want to do. The AI is good at finding things with the same keywords, but not at excluding what isn’t relevant to my thought process.
I use Google Scholar for searching for literature. I put in some keywords, then scan through the titles. Most of them are not relevant, but I can click through hundreds of titles in a few minutes to focus my attention where it matters, then use the references/citations of those papers to build out what I need to focus on.
AI will give me a massive block of text that includes 5-6 references, with long explanations of what each is about. It is an attempt to do the same thing, but I have to throw out most or all of them, re-prompt, and then get another similar answer. Sometimes it throws things out that aren’t peer reviewed.
It also loses the happenstance of stumbling on something irrelevant but important. That’s why I still look at the monthly journal publication lists to see what is happening.
Writing is similar. I need to condense several peer reviewed papers to the core ideas that are relevant to what I am saying, which might mean 1-2 sentences. AI will always give paragraphs that are not really getting to what I want, so I still have to do the work myself anyway. It is just adding steps to do the same process.
Interesting this is different than my experience with it. I find that it removes the process of understanding and as such it feels empty or vapid. It has helped me finding papers that I would not have found because google offers a bubble in scholar that I cannot get removed from.
I believe it evolved from search engine algorithms, and so honestly this is probably one of the few helpful uses of AI.
Still ignores the ethics, but hey at least it isnt all smoke and mirrors