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gedankenstuecke ,
@gedankenstuecke@scholar.social avatar

Got this email earlier and I’m still upset about it. Some unnamed “team from , & ” fed our preprint through their “" to generate "suggestions" on how we could improve it.

This feels like some really shit study that seems to think asking for consent is optional. And like one that wants to spin out into an even shittier start-up in the future (hence not giving any names of team members)?

@academicchatter @hci

Screenshot of an email, reads: Hi there, Congratulations on your recent preprint on arXiv, titled "Co-Designing a wiki-based community knowledge management system for personal science". We are grateful for your hard work and dedication to the field, and we value your contributions! We are part of a team from Northwestern University, Stanford University, and Cornell University, committed to providing research feedback to scholars with the assistance of advance AI models. We have followed your work closely and, upon a thorough examination, generate the suggestions below. These suggestions cover various aspects of your work, including the writing style, research design, and title. We hope they offer you fresh insights that may enhance the depth and impact of your research. To view detailed comments regarding your research, please visit this link: http://feedback.kellogg.northwestern.edu/redacted Once again, congratulations on your achievement. We are certain that your work will have an impact on the future of your field and will inspire fellow researchers worldwide. Should you have any questions, concerns, or suggestions, please do not hesitate to reach out to us at redacted_address@outlook.com. Your insights would be invaluable in helping us better support the community's research development.
ALT
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    • gedankenstuecke OP ,
    @gedankenstuecke@scholar.social avatar

    @RangerRick @academicchatter @hci @tante the latter would be very on-brand though!

    ePD5qRxX ,
    @ePD5qRxX@mastodon.online avatar

    @RangerRick

    Or their lack of a sensible web server config...

    @gedankenstuecke @academicchatter @hci @tante

    ml ,
    @ml@ecoevo.social avatar

    Nothing says "We care about accessibility and equity for disabled people in STEM like 'Go to Google and let their AI handle it""

    @disability @academicchatter

    dingemansemark ,
    @dingemansemark@scholar.social avatar

    Maria Kuteeva and Marta Andersson on how LLMs perpetuate the status quo and hinder rather than help academic discourse https://academic.oup.com/applij/advance-article/doi/10.1093/applin/amae025/7641807 @academicchatter

    Research communities across disciplines recognize the need to diversify and decolonize knowledge. While artificial intelligence-supported large language models (LLMs) can help with access to knowledge generated in the Global North and demystify publication practices, they are still biased toward dominant norms and knowledge paradigms. LLMs lack agency, metacognition, knowledge of the local context, and understanding of how the human language works. These limitations raise doubts regarding their ability to develop the kind of rhetorical flexibility that is necessary for adapting writing to ever-changing contexts and demands. Thus, LLMs are likely to drive both language use and knowledge construction towards homogeneity and uniformity, reproducing already existing biases and structural inequalities. Since their output is based on shallow statistical associations, what these models are unable to achieve to the same extent as humans is linguistic creativity, particularly across languages, registers, and styles. This is the area where key stakeholders in academic publishing—authors, reviewers, and editors—have the upper hand, as our applied linguistics community strives to increase multilingual practices in knowledge production.
    ALT
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