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Special considerations for the use of AI tools by PEERs as a learning and communication aid.
Arango, Maria Camila; Hincapié-Otero, María; Hardeman, Keisha; Shao, Bryanna; Starbird, Leo; Starbird, Chrystal.
Afiliação
  • Arango MC; Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Hincapié-Otero M; Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.
  • Hardeman K; Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Shao B; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA.
  • Starbird L; Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Starbird C; Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
J Cell Physiol ; 239(7): e31339, 2024 Jul.
Article em En | MEDLINE | ID: mdl-38924572
ABSTRACT
There is no doubt that navigating academia is a formidable challenge, particularly for those from underrepresented backgrounds who face additional barriers at every turn. In such an environment, efforts to create learning and training environments that are diverse, equitable, and inclusive can feel like an uphill battle. We believe that harnessing the power of artificial intelligence (AI) tools can help in leveling the playing field. While AI cannot supplant the need for supportive mentorship, it can serve as a vital supplement, offering guidance and assistance to those who may lack access to adequate avenues of support. Embracing AI in this context should not be stigmatized, as it may represent a vital lifeline for underrepresented individuals who often face systemic biases while forging their own paths in pursuit of success and belonging in academia. AI tools should not be gatekept from these individuals, particularly by those in positions of power and privilege within the scientific community. Instead, we argue, institutions should make a strong commitment to educating their community members on how to ethically harness these tools.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizagem Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizagem Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article