Challenges and future directions for integration of large language models into socio-technical systems Article Swipe
Helma Torkamaan
,
Steffen Steinert
,
Maria Soledad Pera
,
Olya Kudina
,
Samuel Kernan Freire
,
Himanshu Verma
,
Sage Kelly
,
Marie-Therese Sekwenz
,
Jie Yang
,
Karolien van Nunen
,
Martijn Warnier
,
Frances Brazier
,
Óscar Oviedo-Trespalacios
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/0144929x.2024.2431068
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1080/0144929x.2024.2431068
Large Language Models (LLMs) are expected to significantly impact various socio-technical systems, offering transformative possibilities for improved interaction between humans and technology. However, their integration poses complex challenges due to the intricate interplay between societal structures, human behaviour, and technological innovation. This research explores these multifaceted challenges, emphasising the need for a human-centered approach in integrating LLMs to ensure that technological advancements are aligned with ethical standards and societal needs. Utilizing a structured methodology comprising a workshop, literature analysis, and expert collaborations, the study uses a multi-dimensional human-centered AI framework to guide the responsible integration of LLMs. Key insights include the importance of inclusive data, considering unintended consequences, maintaining privacy, and respecting intellectual property rights. The paper identifies and advocates for principles like human-in-the-loop, continuous longitudinal studies, proactive awareness campaigns, and regular audits to develop LLMs that are ethically sound, adaptable, and effectively integrated into various socio-technical systems, thus addressing user needs and broader societal impacts. The paper also underlines the importance of collaboration among academia, industry, and policymakers to develop LLMs that are ethically aligned, socially beneficial, and adaptable to future societal needs. The findings offer valuable insights into the strategic integration of LLMs, advocating for a broader research perspective beyond industrial motivations to fully understand and leverage LLMs in socio-technical landscapes.
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- Type
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- Language
- en
- Landing Page
- https://doi.org/10.1080/0144929x.2024.2431068
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Challenges and future directions for integration of large language models into socio-technical systemsWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-12-10Full publication date if available
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Helma Torkamaan, Steffen Steinert, Maria Soledad Pera, Olya Kudina, Samuel Kernan Freire, Himanshu Verma, Sage Kelly, Marie-Therese Sekwenz, Jie Yang, Karolien van Nunen, Martijn Warnier, Frances Brazier, Óscar Oviedo-TrespalaciosList of authors in order
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hybridOpen access status per OpenAlex
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