AI Thinking as a Meaning-Centered Framework: Reimagining Language Technologies Through Community Agency

• URL: http://arxiv.org/abs/2502.14923v1
• Date: Wed, 19 Feb 2025 18:09:24 GMT
• Title: AI Thinking as a Meaning-Centered Framework: Reimagining Language Technologies Through Community Agency
• Authors: Jose F Quesada,
• Abstract summary: AI Thinking proposes a meaning-centered framework that would transform technological development.<n>It recognizes that meaningful solutions emerge through the interplay of cultural understanding, community agency, and technological innovation.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: While language technologies have advanced significantly, current approaches fail to address the complex sociocultural dimensions of linguistic preservation. AI Thinking proposes a meaning-centered framework that would transform technological development from creating tools FOR communities to co-creating solutions WITH them. This approach recognizes that meaningful solutions emerge through the interplay of cultural understanding, community agency, and technological innovation. The proposal articulates a holistic methodology and a five-layer technological ecosystem where communities maintain control over their linguistic and cultural knowledge representation. This systematic integration of community needs, cultural preservation, and advanced capabilities could revolutionize how we approach linguistic diversity preservation in the digital age.

Related papers

• Towards deployment-centric multimodal AI beyond vision and language [67.02589156099391]
  We advocate a deployment-centric workflow that incorporates deployment constraints early to reduce the likelihood of undeployable solutions. We identify common multimodal-AI-specific challenges shared across disciplines and examine three real-world use cases. By fostering multidisciplinary dialogue and open research practices, our community can accelerate deployment-centric development for broad societal impact.
  arXiv  Detail & Related papers  (2025-04-04T17:20:05Z)
• Preserving Cultural Identity with Context-Aware Translation Through Multi-Agent AI Systems [0.4218593777811082]
  Language is a cornerstone of cultural identity, yet globalization and the dominance of major languages have placed nearly 3,000 languages at risk of extinction. Existing AI-driven translation models prioritize efficiency but often fail to capture cultural nuances, idiomatic expressions, and historical significance. We propose a multi-agent AI framework designed for culturally adaptive translation in underserved language communities.
  arXiv  Detail & Related papers  (2025-03-05T06:43:59Z)
• A hybrid marketplace of ideas [0.0]
  We argue that within the Web3 community on the social media platform X, AI agents challenge traditional notions of participation and influence in public discourse.<n>We examine the current state of AI agents in idea generation, propagation, and engagement, positioning their role as cultural agents through the lens of memetics.
  arXiv  Detail & Related papers  (2025-01-03T22:53:43Z)
• LIMBA: An Open-Source Framework for the Preservation and Valorization of Low-Resource Languages using Generative Models [62.47865866398233]
  This white paper proposes a framework to generate linguistic tools for low-resource languages. By addressing the data scarcity that hinders intelligent applications for such languages, we contribute to promoting linguistic diversity.
  arXiv  Detail & Related papers  (2024-11-20T16:59:41Z)
• Layers of technology in pluriversal design. Decolonising language technology with the LiveLanguage initiative [9.063726739562227]
  This paper uses LiveLanguage, a lexical database, as an example to discuss and close the gap from pluriversal design theory to practice. The paper presents a model comprising of five layers of technological activity.
  arXiv  Detail & Related papers  (2024-05-02T23:52:39Z)
• Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions [67.60397632819202]
  Building socially-intelligent AI agents (Social-AI) is a multidisciplinary, multimodal research goal. We identify a set of underlying technical challenges and open questions for researchers across computing communities to advance Social-AI.
  arXiv  Detail & Related papers  (2024-04-17T02:57:42Z)
• Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking [48.21982147529661]
  This paper introduces a novel approach for massively multicultural knowledge acquisition. Our method strategically navigates from densely informative Wikipedia documents on cultural topics to an extensive network of linked pages. Our work marks an important step towards deeper understanding and bridging the gaps of cultural disparities in AI.
  arXiv  Detail & Related papers  (2024-02-14T18:16:54Z)
• Towards Bridging the Digital Language Divide [4.234367850767171]
  multilingual language processing systems often exhibit a hardwired, yet usually involuntary and hidden representational preference towards certain languages. We show that biased technology is often the result of research and development methodologies that do not do justice to the complexity of the languages being represented. We present a new initiative that aims at reducing linguistic bias through both technological design and methodology.
  arXiv  Detail & Related papers  (2023-07-25T10:53:20Z)
• MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning [50.40151403246205]
  Huge language models (LMs) have ushered in a new era for AI, serving as a gateway to natural-language-based knowledge tasks. We define a flexible architecture with multiple neural models, complemented by discrete knowledge and reasoning modules. We describe this neuro-symbolic architecture, dubbed the Modular Reasoning, Knowledge and Language (MRKL) system.
  arXiv  Detail & Related papers  (2022-05-01T11:01:28Z)
• Systematic Inequalities in Language Technology Performance across the World's Languages [94.65681336393425]
  We introduce a framework for estimating the global utility of language technologies. Our analyses involve the field at large, but also more in-depth studies on both user-facing technologies and more linguistic NLP tasks.
  arXiv  Detail & Related papers  (2021-10-13T14:03:07Z)
• Anticipation Next -- System-sensitive technology development and integration in work contexts [0.0]
  This explorative work uses existing literature from the adjoining research fields of system theory, organizational theory, and socio-technical research to combine various concepts. We suggest a conceptual framework that is supposed to be used in very early stages of technology development and integration for and in work contexts.
  arXiv  Detail & Related papers  (2021-03-01T11:27:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.