Privitera Adam John, Ng Siew Hiang Sally, Kong Anthony Pak-Hin, Weekes Brendan Stuart
Centre for Research and Development in Learning, Nanyang Technological University, Singapore 637335, Singapore.
Institute for Pedagogical Innovation, Research, and Excellence, Nanyang Technological University, Singapore 637335, Singapore.
Brain Sci. 2024 Apr 16;14(4):383. doi: 10.3390/brainsci14040383.
Aphasiology has a long and rich tradition of contributing to understanding how culture, language, and social environment contribute to brain development and function. Recent breakthroughs in AI can transform the role of aphasiology in the digital age by leveraging speech data in all languages to model how damage to specific brain regions impacts linguistic universals such as grammar. These tools, including generative AI (ChatGPT) and natural language processing (NLP) models, could also inform practitioners working with clinical populations in the assessment and treatment of aphasia using AI-based interventions such as personalized therapy and adaptive platforms. Although these possibilities have generated enthusiasm in aphasiology, a rigorous interrogation of their limitations is necessary before AI is integrated into practice. We explain the history and first principles of reciprocity between AI and aphasiology, highlighting how lesioning neural networks opened the black box of cognitive neurolinguistic processing. We then argue that when more data from aphasia across languages become digitized and available online, deep learning will reveal hitherto unreported patterns of language processing of theoretical interest for aphasiologists. We also anticipate some problems using AI, including language biases, cultural, ethical, and scientific limitations, a misrepresentation of marginalized languages, and a lack of rigorous validation of tools. However, as these challenges are met with better governance, AI could have an equitable impact.
失语症学在理解文化、语言和社会环境如何影响大脑发育及功能方面有着悠久而丰富的传统。人工智能领域的最新突破能够通过利用所有语言的语音数据来模拟特定脑区损伤如何影响诸如语法等语言共性,从而改变失语症学在数字时代的作用。这些工具,包括生成式人工智能(ChatGPT)和自然语言处理(NLP)模型,也能够为治疗临床患者的从业者在使用基于人工智能的干预措施(如个性化治疗和自适应平台)评估和治疗失语症方面提供参考。尽管这些可能性在失语症学领域引发了热情,但在将人工智能整合到实践之前,对其局限性进行严格审视是必要的。我们解释了人工智能与失语症学之间相互作用的历史和首要原则,强调了对神经网络进行损伤研究如何打开了认知神经语言学处理的黑匣子。然后我们认为,当来自更多语言的失语症数据被数字化并在线可用时,深度学习将揭示迄今未被报道的、对失语症学家具有理论意义的语言处理模式。我们还预测了使用人工智能时会出现的一些问题,包括语言偏见、文化、伦理和科学局限性、对边缘化语言的错误呈现以及工具缺乏严格验证。然而,随着通过更好的治理应对这些挑战,人工智能可能会产生公平的影响。