在谈论心智阅读技术时的权利和错误
1Philosophy and Ethics of Technology Section, TU Delft, Delft, The Netherlands.
概括
应用于大脑数据的大型语言模型 (LLM) 显示了对间接重建心理内容的前景. 这种以技术为媒介的方法不同于真正的心智阅读,但为语音康复提供了潜在的潜力.
科学领域:
- 神经科学和人工智能 人工智能
- 认知科学 认知科学
- 计算语言学 计算语言学
背景情况:
- 新兴研究探讨了大语言模型 (LLM) 对大脑数据的应用.
- 初步发现表明,LLM可以从神经信号中重建心理内容.
- 法学士处理的性质及其与自然语言的关系需要仔细研究.
研究的目的:
- 批判性地评估声称LLM能够从大脑数据中直接阅读思想的说法.
- 区分LLM数据转换与自然语言的理性基础.
- 探索基于LLM的大脑数据处理的潜在应用.
主要方法:
- 分析大型语言模型 (LLM) 的架构和功能.
- 将LLM数据处理与自然语言的特征进行比较.
- 检查涉及LLM应用到大脑数据的实验结果.
主要成果:
- 法律学通过非理性转换来处理数据,这些转换是基于庞大的文本体.
- 自然语言具有基于理由的理性维度,与LLM操作不同.
- 大脑数据,当由LLMs处理时,允许间接预测心理内容,而不是直接重建.
结论:
- 目前LLM对大脑数据的应用并不构成技术介导的心智阅读.
- 这些发现代表了大脑数据处理的令人印象深刻的进步.
- 基于LLM的大脑数据处理对语音康复和新型沟通方法具有重大前景.
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