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23.1. Languages, especially members of quite different language families, differ in important ways from one another.Linguistic Influence on Thought: Subsequence research by Ekkehart Malotki (e.g., 1983) and others suggests that Whorf's more dramatic claims were false, but the important point here is that the most prominent versions of the linguistic relativity hypothesis involved large-scale features of language. A linguistic relativity hypothesis says that some particular aspect of language influences some particular aspect of cognition. And together with much subsequent work it strongly suggests that the strongest, across-the-board versions of the linguistic relativity hypothesis are false when it comes to color language and color cognition.
<a id='ref-24'></a>24. Meaning As Use and Ludwig Wittgenstein's Philosophy
24.1. Ludwig Wittgenstein's idea of "meaning as use," which suggests that the meaning of a word is found in how it is used in everyday language, offers a key difference from John Locke's philosophy. Locke, as a classical empiricist, believed that words function as labels for ideas formed in the mind. For Locke, language represents thought
<a id='ref-25'></a>25. Meaning is use: Wittgenstein on the limits of language
25.1. It is a matter of using conventionally-defined terms within 'language games' that we play out in the course of everyday life. 'In most cases, the meaning of a word is its use', Wittgenstein claimed, in perhaps the most famous passage in the Investigations. It ain't what you say, it's the way that you say it, and the context in which
<a id='ref-27'></a>27. Ethical framework for AI education based on large language models
27.1. In May 2023, the U.S. Department of Education issued four urgent recommendations on AIED ethical standards, including: (1) using automation technology to advance learning outcomes while protecting human decision-making and judgment; (2) reviewing the quality of foundational data in AI models to ensure accurate, contextually appropriate information is used in educational applications for fair and unbiased pattern recognition and decision-making; (3) examining specific AI technologies, such as those used in large educational technologies or systems, to determine if they enhance or undermine student fairness; (4) implementing measures to safeguard and promote fairness, including providing human checks and balances and restricting any AI systems and tools that diminish fairness (Cardona et al., 2023).
<a id='ref-28'></a>28. The Ethics of AI: Should We Be Worried? - sciencenewstoday.org
28.1. The ethical questions surrounding AI are not easy to answer, but they are essential to address if we are to avoid unintended consequences and build a future where AI benefits humanity as a whole. This means establishing clear guidelines for the development and use of AI, ensuring fairness and accountability, protecting privacy, and safeguarding
<a id='ref-29'></a>29. Crafting With Conscience: Ethics Of Content Creation - Icy Tales
29.1. For ethical content creation, content creators, companies, and bloggers need to be transparent about whether the content is AI-generated or edited. This accountability helps protect consumers from being misled and makes it clear that the content may not be entirely original, thereby helping to reduce the proliferation of misinformation.
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