Don Ihde and Lambros Malafouris (Philosophy and Technology 32:195–214, 2019) have argued that “we are homo faber not just because we make things but also because we are made by them.” The emphasis falls on the idea that the things that we create, use, rely on that is, those things with which we engage have a recursive effect on human existence. We make things, but we also make arrangements, many of which are long-standing, material, social, normative, economic, institutional, and/or political, and many of which are supported by various technologies, including AI, more and more. Critical theorists, such as Habermas, have argued that we need a “depth” or critical hermeneutics (one that combines hermeneutical understanding with scientific explanation) to provide a full account of this kind of recursivity. For Habermas, the explanatory aspect of critical hermeneutics has been modeled on neo-Marxist and neo-Freudian theories. We propose a new critical hermeneutical approach that u
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This chapter questions the causal-constitution fallacy raised against the extended mind. It does so by presenting our signature temporal thesis about how to understand constitutive relations in the context of the extended mind, and with respect to dynamical systems, more broadly. We call this thesis diachronic constitution. We will argue that temporalising the constitution relation is not as remarkable (nor problematic) as it might initially seem. It is (arguably) inevitable, given local interactions between microscale and macroscale states of (coupled) dynamical systems. We focus primarily on the metaphysics of the extended mind in this paper. However, we also show how our account of diachronic constitution has important implications for the metaphysics of dependence relations more generally as well as an emerging literature on inter-level explanations in the mechanistic framework applied to the discussion over extended, enactive and embodied cognition.
In this blog we discuss how the transformer architecture naturally extends over external memories, and share empirical results which leverage this capability. These methods are innate (don’t require fine tuning) and outperform popular retrieval augmented generation methods.