This paper proposes epistemic environmentalism as a novel framework for accounting for the contribution of the environment – broadly construed – to epistemic standings and which can be used to improve or protect epistemic environments. The contribution of the environment to epistemic standings is explained through recent developments in epistemology and cognitive science, including embodied cognition, embedded cognition, extended cognition and distributed cognition. The paper examines how these developments support epistemic environmentalism, as well as contributes theoretical resources to make epistemic (...) assessments of dynamic environments. The epistemic environmentalist procedure from the assessment of an individual environment to changes made to that environment based on promoting the attainment of epistemic goods is also discussed. (shrink)

A recent interpretation of artificial intelligence (AI) (Floridi 2013, 2022) suggests that the implementation of AI demands the investigation of the binding conditions that make it possible to build and integrate artifacts into our lived world. Such artifacts can successfully interact with the world because our environment has been designed to be compatible with intelligent machines (such as robots). As the use of AI becomes ubiquitous in society, possibly leading to the formation of increasingly intelligent bio-technological unions, there will likely (...) be a coexistence of a plethora of micro-environments wrapped and tailored around humans and basic robots. The key element of this pervasive process will be the capacity to integrate biological realms in an infosphere suitable for the implementation of AI technologies. This process will require extensive datafication. This is because data is the basis of the logical-mathematical codes and models that drive and guide AI. This process will have huge consequences on workplaces, on workers, as well as on the decision-making processes required for the functioning of future societies. In this paper we will offer a comprehensive reflection on the moral and social implications of datafication as well as a set of considerations about its desirability, which will be informed by the following insights: (1) full protection of privacy may become structurally impossible, thus leading to undesirable forms of political and social control; (2) worker’s freedom may be reduced; (3) human creativity, imagination, and even divergence from AI logic might be channeled and possibly discouraged; (4) there will likely be a push towards efficiency and instrumental reason, which will become preeminent in production lines as well as in society. (shrink)

As we write this research paper, we notice an explosion in popularity of machine learning in numerous fields (ranging from governance, education, and management to criminal justice, fraud detection, and internet of things). In this contribution, rather than focusing on any of those fields, which have been well-reviewed already, we decided to concentrate on a series of more recent applications of deep learning models and technologies that have only recently gained significant track in the relevant literature. These applications are concerned (...) with artistic production (Sect. 2.1), the writing process (Sect. 2.2), music production (Sect. 2.3), text recognition and attribution (Sect. 2.4). After reviewing and analyzing the positive contributions as well as some of the major limitations of these technologies in each of those fields, we critically reflect (Sect. 3) on how their widespread implementation may affect humans and their creativity. In Sect. 4, we notice that deep learning models are here to stay; so, rather than embracing a negative or pessimistic stance with respect to their future applications in creative domains, we suggest a balanced approach for their assessment and beneficial usage. Finally (Sect. 5), we conclude by summarising what we have achieved and by pointing out possible future research directions. (shrink)

The increasing popularity of artificial cognitive enhancements raises the issue of their impact on the agent’s personal autonomy, and issues pertaining to how the latter is to be secured. The extended mind thesis implies that mental states responsible for autonomous action can be partly constituted by the workings of cognitive artifacts themselves, and the question then arises of whether this commits one to embracing an extended agent thesis. My answer is negative. After briefly presenting the main accounts on the conditions (...) for autonomous agency, and analyzing how the latter can be protected from threats posed by the use of cognitive artifacts, I argue that autonomous agency is essentially tied to conscious experience and intentionality, which in turn can only be attributed to the human part of any extended cognitive system. I present both theoretical (conceptual) and practical arguments against recognizing the entire extended system, composed of one human and an artifact, as an autonomous agent. (shrink)