A lot of philosophy taught to science students consists of scientific methodology. But many philosophy of science textbooks have a fraught relationship with methodology, presenting it either a system of universal principles or entirely permeated by contingent factors not subject to normative assessment. In this paper, I argue for an alternative, heuristic perspective for teaching methodology: as fallible, purpose- and context-dependent, subject to cost-effectiveness considerations and systematically biased, but nevertheless subject to normative assessment. My pedagogical conclusion from this perspective is (...) that philosophers should aim to teach science students heuristic reasoning: strategies of normative method choice appraisal that are sensitive to purposes, contexts, biases and cost-effectiveness considerations; and that we should do so by teaching them exemplars of such reasoning. I illustrate this proposal at the hand of three such exemplars, showing how they help students to appreciate the heuristic nature of both methods and methodology, and to normatively assess method choice in such circumstances. (shrink)

Explainable artificial intelligence (XAI) seeks to produce explanations for those machine learning methods which are deemed opaque. However, there is considerable disagreement about what this means and how to achieve it. Authors disagree on what should be explained (topic), to whom something should be explained (stakeholder), how something should be explained (instrument), and why something should be explained (goal). In this paper, I employ insights from means-end epistemology to structure the field. According to means-end epistemology, different means ought to be (...) rationally adopted to achieve different epistemic ends. Applied to XAI, different topics, stakeholders, and goals thus require different instruments. I call this the means-end account of XAI. The means-end account has a descriptive and a normative component: on the one hand, I show how the specific means-end relations give rise to a taxonomy of existing contributions to the field of XAI; on the other hand, I argue that the suitability of XAI methods can be assessed by analyzing whether they are prescribed by a given topic, stakeholder, and goal. (shrink)

Scholars disagree about the plausibility of preference purification. Some see it as a familiar phenomenon. Others denounce it as conceptually incoherent, postulating that it relies on the psychologically implausible assumption of an inner rational agent. I argue that different notions of rationality can be leveraged to advance the debate: procedural rationality and structural rationality. I explicate how structural rationality, in contrast to procedural rationality, allows us to offer an account of the guiding idea behind preference purification that avoids inner rational (...) agents. Afterward, I address two pressing challenges against preference purification that emerge under the structural rationality account. (shrink)

The article explains on the two-year experiment after the author’s finalization of dissertation. The thesis of the dissertation was hidden in the last chapter with analytical linguistics. It was done so with the fascist development of the Chinese Communist regime with neo- Nazi characteristics. Since numerous prior warnings on the political downshifts & coup d’état in China was willfully ignored by the university, the linguistic innovations in dissertation found a balance between multilateralism and outer space (security). The experiments were conducted (...) with a combination of physical unit analysis & thermonuclear dynamics analysis. It describes the experiment process in terms of gravitation as gravitational singularity and Bekenstein-Penrose singularity. Detailed research process is elaborated in the article concerning the sociopolitical interactions the research involved. (shrink)