“What data will show the truth?” is a fundamental question emerging early in any empirical investigation. From a statistical perspective, experimental design is the appropriate tool to address this question by ensuring control of the error rates of planned data analyses and of the ensuing decisions. From an epistemological standpoint, planned data analyses describe in mathematical and algorithmic terms a pre-specified mapping of observations into decisions. The value of exploratory data analyses is often less clear, resulting in confusion about what (...) characteristics of design and analysis are necessary for decision making and what may be useful to inspire new questions. This point is addressed here by illustrating the Popper-Miller theorem in plain terms and using a graphical support. Popper and Miller proved that probability estimates cannot generate hypotheses on behalf of investigators. Consistently with Popper-Miller, we show that probability estimation can only reduce uncertainty about the truth of a merely possible hypothesis. This fact clearly identifies exploratory analysis as one of the tools supporting a dynamic process of hypothesis generation and refinement which cannot be purely analytic. A clear understanding of these facts will enable stakeholders, mathematical modellers and data analysts to better engage on a level playing field when designing experiments and when interpreting the results of planned and exploratory data analyses. (shrink)

Many parts of the contemporary philosophical debate have been built on the radicalization of conclusions derived from the acceptance of a certain set of classical dichotomies. It also discusses how pragmatism and abduction are currently presented to solve the problems arising from these dichotomies. For this reason, the efforts of this article have been directed to analyze the impact of this fact on the philosophy of science and logic. The starting point is that accepting abduction implies, in many ways, accepting (...) the foundations of pragmatism. Also, that the analysis of such problems from pragmatism and the particular use of abduction dissolve the dichotomies and, with it, also modify the philosophical problems related to them. Therefore, I propose to understand abduction as the right conceptual device to review the problems and debates of the twentieth century’s epistemology from a pragmatic perspective. In doing so, the aim is to propose that the current use of abduction in contemporary debates may imply a change of the philosophical perspective. (shrink)

Research on autonomy exhibits a constellation of variegated perspectives, from the problem of the crude deprivation of it to the study of the distinction between personal and moral autonomy, and from the problem of the role of a “self as narrator”, who classifies its own actions as autonomous or not, to the importance of the political side and, finally, to the need of defending and enhancing human autonomy. My precise concern in this article will be the examination of the role (...) of the human cognitive processes that give rise to the most important ways of tracking the external world and human behavior in their relationship to some central aspects of human autonomy, also to the aim of clarifying the link between autonomy and the ownership of our own destinies. I will also focus on the preservation of human autonomy as an important component of human dignity, seeing it as strictly associated with knowledge and, even more significantly, with the constant production of new and pertinent knowledge of various kinds. I will also describe the important _paradox of autonomy_, which resorts to the fact that, on one side, cognitions (from science to morality, from common knowledge to philosophy, etc.) are necessary to be able to perform autonomous actions and decisions because we need believe in rules that justify and identify our choices, but, on the other side, these same rules can become (for example, as a result of contrasting with other internalized and approved moral rules or knowledge contents) oppressive norms that diminish autonomy and can thus, paradoxically, defeat agents’ autonomous capacity “to take ownership”. (shrink)

Under the rubric of understanding the problem of explainability of AI in terms of abductive cognition, I propose to review the lessons from AlphaGo and her more powerful successors. As AI players in Baduk have arrived at superhuman level, there seems to be no hope for understanding the secret of their breathtakingly brilliant moves. Without making AI players explainable in some ways, both human and AI players would be less-than omniscient, if not ignorant, epistemic agents. Are we bound to have (...) less explainable AI Baduk players as they make further progress? I shall show that the resolution of this apparent paradox depends on how we understand the crucial distinction between abduction and inference to the best explanation. Some further philosophical issues arising from explainable AI will also be discussed in connection with this distinction. (shrink)

_Locked_ and _unlocked_ strategies are illustrated in this article as concepts that deal with important cognitive aspects of deep learning systems. They indicate different inference routines that refer to poor (locked) to rich (unlocked) cases of creative production of creative cognition. I maintain that these differences lead to important consequences when we analyze computational deep learning programs, such as AlphaGo/AlphaZero, which are able to realize various types of abductive hypothetical reasoning. These programs embed what I call locked abductive strategies, so, (...) even if they present spectacular performances for example in games, they are characterized by poor types of hypothetical creative cognition insofar as they are constrained in what I call _eco-cognitive openness_. This openness instead characterizes unlocked human cognition that pertains to higher kinds of abductive reasoning, in both the creative and diagnostic cases, in which cognitive strategies are instead unlocked. This special kind of “openness” is physically rooted in the fundamental character of the human brain as an open system constantly coupled with the environment (that is, an “open” or “dissipative” system): its activity is the uninterrupted attempt to achieve the equilibrium with the environment in which it is embedded, and this interplay can never be switched off without producing severe damage to the brain. The brain cannot be conceived as deprived of its physical quintessence that is its openness. In the brain, contrary to the computational case, ordering is not derived from the outside thanks to what I have called in a recent book “computational domestication of ignorant entities”, but it is the direct product of an “internal” open dynamical process of the system. (shrink)