Brains, it has recently been argued, are essentially prediction machines. They are bundles of cells that support perception and action by constantly attempting to match incoming sensory inputs with top-down expectations or predictions. This is achieved using a hierarchical generative model that aims to minimize prediction error within a bidirectional cascade of cortical processing. Such accounts offer a unifying model of perception and action, illuminate the functional role of attention, and may neatly capture the special contribution of cortical processing to (...) adaptive success. This target article critically examines this approach, concluding that it offers the best clue yet to the shape of a unified science of mind and action. Sections 1 and 2 lay out the key elements and implications of the approach. Section 3 explores a variety of pitfalls and challenges, spanning the evidential, the methodological, and the more properly conceptual. The paper ends (sections 4 and 5) by asking how such approaches might impact our more general vision of mind, experience, and agency. (shrink)

We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure that algorithmic (...) governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider barriers to legitimate and effective algorithmic governance and the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence. (shrink)

In this article I explain why cognitive science (including some neuroscience) matters for normative ethics. First, I describe the dual-process theory of moral judgment and briefly summarize the evidence supporting it. Next I describe related experimental research examining influences on intuitive moral judgment. I then describe two ways in which research along these lines can have implications for ethics. I argue that a deeper understanding of moral psychology favors certain forms of consequentialism over other classes of normative moral theory. I (...) close with some brief remarks concerning the bright future of ethics as an interdisciplinary enterprise. (shrink)

This study addresses the question of normative analysis of the value‐based aspects of nursing. In our perspective, values in science may be distinguished into (i) epistemic when related to the goals of truth and objectivity and (ii) non‐epistemic when related to social, cultural or political aspects. Furthermore, values can be called constitutive when necessary for a scientific enterprise, or contextual when contingently associated with science. Analysis of the roles of the various forms of values and models of knowledge translation provides (...) the ground to understand the specific role of values in nursing. A conceptual framework has been built to classify some of the classical perspectives on nursing knowledge and to examine the relationships between values and different forms of knowledge in nursing. It follows that adopting a normative perspective in the analysis of nursing knowledge provides key elements to identify its proper dimension. (shrink)

An understanding of the nature and development of nursing intuition can help nurse educators foster it in young nurses and give clinicians more confidence in this aspect of their knowledge, allowing them to respond with greater assurance to their intuitions. In this paper, accounts from philosophy and neurophysiology are used to argue that intuition, specifically nursing intuition, is a valid form of knowledge. The paper argues that nursing intuition, a kind of practical intuition, is composed of four distinct aspects that (...) include: embodied knowledge rather like that knowledge we have when we have learned to ride a bicycle; well‐trained sensory perceptions attentive to subtle details of complex, often rapidly changing situations; a significant store of pertinent conceptual knowledge; and a history of habitual actions intentionally directed towards achieving the best outcomes for our patients. Contemporary neurophysiology research strongly suggests that human persons experience other persons such that they directly understand the meaning of a variety of different human actions, intentions, emotions, and sensations in immediate, non‐reflective, and non‐conceptual perceptions. This research is supported by the philosophical theories of Jacques Maritain and Yves R. Simon found in their accounts of practical knowledge. Together, these accounts offer us a rich view of the reality of nursing intuition that helps us understand why we find intuitive actions in some but not all nurses and gives us some specific information about how to develop intuition in young nurses. Finally, this research shows us a path for further research. (shrink)