In _Reliable Reasoning_, Gilbert Harman and Sanjeev Kulkarni -- a philosopher and an engineer -- argue that philosophy and cognitive science can benefit from statistical learning theory, the theory that lies behind recent advances in machine learning. The philosophical problem of induction, for example, is in part about the reliability of inductive reasoning, where the reliability of a method is measured by its statistically expected percentage of errors -- a central topic in SLT. After discussing philosophical attempts to evade the (...) problem of induction, Harman and Kulkarni provide an admirably clear account of the basic framework of SLT and its implications for inductive reasoning. They explain the Vapnik-Chervonenkis dimension of a set of hypotheses and distinguish two kinds of inductive reasoning. The authors discuss various topics in machine learning, including nearest-neighbor methods, neural networks, and support vector machines. Finally, they describe transductive reasoning and suggest possible new models of human reasoning suggested by developments in SLT. (shrink)

We provide self-contained proof of a theorem relating probabilistic coherence of forecasts to their non-domination by rival forecasts with respect to any proper scoring rule. The theorem recapitulates insights achieved by other investigators, and clarifi es the connection of coherence and proper scoring rules to Bregman divergence.

The problem of induction is sometimes motivated via a comparison between rules of induction and rules of deduction. Valid deductive rules are necessarily truth preserving, while inductive rules are not.

In this paper, we develop a conceptual framework of the intra-firm transfer of best practices in moral reasoning by integrating three streams of literature: internal knowledge transfer in strategic management, moral reasoning and epistemology in philosophy and business ethics, and leader–member exchange in human resource management. We propose that characteristics of moral reasoning (nature of moral knowledge, tacitness of moral reasoning and causal ambiguity), source characteristics (moral development of leaders), target characteristics (integrity capacity and moral development of subordinates), leader–member exchange (...) and internal ethical climate influence the transfer of best practices in moral reasoning. (shrink)

Stochastic forecasts in complex environments can benefit from combining the estimates of large groups of forecasters (“judges”). But aggregating multiple opinions faces several challenges. First, human judges are notoriously incoherent when their forecasts involve logically complex events. Second, individual judges may have specialized knowledge, so different judges may produce forecasts for different events. Third, the credibility of individual judges might vary, and one would like to pay greater attention to more trustworthy forecasts. These considerations limit the value of simple aggregation (...) methods like linear averaging. In this paper, a new algorithm is proposed for combining probabilistic assessments from a large pool of judges. Two measures of a judge’s likely credibility are introduced and used in the algorithm to determine the judge’s weight in aggregation. The algorithm was tested on a data set of nearly half a million probability estimates of events related to the 2008 U.S. presidential election (∼ 16000 judges). (shrink)

Background and rationale Several factors that motivate individuals to participate in non-therapeutic studies have been identified. This study was conducted as limited data is available regarding these motivations from developing countries. Methods This was a single-centre study conducted over 4 months in which a questionnaire was administered to 102 healthy participants and 16 patient participants who had earlier taken part in non-therapeutic studies at our centre. Descriptive statistics and univariate analysis were used to analyse data. Results The most common motivation (...) among healthy participants was financial reward (65%) followed by altruism, free medical check up, curiosity and personal health benefit. Patient participants, however, most commonly said they consented to take part in the trial as they were ‘invited to participate by the treating physician’ (88%). In comparison with the patient participants, healthy participants were more likely to be satisfied with the financial reward (p=0.02), and recommend participation in studies to friends or relatives (p=0.0013). Conclusions The most common motivating factor to participate in non-therapeutic studies appears to be different for healthy participants (financial reward) and patient participants (invitation to participate by the physician). Participants also felt that adequate information and care was given to them during the trial, and that they would participate in future clinical studies, and would also recommend such studies to their friends. (shrink)

This paper addresses the conflicting environmental interests of a firm and the community, an important stakeholder. The short-term profit maximization objective of a firm may stand in contrast with what the community wants – a "safe and clean environment". This paper argues that the information regarding the environmental impact of a firm's products, processes, and waste may be asymmetrically distributed between the firm and the community. The resultant information asymmetry may influence the probability of a firm acting opportunistically, and ultimately, (...) a firm's ethical behavior. The paper identifies information asymmetry between a firm and community, as well as that within the community. The perceived information asymmetry across various community segments may perhaps be a determinant of environmental discrimination. The paper further contends that information asymmetry may diminish in the long run. Finally it examines the implications of information asymmetry for firms and government policy. (shrink)

This paper addresses the conflicting environmental interests of a firm and the community, an important stakeholder. The short-term profit maximization objective of a firm may stand in contrast with what the community wants – a "safe and clean environment". This paper argues that the information regarding the environmental impact of a firm's products, processes, and waste may be asymmetrically distributed between the firm and the community. The resultant information asymmetry may influence the probability of a firm acting opportunistically, and ultimately, (...) a firm's ethical behavior. The paper identifies information asymmetry between a firm and community, as well as that within the community. The perceived information asymmetry across various community segments may perhaps be a determinant of environmental discrimination. The paper further contends that information asymmetry may diminish in the long run. Finally it examines the implications of information asymmetry for firms and government policy. (shrink)

The article focuses on the ‘meaningfulness in work’ concept and addresses three theoretical gaps by investigating ‘meaningfulness in work’ from the perspective of Heidegger’s ‘authenticity’ and ‘Dasein’ constructs as well as virtue ethics. First, it adapts Heideggerian phenomenology and argues that meaningfulness in work may be revealed to an ‘authentic’ employee, while they performs everyday activities by ‘existing’ in their world and discovers their Dasein. Second, it emphasizes the normative, as opposed to instrumental implications of meaningfulness and invokes virtue ethics (...) towards this end. Third, it integrates the Heideggerian approach with virtue ethics to describe how an ‘authentic’ and ‘virtuous’ employee may achieve meaningfulness in work (conceptualized as ‘eudaimonia’). An ‘authentic virtuous employee’ ‘exists in their world’ and discovers what is truly meaningful in work to them. They also displays temperance and courage in terms of closing the gaps between current and desired levels of meaningfulness in work, and continually contemplates it. We describe a ‘professional’ as an example of an ‘authentic virtuous employee’. (shrink)

This paper analyzes individual probabilistic predictions of state outcomes in the 2008 U.S. presidential election. Employing an original survey of more than 19,000 respondents, ours is the first study of electoral forecasting to involve multiple subnational predictions and to incorporate the influence of respondents’ home states. We relate a range of demographic, political, and cognitive variables to individual accuracy and predictions, as well as to how accuracy improved over time. We find strong support for wishful thinking bias in expectations, as (...) Republicans gave higher probabilities to McCain victories and were worse at overall prediction. In addition, we find that respondents living in states with higher vote shares for Obama performed better at prediction and displayed less wishful thinking bias. We conclude by showing that suitable aggregations of our respondents’ predictions outperformed Intrade (a prediction market) and fivethirtyeight.com (a poll-based forecast) at most points in time. (shrink)

Statistical Learning Theory (e.g., Hastie et al., 2001; Vapnik, 1998, 2000, 2006) is the basic theory behind contemporary machine learning and data-mining. We suggest that the theory provides an excellent framework for philosophical thinking about inductive inference.

Papers presented at two national seminars on Language science and cognition and Epistemology and cognition held at Hyderabad.

Like Glenn Shafer, we are nostalgic for the time when “philosophers, mathematicians, and scientists interested in probability, induction, and scientific methodology talked with each other more than they do now”, [p.10]. 1 Shafer goes on to mention other relevant contemporary communities. He himself has been at the interface of many of these communities while at the same time making major contributions to them and this very symposium represents something of that desired discussion. We begin with a couple of general points (...) about issues several commentators have raised and then discuss other more particular issues. (shrink)

The transplant community has faced unprecedented challenges balancing risks of performing living donor transplants during the COVID-19 pandemic with harms of temporarily suspending these procedures. Decisions regarding postponement of living donation stem from its designation as an elective procedure, this despite that the Centers for Medicare and Medicaid Services categorise transplant procedures as tier 3b (high medical urgency—do not postpone). In times of severe resource constraints, health systems may be operating under crisis or contingency standards of care. In this manuscript, (...) the United Network for Organ Sharing Ethics Workgroup explores prioritisation of living donation where health systems operate under contingency standards of care and provide a framework with recommendations to the transplant community on how to approach living donation in these circumstances.To guide the transplant community in future decisions, this analysis suggests that: (1) living donor transplants represent an important option for individuals with end-stage liver and kidney disease and should not be suspended uniformly under contingency standards, (2) exposure risk to SARS-CoV-2 should be balanced with other risks, such as exposure risks at dialysis centres. Because many of these risks are not quantifiable, donors and recipients should be included in discussions on what constitutes acceptable risk, (3) transplant hospitals should strive to maintain a critical transplant workforce and avoid diverting expertise, which could negatively impact patient preparedness for transplant, (4) transplant hospitals should consider implementing protocols to ensure early detection of SARS-CoV-2 infections and discuss these measures with donors and recipients in a process of shared decision-making. (shrink)

A firm’s enterprise strategy denotes what a firm stands for. Despite its importance, there has been little research on this topic. Furthermore, the theoretical bases underlying the existing approaches to enterprise strategy suffer from several limitations. In view of these shortcomings, this paper invokes Amartya Sen’s Capabilities Approach (SCA) and its notion of “justice as freedom” as a normative foundation of enterprise strategy. Toward this end, it integrates different streams in the stakeholder theory/business ethics and economics literature. It focuses on (...) the stakeholder capability of “having a voice,” and the managerial capability of “using the knowledge to provide stakeholders a voice and freedom.”. (shrink)

A firm’s enterprise strategy denotes what a firm stands for. Despite its importance, there has been little research on this topic. Furthermore, the theoretical bases underlying the existing approaches to enterprise strategy suffer from several limitations. In view of these shortcomings, this paper invokes Amartya Sen’s Capabilities Approach (SCA) and its notion of “justice as freedom” as a normative foundation of enterprise strategy. Toward this end, it integrates different streams in the stakeholder theory/business ethics and economics literature. It focuses on (...) the stakeholder capability of “having a voice,” and the managerial capability of “using the knowledge to provide stakeholders a voice and freedom.”. (shrink)

In this article, we provide a tutorial overview of some aspects of statistical learning theory, which also goes by other names such as statistical pattern recognition, nonparametric classification and estimation, and supervised learning. We focus on the problem of two-class pattern classification for various reasons. This problem is rich enough to capture many of the interesting aspects that are present in the cases of more than two classes and in the problem of estimation, and many of the results can be (...) extended to these cases. Focusing on two-class pattern classification simplifies our discussion, and yet it is directly applicable to a wide range of practical settings. (shrink)

Understanding why individuals opt out of living donation is crucial to enhancing protections for all living donors and to identify modifiable barriers to donation. We developed an ethical approach to conducting research on individuals who opted out of living kidney donation and applied it in a small-scale qualitative study at one US transplant centre. The seven study participants had varied reasons for opting out, the most prominent of which was concern about the financial burden from lost wages during the postoperative (...) period. Several reported feeling alone during their decision-making process. Although no participants used an alibi, a centre-provided statement of non-eligibility to donate, all believed that centres should offer alibis to help preserve donor autonomy. Given the complexity of participants' decisions and the emotions they experienced before and after deciding not to donate, we suggest approaches for independent living donor advocates to support this population. This study demonstrates that research on individuals who opt out of donation is feasible and yields valuable insight into methods to improve the evaluation experience for potential living donors. (shrink)

��The Coherent Approximation Principle (CAP) is a method for aggregating forecasts of probability from a group of judges by enforcing coherence with minimal adjustment. This paper explores two methods to further improve the forecasting accuracy within the CAP framework and proposes practical algorithms that implement them. These methods allow flexibility to add fixed constraints to the coherentization process and compensate for the psychological bias present in probability estimates from human judges. The algorithms were tested on a data set of nearly (...) half a million probability estimates of events related to the 2008 U.S. presidential election (from about 16000 judges). The results show that both methods improve the stochastic accuracy of the aggregated forecasts compared to using simple CAP. (shrink)

This book is a collection of essays written by various authors including the editors of the collection, Phoebe V. Moore, Martin Upchurch, and Xanthe Whittaker. These essays deal with the current topics of monitoring of workers in the new gig economy, digitalization of the work, and use of big data for the restructuring of the workforce. This book examines how new forms of surveillance are being adopted into contemporary work. It draws from original empirical research engaging with existing and emerging (...) fields of social inquiry and discusses the occurrence of surveillance and new forms of measurement of work in a range of industries. (shrink)

This book is a collection of essays written by various authors including the editors of the collection, Phoebe V. Moore, Martin Upchurch, and Xanthe Whittaker. These essays deal with the current topics of monitoring of workers in the new gig economy, digitalization of the work, and use of big data for the restructuring of the workforce. This book examines how new forms of surveillance are being adopted into contemporary work. It draws from original empirical research engaging with existing and emerging (...) fields of social inquiry and discusses the occurrence of surveillance and new forms of measurement of work in a range of industries. (shrink)