In bioethics and health policy, we often discuss the appropriate boundaries of public funding; how the interface of public and private purchasers and providers should be organized and regulated receives less attention. In this paper, I discuss ethical and regulatory issues raised at this interface by three medical practice models in which physicians provide insured services while requiring or requesting that patients pay for services or for the non-insured services of the physicians themselves or their associates. This choice for such (...) practice models is different from the decision to design an insurance plan to include or exclude user fees, co-payments and deductibles. I analyze the issues raised with regards to familiar health care values of equity and efficiency, while highlighting additional concerns about fair terms of access, provider integrity, and fair competition. I then analyze the common Canadian regulatory response to block fee models, considering their extension to wellness clinics, with regards to fiduciary standards governing the physician–patient relationship and the role of informed consent. I close by highlighting briefly issues that are of common concern across different fundamental normative frameworks for health policy. (shrink)

The renaissance of Aristotelian virtue ethics has produced an extensive philosophical literature that criticizes markets for a lack of virtues. Drawing on Michael Sandel’s virtue-ethical critique of price gouging during natural disasters, we (1) identify and clarify serious misunderstandings in recurring price-gouging debates between virtue-ethical critics and economists. Subsequently, (2) we respond to Sandel’s call for interdisciplinary dialogue. However, instead of solely calling on economics to embrace insights from virtue ethics, we prefer a two-sided version of interdisciplinary dialogue and argue (...) that virtue ethics should embrace economic insights. In particular, we argue that if virtue ethics is to preserve its social relevance under modern conditions, it should re-conceptualize its notion of virtue and re-evaluate the self-interested but effective—and in this sense solidary—help among strangers via markets as virtuous rather than devaluate it as greed, that is, as vicious price gouging. (shrink)

Algorithmic predictions are promising for insurance companies to develop personalized risk models for determining premiums. In this context, issues of fairness, discrimination, and social injustice might arise: Algorithms for estimating the risk based on personal data may be biased towards specific social groups, leading to systematic disadvantages for those groups. Personalized premiums may thus lead to discrimination and social injustice. It is well known from many application fields that such biases occur frequently and naturally when prediction models are applied to (...) people unless special efforts are made to avoid them. Insurance is no exception. In this paper, we provide a thorough analysis of algorithmic fairness in the case of insurance premiums. We ask what “fairness” might mean in this context and how the fairness of a premium system can be measured. For this, we apply the established fairness frameworks of the fair machine learning literature to the case of insurance premiums and show which of the existing fairness criteria can be applied to assess the fairness of insurance premiums. We argue that two of the often-discussed group fairness criteria, independence (also called statistical parity or demographic parity) and separation (also known as equalized odds), are not normatively appropriate for insurance premiums. Instead, we propose the sufficiency criterion (also known as well-calibration) as a morally defensible alternative that allows us to test for systematic biases in premiums towards certain groups based on the risk they bring to the pool. In addition, we clarify the connection between group fairness and different degrees of personalization. Our findings enable insurers to assess the fairness properties of their risk models, helping them avoid reputation damage resulting from potentially unfair and discriminatory premium systems. (shrink)

The article presents two main arguments. First, we claim that in contemporary societies, insurance enacts peculiar kinds of solidarities as well as inequality and exclusion. Especially important in this respect are life, health, disability and old age pension insurance, both in compulsory and voluntary forms. Second, the article maintains that the ideas of solidarity, inequality and exclusion are transformed by the machinery of insurance. In other words, the concrete ways in which insurance relations are practically arranged have an effect on (...) the ways in which the related moral and political concepts are perceived. We elaborate on three different forms of insurance solidarity, which we call chance, risk and income solidarity. The existence of multiple forms of solidarity relevant to insurance is significant because practices of insurance require decisions concerning what kind of solidarity is emphasised, when it is emphasised, and on what grounds. Moreover, what is solidarity for some can entail exclusion and inequality for others. Showing these internal tensions within insurance practice underlines the inherently political and moral nature of insurance. (shrink)

Public insurance is both everywhere and nowhere. It is everywhere in the sense that it is omnipresent in industrialised societies: public health insurance, unemployment benefits and pensions. It is a sizeable part of modern nations’ public budget . It has permeated our understanding of societal institutions to the extent that now access to public insurance coverage is understood as being a struggle for equality and equal citizenship .Public insurance is only one aspect of a broader phenomenon: the transformation of modern (...) societies into insurance societies, i.e. societies that are orientated toward risk-management . Nevertheless, public insurance is at the core of the welfare state as insurance system. Paul Krugman once said of the modern state that it is ‘an insurance company with an army’ while David Moss argues that government is the ultimate risk manager ( .. (shrink)

Insurance is pervasive in many social settings. As a cooperative device based on risk pooling, it serves to attenuate the adverse consequences of various risks by offering policyholders coverage against the losses implied by adverse events in exchange for the payment of premiums. In the insurance industry, the concept of actuarial fairness serves to establish what could be adequate, fair premiums. Accordingly, premiums paid by policyholders should match as closely as possible their risk exposure. Such premiums are the product of (...) the probabilities of losses and the expected losses. This article presents a discussion of the fairness of actuarial fairness through three steps: defining the concept based on its formulation within the insurance industry; determining in which sense it may be about fairness; and raising some objections to the actual fairness of actuarial fairness. The necessity of a normative evaluation of actuarial fairness is justified by the influence of the concept on the current reforms of public insurance systems and the fact that it highlights the question of the repartition of the gains and burdens of social cooperation. (shrink)

In recent years, scholars in the social sciences and humanities have turned their attention to how the rise of digital technologies is reshaping political life in contemporary society. Here, we analyze this issue by distinguishing between two classification technologies typical of pre-digital and digital eras that differently constitute the relationship between individuals and groups. In class-based systems, characteristic of the pre-digital era, one’s status as an individual is gained through membership in a group in which salient social identities are shared (...) in common with other group members. In attribute-based systems, characteristic of the digital era, one’s status as an individual is determined by virtue of possession of a set of attributes that need not be shared with others. We argue that differences between these two types of classification technologies have important implications for how persons attach (or fail to attach) to groups, and therefore what kinds of political mobilization are possible. We illustrate this argument by examining contention over the use of gender as a variable in the pricing of risk in insurance and credit – two markets in which individuals directly encounter class-based and attribute-based systems of classification, respectively. (shrink)

The recent proliferation of new data and technologies enables increasingly finer personalization of products and prices in every domain. In insurance, this revives and enlarges old debates around fairness that have never been completely settled. We will argue that the commonly accepted “actuarial fairness” as based on the “individual cost of risk” derives in fact from a conflation: while it indicates the average cost for a group of insureds from the perspective of an insurance company—and is therefore sound from a (...) business profitability viewpoint—it is arguable whether it represents the “fair price” for the individual insured. We first show in a historical perspective the intertwinement of conceptions of fairness with knowledge, in order to point to the alternative to actuarial fairness for insurance. We then describe the intrinsic difference between the insured and the insurer when underwriting an insurance contract. Finally, we build on this distinction to discuss the meaning of fairness in insurance prices. We thus hope to re-center the debate around insurance fairness on its underlying solidarity mechanisms rather than technical and actuarial considerations. (shrink)

In preparing for and responding to natural hazards and disasters, the welfare state establishes a social contract, distributing responsibilities for what will be collectively managed and what will be individually borne. Drawing on archival, interview, and ethnographic data, this article examines the renegotiation of that social contract through the lens of contested efforts to reform the massively indebted US National Flood Insurance Program from 2011 to 2014. In the face of a morally charged debate about deservingness and individual choice, Congress (...) passed legislation that committed to incorporating need-based considerations to the NFIP for the first time. The result defined “deservingness” in terms of ability to pay for risk exposure, qualifying an individualization of responsibility for addressing the problem of flood loss—a problem that might instead demand broader risk sharing, particularly as climate change worsens the threat of flooding. (shrink)

With their intensive use of data to classify and price risk, insurers have often been confronted with data-related issues of fairness and discrimination. This paper provides a comparative review of discrimination issues raised by traditional statistics versus machine learning in the context of insurance. We first examine historical contestations of insurance classification, showing that it was organized along three types of bias: pure stereotypes, non-causal correlations, or causal effects that a society chooses to protect against, are thus the main sources (...) of dispute. The lens of this typology then allows us to look anew at the potential biases in insurance pricing implied by big data and machine learning, showing that despite utopic claims, social stereotypes continue to plague data, thus threaten to unconsciously reproduce these discriminations in insurance. To counter these effects, algorithmic fairness attempts to define mathematical indicators of non-bias. We argue that this may prove insufficient, since as it assumes the existence of specific protected groups, which could only be made visible through public debate and contestation. These are less likely if the right to explanation is realized through personalized algorithms, which could reinforce the individualized perception of the social that blocks rather than encourages collective mobilization. (shrink)