This paper develops my position on the ethics of price gouging in response to Jeremy Snyder's article, "What's the Matter with Price Gouging." First, it explains how the "nonworseness claim" supports the moral permissibility of price gouging, even if it does not show that price gougers are morally virtuous agents. Second, it argues that questions about price gouging and distributive justice must be answered in light of the relevant possible institutional alternatives, and that Snyder's proposed alternatives to price gouging fare (...) worse on the dimension of justice than a system in which goods are allocated by a system of market prices. (shrink)

Price gouging occurs when, in the wake of an emergency, sellers of a certain necessary goods sharply raise their prices beyond the level needed to cover increased costs. Most people think that price gouging is immoral, and most states have laws rendering the practice a civil or criminal offense. The purpose of this paper is to explore some of the philosophic issues surrounding price gouging, and to argue that the common moral condemnation of it is largely mistaken. I make this (...) argument in three steps, by rebutting three widely held beliefs about the ethics of price gouging: 1) that laws prohibiting price gouging are morally justified, 2) that price gouging is morally impermissible behavior, even if it ought not be illegal, and 3) that price gouging reflects poorly on the moral character of those who engage in it, even if the act itself is not morally impermissible. (shrink)

We are sceptical of concerns over the opacity of algorithmic decision tools. While transparency and explainability are certainly important desiderata in algorithmic governance, we worry that automated decision-making is being held to an unrealistically high standard, possibly owing to an unrealistically high estimate of the degree of transparency attainable from human decision-makers. In this paper, we review evidence demonstrating that much human decision-making is fraught with transparency problems, show in what respects AI fares little worse or better and argue that (...) at least some regulatory proposals for explainable AI could end up setting the bar higher than is necessary or indeed helpful. The demands of practical reason require the justification of action to be pitched at the level of practical reason. Decision tools that support or supplant practical reasoning should not be expected to aim higher than this. We cast this desideratum in terms of Daniel Dennett’s theory of the “intentional stance” and argue that since the justification of action for human purposes takes the form of intentional stance explanation, the justification of algorithmic decisions should take the same form. In practice, this means that the sorts of explanations for algorithmic decisions that are analogous to intentional stance explanations should be preferred over ones that aim at the architectural innards of a decision tool. (shrink)

Must the state handle the adjudication of disputes? Researchers of different perspectives, from heterodox scholars of law who advocate legal pluralism to libertarian economists who advocate the privatization of law, have increasingly questioned the idea that the state is, or should be, the only source of law. Both groups point out that government law has problems and that non-state alternatives exist. This Article discusses some problems with the public judicial system and several for-profit alternatives. Public courts lack both incentives to (...) embrace customer orientation and pricing mechanisms, plus they face problems associated with the bureaucratic provision of services. When parties are able to choose their tribunals, in contrast, those tribunals must provide service to customers and be mindful about conserving resources. Competition between arbitrators also can allow for experimentation and the provision of customized services rather than a centrally planned, one-size-fits-all system. Contracts with arbitration clauses can easily stipulate the choice of tribunal, and we argue that if government courts simply refused to overrule binding arbitration agreements, de facto privatization could easily take place. This Article discusses how the private adjudication of disputes could enable the market to internalize externalities and provide services that customers desire. (shrink)

ABSTRACT:In this response, I reiterate my argument that price gouging undercuts the goal of equity in access to essential goods whereas Zwolinski emphasizes the importance of the efficient provision of essential goods above all other goals. I agree that the efficient provision of essential goods is important as I argue for the goal of equitable access to sufficient of the goods essential to living a minimally flourishing human life. However, efficiency is a means to this goal rather than the end (...) itself. Finally, I offer additional arguments against the non-worseness claim. (shrink)

We argue that some algorithms are value-laden, and that two or more persons who accept different value-judgments may have a rational reason to design such algorithms differently. We exemplify our claim by discussing a set of algorithms used in medical image analysis: In these algorithms it is often necessary to set certain thresholds for whether e.g. a cell should count as diseased or not, and the chosen threshold will partly depend on the software designer’s preference between avoiding false positives and (...) false negatives. This preference ultimately depends on a number of value-judgments. In the last section of the paper we discuss some general principles for dealing with ethical issues in algorithm-design. (shrink)

In recent years, the sharing economy has attracted considerable attention, both scholarly and popular, relating to its capacity to enforce or undermine extant economic conventions. However, the process through which technological developments can effectively have this outcome of altering extant conventions on what is morally acceptable or desirable is still unclear. In this paper, we draw on the work of Boltanski and Thévenot and the notion of agencement to investigate the moral and performative dimension of controversies related to the SE. (...) The research stems from a qualitative case-based study of the controversy following Uber’s implementation in Montréal’s taxi market. We contribute to the literature on the SE through an empirical study of the moral debates entailed in the unfolding in situ of a SE device. We also add to the literature using the ‘Orders of Worth’ framework by showing how a compromise is solidified. We find that beyond discursive strategies, it is the concrete recomposition of laws, conventions, devices, persons, etc. that harmonised different definitions of the common good. Finally, we contribute to the literature on the relationship between technology, ethics, and social change by capturing the specific values that legitimise Uber, and by following their unfolding throughout a controversy. (shrink)

Algorithms silently structure our lives. Algorithms can determine whether someone is hired, promoted, offered a loan, or provided housing as well as determine which political ads and news articles consumers see. Yet, the responsibility for algorithms in these important decisions is not clear. This article identifies whether developers have a responsibility for their algorithms later in use, what those firms are responsible for, and the normative grounding for that responsibility. I conceptualize algorithms as value-laden, rather than neutral, in that algorithms (...) create moral consequences, reinforce or undercut ethical principles, and enable or diminish stakeholder rights and dignity. In addition, algorithms are an important actor in ethical decisions and influence the delegation of roles and responsibilities within these decisions. As such, firms should be responsible not only for the value-laden-ness of an algorithm but also for designing who-does-what within the algorithmic decision. As such, firms developing algorithms are accountable for designing how large a role individual will be permitted to take in the subsequent algorithmic decision. Counter to current arguments, I find that if an algorithm is designed to preclude individuals from taking responsibility within a decision, then the designer of the algorithm should be held accountable for the ethical implications of the algorithm in use. (shrink)

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would transparency contribute to restoring accountability for such systems as is often maintained? Several objections to full transparency are examined: the loss of privacy when datasets become public, the perverse effects of disclosure of the very algorithms themselves (“gaming the system” in particular), the potential loss of companies’ competitive edge, and the limited gains in answerability to be expected (...) since sophisticated algorithms usually are inherently opaque. It is concluded that, at least presently, full transparency for oversight bodies alone is the only feasible option; extending it to the public at large is normally not advisable. Moreover, it is argued that algorithmic decisions preferably should become more understandable; to that effect, the models of machine learning to be employed should either be interpreted ex post or be interpretable by design ex ante. (shrink)

The debate on the right to be forgotten on Google involves the relationship between human information processing and digital processing by algorithms. The specificity of digital memory is not so much its often discussed inability to forget. What distinguishes digital memory is, instead, its ability to process information without understanding. Algorithms only work with data without remembering or forgetting. Merely calculating, algorithms manage to produce significant results not because they operate in an intelligent way, but because they “parasitically” exploit the (...) intelligence, the memory, and the attribution of meaning by human actors. The specificity of algorithmic processing makes it possible to bypass the paradox of remembering to forget, which up to now blocked any human-based forgetting technique. If you decide to forget some memory, the most immediate effect is drawing attention to it, thereby activating remembering. Working differently from human intelligence, however, algorithms can implement, for the first time, the classical insight that it might be possible to reinforce forgetting not by erasing memories but by multiplying them. After discussing several projects on the web which implicitly adopt this approach, the article concludes by raising some deeper problems posed when algorithms use data and metadata to produce information that cannot be attributed to any human being. (shrink)

Price discrimination is the practice of charging different customers different prices for the same product. Many people consider price discrimination unfair, but economists argue that in many cases price discrimination is more likely to lead to greater welfare than is the uniform pricing alternative—sometimes for every party in the transaction. This article shows i) that there are many situations in which it is necessary to engage in differential pricing in order to make the provision of a product possible; and ii) (...) that in many such situations, the seller does not obtain an above-average rate of return. It concludes that price discrimination is not inherently unfair. The article also contends that even when conditions i) and/or ii) do not obtain, price discrimination is not necessarily unethical. In itself, the fact that some people get an even better deal than do others does not entail that the latter are wronged. (shrink)

This article argues that the price obtainable in an open market provides the best standard for determining the justice or injustice of the price of a product. The article argues that this standard, which is closely related to positions which have been held for hundreds of years, is superior to several alternative conceptions of the just price that have been put forward in recent years and is not subject to fundamental criticisms which can be addressed to them. The article also (...) shows how this standard is grounded in more fundamental principles of justice such as desert and equality. (shrink)

In the sixteenth and seventeenth centuries, members of the Salamanca School engaged in a sustained and sophisticated discussion of the issue of just prices. This article uses their contribution as a point of departure for a consideration of justice in pricing which will be relevant to current-day circumstances. The key theses of members of this school were that fairness of exchanges should be assessed objectively, that the fair price of an article is one equal to its ‘value’, and that the (...) best indicator of that value is the price that article commonly fetches in an open market. This article tries to bring to light the attractiveness of those views in order to guide current practice by contrasting them with alternative views, showing their connection with intuitively attractive basic standards, and linking them to commonly shared intuitions. (shrink)

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would transparency contribute to restoring accountability for such systems as is often maintained? Several objections to full transparency are examined: the loss of privacy when datasets become public, the perverse effects of disclosure of the very algorithms themselves, the potential loss of companies’ competitive edge, and the limited gains in answerability to be expected since sophisticated algorithms usually are (...) inherently opaque. It is concluded that, at least presently, full transparency for oversight bodies alone is the only feasible option; extending it to the public at large is normally not advisable. Moreover, it is argued that algorithmic decisions preferably should become more understandable; to that effect, the models of machine learning to be employed should either be interpreted ex post or be interpretable by design ex ante. (shrink)

Resting as it does on the principle of freedom, today’s global economic system is in need of a global economic ethos of responsibility so as to assure its social and ecological sustainability. Not all ideas of freedom, however, are equally amenable to conceptions of cosmopolitan responsibilities. This article examines how quantitative versus qualitative notions of freedom respectively respond to this challenge. Simply put, quantitative models hinder the integration of responsibility into models of economic rationality whereas qualitative conceptions advance it. As (...) a consequence, efforts to promote a humanistic paradigm of economics and management fare better when oriented at a qualitative idea of freedom. Cast along the lines of a qualitative conception of freedom, corporate responsibility more readily takes on a cosmopolitan dimension apt to meet the needs of the current age of globality. (shrink)

Cryptocurrencies such as Bitcoin, SETLcoin, Ether, Solar Coin, or Liberty Reserve exist since 2009. Because of their decentralized control, they are often considered a threat or alternative to the conventional centralized banking system. While the technological implication of some such currencies, especially of Bitcoin, has attracted much attention, so far there is little discussion about the entire field of cryptocurrencies and very little academic literature addressing its ethical significance. In this article, we thus address the impact of “blockchain technology” on (...) the nature of financial transactions from a business ethics perspective. We begin with a survey on relevant literature from neighboring disciplines. Next, we work towards a 3 × 3 framework for current debates on the ethics of cryptocurrencies : we combine the micro, meso, and macro levels of business and society with assessments of the potential ethical impact of cryptocurrencies as morally beneficial, detrimental, and ambiguous. In addition, we highlight possible avenues for future research, such as the changing roles of the miners and regulators, the prosocial use of cryptocurrencies, the antisocial use for shadow banking and transactions in the ‘dark net’ and cryptocurrencies’ effect on inflation and deflation. (shrink)

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would transparency contribute to restoring accountability for such systems as is often maintained? Several objections to full transparency are examined: the loss of privacy when datasets become public, the perverse effects of disclosure of the very algorithms themselves, the potential loss of companies’ competitive edge, and the limited gains in answerability to be expected since sophisticated algorithms usually are (...) inherently opaque. It is concluded that, at least presently, full transparency for oversight bodies alone is the only feasible option; extending it to the public at large is normally not advisable. Moreover, it is argued that algorithmic decisions preferably should become more understandable; to that effect, the models of machine learning to be employed should either be interpreted ex post or be interpretable by design ex ante. (shrink)

While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...) expectations about algorithms may be manipulative, adaptive, or moral; and that when accountability relationships are heavily burdened by the opacity and fluidity of complex algorithmic systems, the emphasis of engagement should shift to a rational communication process through which a continuous and tentative assessment of the development, workings, and consequences of algorithms can be achieved over time. The degree to which such engagement is, in fact, rational can be assessed based on four discourse-ethical principles of participation, comprehension, multivocality, and responsiveness. We conclude that the framework may help organizations and their environments to jointly work toward greater accountability for complex algorithms. It may further help organizations in reputational positioning surrounding accountability issues. The discourse-ethical principles introduced in this article are meant to elevate these positioning contests to extend beyond mere adaption or compliance and help guide organizations to find moral and forward-looking solutions to accountability issues. (shrink)

The sale of faster access to financial market data has recently generated public controversy. NY Attorney General Eric Schneiderman has referred to such fast data feeds as “Insider Trading 2.0”. For example, Thomson Reuters sold the University of Michigan’s Consumer Sentiment Index to computerized trading firms 2 seconds before releasing its data to its other paying clients. This paper explores the ethical issues involved in the sale of such information. Is selling faster access ethically the same as traditional insider trading, (...) which generally involves a breach of fiduciary duty or the use of misappropriated information? Such practices are extremely different from traditional insider trading as there is neither a breach of fiduciary duty nor misappropriation of inside information. The ethical issues are similar to other market segmentation and price discrimination issues, in which different prices are charged to different customers. The ability to price discriminate across segments can actually benefit large segments of the population who may receive lower prices because others, such as the high-speed traders, are paying more. The sale of faster access to information, especially by exchanges, raises additional ethical issues. There may be adverse effects on market quality that must be addressed. The moral distaste for the practice expressed by some stems from the seeming unfairness of a modern market structure that provides advantages to a small group of computerized traders. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)