Cognitive science has recently begun exploring how people conceptualize and reason about truth. We offer the field a framework that can guide inquiry into intuitive theories of truth, centered on three core questions: how do people judge whether statements could be true, whether statements are true, and whether to assert them as true.
Explanations are social, and when people try to explain something, they usually seek input from others. We present a simple theory of how people use the explanations they encounter as clues to the broader landscape of possible explanations, informing their decision to exploit what has been found or explore new possibilities. The challenge of coming up with novel explanations draws people to exploit or imitate appealing ones (information cascades); this draw increases as less appealing alternatives become more distant (the ``strawman'' effect). Conversely, pairs of low-quality explanations promote exploratory behavior or long-leaps away from observed attempts, and pairs of divergent high-quality explanations can lead to merging and syncretism. We use a transmission-chain experiment to test, and confirm, these predictions. Intriguingly, we also find that while people imitate good explanations, their imitations often fall short in quality. Our work provides new insight into how collective exploration can be promoted, or stalled, by implicit information about what is yet to be discovered.
Traditionally, epistemologists have distinguished between epistemic and pragmatic goals. In so doing, they presume that much of game theory is irrelevant to epistemic enterprises. I will show that this is a mistake. Even if we restrict attention to purely epistemic motivations, members of epistemic groups will face a multitude of strategic choices. I illustrate several contexts where individuals who are concerned solely with the discovery of truth will nonetheless face difficult game theoretic problems. Examples of purely epistemic coordination problems and social dilemmas will be presented. These show that there is a far deeper connection between economics and epistemology than previous appreciated.
This paper approaches the problem of testimony from a new direction. Rather than focusing on the epistemic grounds for testimony, it considers the problem from the perspective of an individual who must choose whom to trust from a population of many would-be testifiers. A computer simulation is presented which illustrates that in many plausible situations, those who trust without attempting to judge the reliability of testifiers outperform those who attempt to seek out the more reliable members of the community. In so doing, it presents a novel defense for the credulist position that argues one should trust testimony without considering the underlying reliability of the testifier.
Several philosophers of science have argued that epistemically rational individuals might form epistemically irrational groups and that, conversely, rational groups might be composed of irrational individuals. We call the conjunction of these two claims the Independence Thesis, as they entail that methodological prescriptions for scientific communities and those for individual scientists are logically independent. We defend the inconsistency thesis by characterizing four criteria for epistemic rationality and then proving that, under said criteria, individuals will be judged rational when groups are not and vice versa. We then explain the implications of our results for descriptive history of science and normative epistemology.
We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the performance of various, common boundedly-rational strategies depends crucially upon the social context (if any) in which such strategies are to be employed.
Much of contemporary knowledge is generated by groups not single individuals. A natural question to ask is, what features make groups better or worse at generating knowledge? This paper surveys research that spans several disciplines which focuses on one aspect of epistemic communities: the way they communicate internally. This research has revealed that a wide number of different communication structures are best, but what is best in a given situation depends on particular details of the problem being confronted by the group.
It is widely believed that bringing parties with differing opinions together to discuss their differences will help both in securing consensus and also in ensuring that this consensus closely approximates the truth. This paper investigates this presumption using two mathematical and computer simulation models. Ultimately, these models show that increased contact can be useful in securing both consensus and truth, but it is not always beneficial in this way. This suggests one should not, without qualification, support policies which increase interpersonal contact if one seeks to improve the epistemic performance of groups.
Conformity is an often criticized feature of human belief formation. Although generally regarded as a negative influence on reliability, it has not been widely studied. This paper attempts to determine the epistemic effects of conformity by analyzing a mathematical model of this behavior. In addition to investigating the effect of conformity on the reliability of individuals and groups, this paper attempts to determine the optimal structure for conformity. That is, supposing that conformity is inevitable, what is the best way for conformity effects to occur? The paper finds that in some contexts conformity effects are reliability inducing and, more surprisingly even when it is counterproductive, not all methods for reducing its effect are helpful. These conclusions contribute to a larger discussion in social epistemology regarding the effect of social behavior on individual reliability.
Meta science
Against theory-motivated experimentation: Can random experimental choice lead to better theories? with Marina Dubova & Arseny Moskvichev Collective Intellegence Scientists must choose which among many experiments to perform. We study the epistemic success of experimental choice strategies proposed by philosophers of science or executed by scientists themselves. We develop a multi-agent model of the scientific process that jointly formalizes its core aspects: active experimentation, theorizing, and social learning. We find that agents who choose new experiments at random develop the most informative and predictive theories of the world. The agents aiming to confirm, falsify theories, or resolve theoretical disagreements end up with an illusion of epistemic success: they develop promising accounts for the data they collected, while misrepresenting the ground truth that they intended to learn about. Agents experimenting in these theory-motivated ways acquire less diverse or less representative samples from the ground truth that also turn out to be easier to account for. Random data collection, on the other hand, combines virtues of diverse and representative sampling from a target scientific domain which enables cumulative development of the successful theoretical accounts of it. We suggest that randomization, already a gold standard within experiments, is also beneficial at the level of experiments themselves.
The Evolution of Scientific Credit: When Authorship Norms Impede Collaboration with Toby Handfield, Royal Society Open Science Scientific authorship norms vary dramatically across disciplines, from contribution-sensitive systems where first author is the greatest contributor and subsequent author order reflects relative input, to contribution-insensitive conventions like alphabetical ordering or senior-author-last. We develop evolutionary game-theoretic models to examine both how these divergent norms emerge and their subsequent effects on collaborative behaviour. Our first model reveals that contribution-insensitive norms evolve when researchers who sacrifice positional advantage face the strongest adaptive pressure—for example, senior authors managing larger collaboration portfolios or bearing heavier reputational stakes. This ‘Red King’ dynamic potentially explains why fields in which senior researchers command large laboratories, major grants and extensive collaboration portfolios may paradoxically evolve conventions that favour junior authors. Our second model demonstrates that established norms influence researchers’ willingness to collaborate, with contribution-sensitive norms consistently outperforming insensitive alternatives in fostering successful partnerships. Contribution-insensitive norms create systematic coordination failures through two mechanisms: ‘main contributor resentment’ when exceptional work goes unrecognized; and ‘second contributor resentment’ when comparable efforts receive unequal credit. These findings suggest that widely adopted practices like senior-last positioning and alphabetical ordering may function as institutional frictions that impede valuable scientific collaborations rather than neutral organizational conventions, potentially reducing overall scientific productivity across affected disciplines.
Academic journals, incentives, and the quality of peer review: a model with Toby Handfield and Julian García, Philosophy of Science We model the impact of different incentives on journal behavior in undertaking peer review. Under one scheme, the journal aims to publish the highest-quality papers; under the second, the journal aims to maintain a high rejection rate. Under both schemes, journals prefer to set very high standards for acceptance despite allowing significant error in peer review. Under the second scheme, however, in order to encourage more submissions of mediocre papers, the journal is incentivized to make its editorial process less accurate. This leads to both worse peer review and lower-quality articles being published.
Academic journals provide a key quality-control mechanism in science. Yet, information asymmetries and conflicts of interests incentivize scientists to deceive journals about the quality of their research. How can honesty be ensured, despite incentives for deception? Here, we address this question by applying the theory of honest signaling to the publication process. Our models demonstrate that several mechanisms can ensure honest journal submission, including differential benefits, differential costs, and costs to resubmitting rejected papers. Without submission costs, scientists benefit from submitting all papers to high-ranking journals, unless papers can only be submitted a limited number of times. Counterintuitively, our analysis implies that inefficiencies in academic publishing (e.g., arbitrary formatting requirements, long review times) can serve a function by disincentivizing scientists from submitting low-quality work to high-ranking journals. Our models provide simple, powerful tools for understanding how to promote honest paper submission in academic publishing.
Fraud and misleading research represent serious impediments to scientific progress. We must uncover the causes of fraud in order to understand how science functions and in order to develop strategies for combating epistemically detrimental behavior. This paper investigates how the incentive to commit fraud is enhanced by the structure of the scientific reward system. Science is an "accumulation process:" success begets resources which begets more success. Through a simplified mathematical model, I argue that this cyclic relationship enhances the appeal of fraud and makes combating it extremely difficult.
Learning to Collaborate forthcoming in Boyer-Kasem, Mayo-Wilson, Weisberg (eds.) Scientific Collaboration and Collective Knowledge (Cambridge University Press).
This paper presents a rudimentary model of collaboration with the aim to understand the conditions under which groups of scientists will endogenously form optimal collaborative groups. By analyzing the model with computer simulations, I uncover three lessons for collaborative groups. First, in reducing the cost borne by scientists from collaborating, one benefits the members of the group. Second, increasing the number of potential collaborative partners benefits all those involved in a collaborative group. Finally and counter-intuitively, this model suggests that groups do better when scientists avoid experimenting with new collaborative interactions.
Theories of scientific rationality typically pertain to belief. This paper argues that we should expand our focus to include motivations as well as belief. An economic model is used to evaluate whether science is best served by scientists motivated only by truth, only by credit, or by both truth and credit. In many, but not all, situations scientists motivated by both truth and credit should be judged as the most rational scientists.
Those who comment on modern scientific institutions are often quick to praise institutional structures that leave scientists to their own devices. These comments reveal an underlying presumption that scientists do best when left alone -- when they operate in what we call the scientific state of nature. Through computer simulation, we challenge this presumption by illustrating an inefficiency that arises in the scientific state of nature. This inefficiency suggests that one cannot simply presume that science is most efficient when institutional control is absent. In some situations actively encouraging unpopular, risky science would improve scientific outcomes.
While the popular image of scientists portrays them as objective, dispassionate observers of nature, actual scientists rarely are. It is not really known to what extent these individual departures from the scientific ideal effects the reliability of the scientific community. This paper suggests a number of concrete projects which help to determine this relationship.
Journals regulate a significant portion of the communication between scientists. This paper devises an agent-based model of scientific practice and uses it to compare various strategies for selecting publications by journals. Surprisingly, it appears that the best selection method for journals is to publish relatively few papers and to select those papers it publishes at random from the available ``above threshold'' papers it receives. This strategy is most effective at maintaining an appropriate type of diversity which is needed to solve a particular type of scientific problem. This problem and the limitation of the model is discussed in detail.
There is growing interest in understanding and eliciting division of labor within groups of scientists. This paper illustrates the need for this division of labor through a historical example, and a formal model is presented to better analyze situations of this type. Analysis of this model reveals that a division of labor can be maintained in two different ways: by limiting information or by endowing the scientists with extreme beliefs. If both features are present however, cognitive diversity is maintained indefinitely, and as a result agents fail to converge to the truth. Beyond the mechanisms for creating diversity suggested here, this shows that the real epistemic goal is not diversity but transient diversity.
PressIncreasingly, epistemologists are becoming interested in social structures and their effect on epistemic enterprises, but little attention has been paid to the proper distribution of experimental results among scientists. This paper will analyze a model first suggested by two economists, which nicely captures one type of learning situation faced by scientists. The results of a computer simulation study of this model provide two interesting conclusions. First, in some contexts, a community of scientists is, as a whole, more reliable when its members are less aware of their colleagues' experimental results. Second, there is a robust trade-off between the reliability of a community and the speed with which it reaches a correct conclusion.
Animal signals, while informative, are unlikely to be entirely reliable. Models of such partially honest communication have traditionally taken the form of ‘honest-enough’ signalling, in which a subset of signallers can signal at lower cost and therefore exaggerate their perceived ability or condition. Although support for these models has been demonstrated, alternatives are rarely tested in nature. Recent theory has highlighted an alternative model that also results in partial reliability, yet functions through a different mechanism. In so-called hybrid equilibria, all signallers pay the same costs given their condition, yet low-quality signallers sometimes spoof the high-quality signal, which receivers sometimes heed and sometimes ignore. Although theoretically well established, documentation of hybrid equilibria in nature is rare. Here, using previously collected behavioural data from the field and literature, we detail a game-theoretic model based on the natural history of hummingbirds. We demonstrate that an unusual female plumage polymorphism found in these birds is best explained as a hybrid equilibrium. In addition to explaining the persistence of polymorphism, the model also offers testable parameters that may predict the wide range of sex variation in plumage found across hummingbirds and other taxa, including bright and dull monomorphism and sexual dimorphism. Ultimately, our findings show that intersexual mimicry can be modelled as a hybrid equilibrium, that hybrid signals likely exist in nature, and that there is the need for a greater diversity of models to explain stable communication.
Communication via evolved signals is ubiquitous (both within and between species) in the natural world. However, how honest we should expect signals to be remains an open question. Hybrid equilibria are a form of equilibria predicted by discrete signaling games in which signalers are sometimes dishonest and signals do not completely reliably convey information on signaler quality. While these equilibria have been theoretically demonstrated in several signaling games, their dynamics in a stochastic simulation of evolutionary trajectories (that include representation of the inherent noise expected in evolution in the natural world) have not previously been studied. In this paper, we present an agent-based simulation of a discrete signaling game which exhibits hybrid equilibria. We find that while hybrid equilibria are evolutionarily attractive where they exist, populations exhibit variable and often drastic oscillating behavior around the predicted equilibrium values. We discuss how these dynamics might offer valuable opportunity for detecting hybrid equilibria in natural populations.
This paper examines and contrasts two closely related evolutionary explanations in human behaviour: signalling theory, and the theory of Credibility Enhancing Displays (CREDs). Both have been proposed to explain costly, dangerous, or otherwise ‘extravagant’ social behaviours, especially in the context of religious belief and practice, and each have spawned significant lines of empirical research. However, the relationship between these two theoretical frameworks is unclear, and research which engages both of them (especially in systematic comparison) is largely absent. In this paper we seek to address this gap at the theoretical level, examining the core differences between the two approaches and prospects and conditions for future empirical testing. We clarify the dynamical and mechanistic bases of signalling and CREDs as explanatory models and contrast the previous uses to which they have been put in the human sciences. Because of idiosyncrasies regarding those uses (especially with signalling), several commonly supposed differences and comparative advantages are actually misleading and not in fact generalisable. We also show that signalling and CREDs theories as explanatory models are not interchangeable (or reducible to one another), because of deep structural differences. As we illustrate, the proposed causal networks of each theory are distinct, with important differences in the endogeneity of various phenomena within each model and their explanatory targets. As a result, they can be seen as complementary rather than in competition. We conclude by surveying the current state of the literature and identifying the differential predictions which could underpin more comprehensive empirical comparison in future research.
The concept of fitness is central to evolutionary biology. Models of evolutionary change typically use some quantity called “fitness” which measures an organism’s reproductive success. But what exactly does it mean that fitness is such a measure? In what follows, we look at the interplay between abstract evolutionary models and quantitative measures of fitness and develop a measurement-theoretic perspective on fitness in order to explore what makes certain measures of fitness significant.
Signals without Teleology with Carl Bergstrom and Simon Huttegger Studies in History and Philosophy of Science Part C
"Signals" are a conceptual apparatus in many scientific disciplines. Biologists inquire about the evolution of signals, economists talk about the signaling function of purchases and prices, and philosophers discuss the conditions under which signals acquire meaning. However, less attention has been paid to what is a signal. Most existing accounts are teleological in some way. This paper provides a definition of signals that avoids reference to form or purpose. Along the way we introduce novel notions of "information revealing" and "information concealing" moves in games. In the end, our account offers an alternative to teleological accounts of communication.
In this paper, we develop the notion of a natural convention, and illustrate its usefulness in a detailed examination of indirect requests in English. Our treatment of convention is grounded in Lewis’s (1969) seminal account; we do not here redefine convention, but rather explore the space of possibilities within Lewis’s definition, highlighting certain types of variation that Lewis de-emphasized. Applied to the case of indirect requests, which we view through a Searlean lens, the notion of natural convention allows us to give a nuanced answer to the question: Are indirect requests conventional? In conclusion, we reflect on the consequences of our view for the understanding of the semantics/pragmatics divide.
In the study of signaling, it is well known that the cost of deception is an essential element for stable honest signaling in nature. In this paper, we show how costs for deception can arise endogenously from repeated interactions between individuals. Utilizing the Sir Philip Sidney game as an illustrative case, we show that repeated interactions can sustain honesty with no observable signal costs, even when deception cannot be directly observed. We provide a number of potential experimental tests for this theory which distinguish it from the available alternatives.
Recent work on costly signaling games has identified new Nash equilibria in addition to the standard costly signaling equilibrium as a possible explanation for signaling behavior. These so-called hybrid equilibria are Liapunov stable, but not asymptotically stable for the replicator dynamics. Since some eigenvalues of the hybrid equilibria have zero real part, this result is not structurally stable. The purpose of this paper is to show that under one reasonable perturbation of the replicator dynamics—the selection–mutation dynamics—rest points close to the hybrid equilibrium exist and are asymptotically stable. Moreover, for another plausible version of the replicator dynamics—Maynard Smith’s adjusted replicator dynamics—the same is true. This reinforces the significance of hybrid equilibria for signaling.
The handicap principle has come under significant challenge both from empirical studies and from theoretical work. As a result, a number of alternative explanations for honest signaling have been proposed. This paper compares the evolutionary plausibility of one such alternative, the “hybrid equilibrium,” to the handicap principle. We utilize computer simulations to compare these two theories as they are instantiated in Maynard Smith’s Sir Philip Sidney game. We conclude that, when both types of communication are possible, evolution is unlikely to lead to handicap signaling and is far more likely to result in the partially honest signaling predicted by hybrid equilibrium theory.
Game theory has a prominent role in evolutionary biology, in particular in the ecological study of various phenomena ranging from conflict behavior to altruism to signaling and beyond. The two central methodological tools in biological game theory are the concepts of Nash equilibrium and Evolutionarily Stable Strategy(ESS). While both were inspired by a dynamic conception of evolution, these concepts are essentially static -- they only show that a population is uninvadable, but not that a population is likely to evolve. In this paper we argue that a static methodology can lead to misleading views about a dynamic evolutionary processes. Instead, we advocate a more pluralistic methodology, which includes both static and dynamic game theoretic tools. Such an approach provides a more complete picture of the evolution of strategic behavior.
The handicap principle is one of the most influential ideas in evolutionary biology. It asserts that when there is conflict of interest in a signaling interaction signals must be costly in order to be reliable. We show how the handicap principle is a limiting case of honest signaling, which can also be sustained by other mechanisms. This fact has gone unnoticed because in evolutionary biology it is a common practice to distinguish between cues, indexes and fakable signals, where cues provide information but are not signals and indexes are signals that cannot be faked. We find that the dichotomy between indexes and fakable signals is an artifact of the existing signaling models. Our results suggest that one cannot adequately understand signaling behavior by focusing solely on cost. Under our reframing, cost becomes one -- and probably not the most important -- of a collection of factors preventing deception.
The Limits of ESS Methodology (with Simon Huttegger) in (Samir Okasha and Ken Binmore, eds.) Evolution and Rationality: Decisions, Cooperation, and Strategic Behavior
In this paper we show that there are certain limits as to what applications of Maynard Smith's concept of evolutionarily stable strategy (ESS) can tell us about evolutionary processes. We shall argue that ESS is very similar in spirit to a particular branch of rational choice game theory, namely, the literature on refinements of Nash equilibrium. In the first place, ESS can also be viewed as a Nash equilibrium refinement. At a deeper level, ESS shares a common structure with other rational choice equilibrium refinements. An equilibrium is evaluated according to whether it persists under specific kinds of perturbations. In the case of ESS, these perturbations are mutations. However, from a dynamical point of view, focusing exclusively on perturbations of equilibria provides only a partial account of the system under consideration. We will show that this has important consequences when it comes to analyzing game-theoretic models of evolutionary processes. In particular, there are non-ESS states which are significant for evolutionary dynamics.
Costly signaling theory has become a common explanation for honest communication when interests conflict. In this paper, we provide an alternative explanation for partially honest communication that does not require significant signal costs. We show that this alternative is at least as plausible as traditional cost signaling, and we suggest a number of experiments that might be used to distinguish the two theories.
We study a low-rationality learning dynamics called probe and adjust. Our emphasis is on its properties in games of information transfer such as the Lewis signaling game or the Bala-Goyal network game. These games fall into the class of weakly better reply games, in which, starting from any action profile, there is a weakly better reply path to a strict Nash equilibrium. We prove that probe and adjust will be close to strict Nash equilibria in this class of games with arbitrarily high probability. In addition, we compare these asymptotic properties to short-run behavior.
We study the handicap principle in terms of the Sir Philip Sidney game. The handicap principle asserts that cost is required to allow for honest signalling in the face of conflicts of interest. We show that the significance of the handicap principle can be challenged from two new directions. Firstly, both the costly signalling equilibrium and certain states of no communication are stable under the replicator dynamics (i.e. standard evolutionary dynamics); however, the latter states are more likely in cases where honest signalling should apply. Secondly, we prove the existence and stability of polymorphisms where players mix between being honest and being deceptive and where signalling costs can be very low. Neither the polymorphisms nor the states of no communication are evolutionarily stable, but they turn out to be more important for standard evolutionary dynamics than the costly signalling equilibrium.
The Handicap Principle represents a central theory in the biological understanding of signaling. This paper presents a number of alternative theories to the Handicap Principle and argues that some of these theories may provide a better explanation for the evolution and stability of honest communication.
Most contemporary accounts of meaning utilize some notion of the intentions of the speaker and or hearer. In this paper I develop an account of the distinction between directives and assertions which does not require that the speakers have intentions. Instead, this account relies on behavioral differences modeled as different strategies in an appropriately defined game.
In recent years, many scholars have suggested that the Baldwin effect may play an important role in the evolution of language. However, the Baldwin effect is a multifaceted and controversial process and the assessment of its connection with language is difficult without a formal model. This paper provides a first step in this direction. We examine a game-theoretic model of the interaction between plasticity (represented by Herrnstein reinforcement learning) and evolution in the context of a simple language game. Additionally, we describe three distinct aspects of the Baldwin effect: the Simpson-Baldwin effect, the Baldwin expediting effect and the Baldwin optimizing effect. We find that a simple model of the evolution of language lends theoretical plausibility to the existence of the Simpson-Baldwin and the Baldwin optimizing effects in this arena, but not the Baldwin expediting effect.
Recent research into the evolution of higher cognition has piqued an interest in the effect of natural selection on the ability of creatures to respond to their environment (behavioral plasticity). It is believed that environmental variation is required for plasticity to evolve in cases where the ability to be plastic is costly. We investigate one form of environmental variation: frequency dependent selection. Using tools in game theory, we investigate a few models of plasticity and outline the cases where selection would be expected to maintain it. Ultimately we conclude that frequency dependent selection is likely insufficient to maintain plasticity given reasonable assumptions about its costs. This result is very similar to one aspect of the well-discussed Baldwin effect, where plasticity is first selected for and then later selected against. We show how in these models one would expect plasticity to grow in the population and then be later reduced. Ultimately we conclude that if one is to account for the evolution of behavioral plasticity in this way, one must appeal to a very particular sort of external environmental variation.
Transfer of information between senders and receivers, of one kind or another, is essential to all life. David Lewis introduced a game theoretic model of the simplest case, where one sender and one receiver have pure common interest. How hard or easy is it for evolution to achieve information transfer in Lewis signaling?. The answers involve surprising subtleties. We discuss some if these in terms of evolutionary dynamics in both finite and infinite populations, with and without mutation.
Lewis signaling games illustrate how language might evolve from random behavior. The probability of evolving an optimal signaling language is, in part, a function of what learning strategy the agents use. Here we investigate three learning strategies, each of which allows agents to forget old experience. In each case, we find that forgetting increases the probability of evolving an optimal language. It does this by making it less likely that past partial success will continue to reinforce suboptimal practice. The learning strategies considered here show how forgetting past experience can promote learning in the context of games with suboptimal equilibria.
In seeking to explain the evolution of social cooperation, many scholars are using increasingly complex game-theoretic models. These complexities often model readily observable features of human and animal populations. In the case of previous games analyzed in the literature, these modifications have had radical effects on the stability and efficiency properties of the models. We will analyze the effect of adding spatial structure to two communication games: the Lewis Sender-Receiver game and a modified Stag Hunt game. For the Stag Hunt, we find that the results depart strikingly from previous models. In all cases, the departures increase the explanatory value of the models for social phenomenon.
The idea that there is a fundamental difference in value between persons and things and that respecting this difference is an important moral requirement has strong intuitive appeal. Kantian ethics is unique in placing this requirement at the center of a moral system and for explicating the conditions for complying with it. Unlike challenges to Kantian ethics that focus on tragic cases that pit respect for one person against respect for another, this paper focuses on the question of how we can respect the value distinction between persons and things under conditions of uncertainty. After exploring why decision making under uncertainty is a neglected topic among Kantians and demonstrating how uncertainty challenges our ability to comply with this norm, we propose a notion of morally insignificant risk within a framework that allows agents to navigate real world decisions involving material benefit and some risk to dignity without violating the Kantian’s core commitments. We conclude by exploring some of the challenges facing this approach.
The Computational Philosophy: Simulation as a Core Philosophical Method with Conor Mayo-Wilson Synthese (free version) Modeling and computer simulations, we claim, should be considered core philosophical methods. More precisely, we will defend two theses. First, philosophers should use simulations for many of the same reasons we currently use thought experiments. In fact, simulations are superior to thought experiments in achieving some philosophical goals. Second, devising and coding computational models instill good philosophical habits of mind. Throughout the paper, we respond to the often implicit objection that computer modeling is “not philosophical.”
Flipping a coin to decide what to do is a common feature of everyday life. Mixed strategies, as these are called, have a thorny status in normative decision theories. This paper explores various ways to justify choosing one's actions at random. I conclude that it is hard to make sense of this behavior without dealing with some difficult consequences.
The idea that there is a fundamental difference in value between persons and things and that respecting this difference is an important moral requirement has strong intuitive appeal. Kantian ethics is unique in placing this requirement at the center of a moral system and for explicating the conditions for complying with it. Unlike challenges to Kantian ethics that focus on tragic cases that pit respect for one person against respect for another, this paper focuses on the question of how we can respect the value distinction between persons and things under conditions of uncertainty. After exploring why decision making under uncertainty is a neglected topic among Kantians and demonstrating how uncertainty challenges our ability to comply with this norm, we propose a notion of morally insignificant risk within a framework that allows agents to navigate real world decisions involving material benefit and some risk to dignity without violating the Kantian’s core commitments. We conclude by exploring some of the challenges facing this approach.
In this paper we distinguish two competing conceptions of dignity, one recognizably Hobbesian and one recognizably Kantian. We provide a formal model of how decision makers committed to these conceptions of dignity might reason when engaged in an economic transaction that is it not inherently insulting, but in which it is possible for the dignity of the agent to be called into question. This is a modified version of the ultimatum game. We then use this model to illustrate ways in which the Kantian evaluative standpoint enjoys a kind of internal stability that the Hobbesian framework lacks. Our interpersonal argument shows that, under certain conditions, Hobbesians prefer to cultivate Kantian commitments in others and promote the presence of Kantians in the population. Our intrapersonal argument shows that agents who are conflicted between Kantian and Hobbesian commitments have powerful reasons not to resolve this commitment in favour of Hobbesian values. Our emulation argument illustrates that in repeated versions of the ultimatum game, the Hobbesian chooses to behave like a Kantian, including publicly repudiating her Hobbesian commitments. Here again, however, the Hobbesian is able to achieve a desired benefit only on the condition that there are genuine Kantians in the population. Finally, our social planning argument explores the reasons that a community of Hobbesians would opt to enshrine a Kantian conception of dignity into law. The paper concludes with some remarks about the policy implications of this work.
The "fair benefits" approach to international research is designed to produce results that all can agree are fair without taking a stand on divisive questions of justice. But its appealing veneer of collaboration masks ambiguities at both a conceptual and an operational level. An attempt to put it into practice would look a lot like an auction, leaving little reason to think the outcomes will satisfy even minimal conditions of fairness.
This paper presents the evolutionary dynamics of three games: Nash Bargaining game, the Ultimatum Game, and a hybrid of the two. One might expect that the probability that some behavior evolves in an environment with two games would be near the probability that the same behavior evolves in either game alone. This is not the case for the Ultimatum and Nash Bargaining Games. Fair behavior is more likely to evolve in a combined game than in either game taken individually. This result confirms a conjecture that the complexity of our actual environment provides an explanation for the evolution of fair behavior.
In this article, we aim to illustrate evolutionary explanations for the emergence of framing effects, discussed in detail in Cristina Bicchieri’s The Grammar of Society. We show how framing effects might evolve which coalesce two economically distinct interactions into a single one, leading to apparently irrational behavior in each individual interaction. Here we consider the now well-known example of the ultimatum game, and show how this "irrational" behavior might result from a single norm which governs behavior in multiple games. We also show how framing effects might result in radically different play in strategically identical situations. We consider the Hawk-Dove game (the game of chicken) and also the Nash bargaining game. Here arbitrary tags or signals might result in one party doing better than another.