Predicting terrorist attacks with prediction markets has been accused of being immoral. While some of these concerns are about the likely effectiveness of prediction markets on terrorism (PMsoT), this paper discusses the three main reasons why even effective prediction markets on terrorism might be considered immoral. We argue that these three reasons establish only that PMsoT cause offense and/or fleeting mild harm, and that, even taken together, they do not constitute serious harm. (...) The moral issues considered are that PMsoT: 1) create character-affecting perverse incentives, 2) desensitise society to tragic events, and 3) disrespect important ideals. In addition to arguing against the force of these three potential moral problems, it is also argued that societies and governments already endorse intelligence-gathering methods that are clearly more immoral than PMsoT in the relevant respects. We also argue that some circumstances require governments to cause non-serious harm to some people in order to protect and promote the rights and welfare of its citizens. We conclude that a government’s obligation to protect and promote the rights and welfare of its citizens outweighs the non-serious harm that could be caused by effective PMsoT. As a result, we recommend that the likelihood of PMsoT being effective is investigated more closely. (shrink)

Real-world policy decisions involve trade-offs. Sometimes the trade-offs involve both the efficacy and morality of potential policies. In this chapter, the morality and likely efficacy of hiring one more spy to help anti-terrorist intelligence gathering efforts is compared to the morality and likely efficacy of implementing a prediction market on terrorism. Prediction markets on terrorism allow registered traders to buy and sell shares in predictions about terrorism-related real-world events. The comparison at the heart of (...) this chapter is based on the assumption that it would cost about $5 million to bankroll the prediction market project, or to establish another spy, including equipment and head office support, for 15 years. The comparison reveals that implementing a prediction market on terrorism is likely to be more efficacious and less morally problematic than hiring one more spy. (shrink)

Prediction markets designed to predict terrorism through traders’ investments on the likelihood of specific terrorist attacks are, strictly speaking, enabling those traders to bet on terrorism. Betting on terrorist attacks, like some other forms of betting on death, has been accused of being repugnant. In this paper, it is argued that while government-backed effective intelligence-gathering prediction markets on terrorism (PMsoT) might elicit feelings of repugnance, those feelings are likely to be misguided. The feelings (...) of repugnance arise because PMsoT are assumed to be associated with terrorism in encouraging and endorsing ways and with human death in a disrespectful way. However, it is argued that these feelings of repugnance are misguided in the case of government-backed effective intelligence-gathering PMsoT because the purpose and effect of such prediction markets, and (on balance) the trading they encourage, is to prevent and renounce terrorism and show respect for matters of life and death. (shrink)

This paper analyzes the proposed use of combinatorial derivatives markets for event prediction, especially for catastrophic events such as terrorism, war, or political assasination. Following a presentation of the philosophical principles underlying these politico-economic tools, I examine case studies (U.S. DoD proposals) that evaluate their advantages and disadvantages in terms of both efficacy and moral considerations. I conclude that these markets are both fatally flawed due to internal conceptual contradictions and morally problematic.

Prediction markets, which trade contracts based on the results of predictions, have been remarkably successful in predicting the results of political events. A number of proposals have been made to extend prediction markets to scientific questions, and some small-scale science prediction markets have been implemented. Advocates for science prediction markets argue that they could alleviate problems in science such as bias in peer review and epistemically unjustified consensus. I argue that bias in (...) peer review and epistemically unjustified consensuses are genuine problems in science, and that current attempts to solve them fail in practical circumstances. Prediction markets do show some promise for answering scientific questions while avoiding the pitfalls of consensus and peer review. However, there are strong reasons to believe that science prediction markets will not perform nearly so well as election prediction markets, and implementing prediction markets on a large scale could have significant unintended consequences for the organization of scientific research. The promise of prediction markets to solve current problems in assessing scientific claims is therefore largely illusory. (shrink)

Prediction markets are low volume speculative markets whose prices offer informative forecasts on particular policy topics. Observers worry that traders may attempt to mislead decision makers by manipulating prices. We adapt a Kyle-style market microstructure model to this case, adding a manipulator with an additional quadratic preference regarding the price. In this model, when other traders are uncertain about the manipulator’s target price, the mean target price has no effect on prices, and increases in the variance of (...) the target price can increase average price accuracy, by increasing the returns to informed trading and thereby incentives for traders to become informed. (shrink)

In this paper, prediction markets that encourage traders to bet on matters of life and death are used to explore the varieties and dynamics of moral repugnance. We define moral repugnance as morally charged feelings of revulsion that correspond (correctly, incorrectly, and indeterminately) to moral reasons and contexts. Rich variations of moral repugnance and their dynamic qualities are presented by investigating the contextual frames in which they arise. These contextual frames constitute interacting conditions composed of information about states (...) of affairs, moral reasons, and feelings of revulsion. Through careful study of two medical prediction markets that encourage betting on death, we can observe the interaction between these causal conditions to see how the varieties of moral repugnance emerge. We also present three interesting results that arise from analyzing the dynamics of moral repugnance in response to prediction markets. First, a prediction market can elicit several conflicting types of moral repugnance at the same time. Second, moral indeterminacy can arise in two different ways when judging prediction markets. Finally, some prediction markets can generate a moral endogeneity problem, a disruptive feedback loop between a given prediction market and the morally relevant outcome it predicts. (shrink)

We study the equilibrium behavior of informed traders interacting with market scoring rule (MSR) market makers. One attractive feature of MSR is that it is myopically incentive compatible: it is optimal for traders to report their true beliefs about the likelihood of an event outcome provided that they ignore the impact of their reports on the profit they might garner from future trades. In this paper, we analyze non-myopic strategies and examine what information structures lead to truthful betting by traders. (...) Specifically, we analyze the behavior of risk-neutral traders with incomplete information playing in a dynamic game. We consider finite-stage and infinite-stage game models. For each model, we study the logarithmic market scoring rule (LMSR) with two different information structures: conditionally independent signals and (unconditionally) independent signals. In the finite-stage model, when signals of traders are independent conditional on the state of the world, truthful betting is a Perfect Bayesian Equilibrium (PBE). Moreover, it is the unique Weak Perfect Bayesian Equilibrium (WPBE) of the game. In contrast, when signals of traders are unconditionally independent, truthful betting is not a WPBE. In the infinite-stage model with unconditionally independent signals, there does not exist an equilibrium in which all information is revealed in a finite amount of time. We propose a simple discounted market scoring rule that reduces the opportunity for bluffing strategies. We show that in any WPBE for.. (shrink)

This essay argues that prediction markets, as one approach for aggregating dispersed private information, may not only be praised for their epistemic accuracy. They also feature characteristics that are morally desirable from the point of view of epistemic justice. Notably, they are a promising approach when we are trying to address testimonial injustice. The impersonality of market transactions effectively tackles the issue of identity prejudice, which underlies many forms of testimonial injustice. This is not to say that (...) class='Hi'>prediction markets do not pose challenges for epistemic justice of their own like the risk of excluding knowers based on ability to pay. Or, in light of identity prejudice’s systematicity, the risk of discouraging some knowers because of differences in education or social background that lead to a certain unease when faced with prediction markets. The essay discusses these challenges, concedes limitations but also offers countermeasures to certain worries – e.g. hosting prediction markets on a play-money basis. Throughout, the essay addresses the question of the potential scope of using prediction markets for epistemic purposes, notably by means of the practical example of a prediction market for monetary policy. (shrink)

For multiple reasons, deliberating groups often converge on falsehood rather than truth. Individual errors may be amplified rather than cured. Group members may fall victim to a bad cascade, either informational or reputational. Deliberators may emphasize shared information at the expense of uniquely held information. Finally, group polarization may lead even rational people to unjustified extremism. By contrast, prediction markets often produce accurate results, because they create strong incentives for revelation of privately held knowledge and succeed in aggregating (...) widely dispersed information. The success of prediction markets offers a set of lessons for increasing the likelihood that groups can obtain the information that their members have. (shrink)

For multiple reasons, deliberating groups often converge on falsehood rather than truth. Individual errors may be amplified rather than cured. Group members may fall victim to a bad cascade, either informational or reputational. Deliberators may emphasize shared information at the expense of uniquely held information. Finally, group polarization may lead even rational people to unjustified extremism. By contrast, prediction markets often produce accurate results, because they create strong incentives for revelation of privately held knowledge and succeed in aggregating (...) widely dispersed information. The success of prediction markets offers a set of lessons for increasing the likelihood that groups can obtain the information that their members have. (shrink)

For multiple reasons, deliberating groups often converge on falsehood rather than truth. Individual errors may be amplifi ed rather than cured. Group members may fall victim to a bad cascade, either informational or reputational. Deliberators may emphasize shared information at the expense of uniquely held information. Finally, group polarization may lead even rational people to unjustifi ed extremism. By contrast, prediction markets often produce accurate results, because they create strong incentives for revelation of privately held knowledge and succeed (...) in aggregating widely dispersed information. The success of prediction markets off ers a set of lessons for increasing the likelihood that groups can obtain the information that their members have. (shrink)

This paper focuses on the conception and use of machine-learning algorithms for marketing. In the last years, specialized service providers as well as in-house data scientists have been increasingly using machine learning to predict consumer behavior for large companies. Predictive marketing thus revives the old dream of one-to-one, perfectly adjusted selling techniques, now at an unprecedented scale. How do predictive marketing devices change the way corporations know and model their customers? Drawing from STS and the sociology of quantification, I propose (...) to study the original ambivalence that characterizes the promise of a mass personalization, i.e. algorithmic processes in which the precise adjustment of prediction to unique individuals involves the computation of massive datasets. By studying algorithms in practice, I show how the active embedding of local preexisting consumer knowledge and punctual de-personalization mechanisms are keys to the epistemic and organizational success of predictive marketing. This paper argues for the study of algorithms in their contexts and suggests new perspectives on algorithmic objectivity. (shrink)

May you sell your vote? May you sell your kidney? May gay men pay surrogates to bear them children? May spouses pay each other to watch the kids, do the dishes, or have sex? Should we allow the rich to genetically engineer gifted, beautiful children? Should we allow betting markets on terrorist attacks and natural disasters? Most people shudder at the thought. To put some goods and services for sale offends human dignity. If everything is commodified , then nothing (...) is sacred. The market corrodes our character. Or so most people say. In Markets without Limits , Jason Brennan and Peter Jaworski give markets a fair hearing. The market does not introduce wrongness where there was not any previously. Thus, the authors claim, the question of what rightfully may be bought and sold has a simple answer: if you may do it for free, you may do it for money. Contrary to the conservative consensus, they claim there are no inherent limits to what can be bought and sold, but only restrictions on how we buy and sell. (shrink)

The Myth of Martyrdom: What Really Drives Suicide Bombers, Rampage Shooters, and Other Self-Destructive Killersproposes that suicide terrorists are psychologically and behaviorally similar to other people who commit suicide, due to a range of individual, social, and situational factors. Some commentators agree, while others are skeptical, given the lack of information about many attackers' lives. However, the book's position is not simply based on individual case studies; it is also supported by other independent assessments, the confirmation of empirical predictions, the (...) paucity of contradictory evidence, and new applications of evolutionary theory. It is undisputed that human beings behave as the author suggests; it is unknown if they behave as the conventional wisdom suggests. Those who argue that suicide terrorists are psychologically normal and altruistically sacrificing their lives for an ideological cause should bear the burden of proof for those claims. (shrink)

We present experimental data on a simple market game. Several solution concepts from cooperative game theory are applied to predict the observed payoff distributions. Notably, a recently introduced solution concept meant to capture the influence of outside options on the payoff distribution within groups fares better than most other solution concepts under consideration. Our results shed some light on the effects of scarcity relations on markets on bargaining outcomes within negotiating dyads.

With the progress of social production, the competition for talents among enterprises is fierce, and the market often lacks capable leaders, which leads to the lack of management of enterprise employees and cannot bring more economic benefits to enterprises. Traditional leaders make subordinate employees work actively and achieve the common goal of the enterprise by exerting their own leadership characteristics and observing their subordinates, but they cannot take care of the psychological state of each employee, resulting in the employee's work (...) efficiency is not very high. In recent years, charismatic leadership has become an important economic leader in the new era, and the theoretical spirit of charismatic leadership can well guide employees to work actively. Artificial intelligence affective computing can well identify the psychological state of the subject, and the combination of artificial intelligence affective computing and charismatic leadership can achieve effective management of employees through the predictive analysis of employees' psychological state. This paper compares the psychological state prediction analysis of employees' work attitudes between charismatic leaders based on artificial intelligence affective computing and traditional leaders through experiments. The results show that: charismatic leaders based on artificial intelligence affective computing predictive analytics can improve sensitivity to employee needs, resulting in an 8.2% increase in employee trust in leadership, a 4.4% increase in employee commitment to achieving organizational goals, and a 19.3% increase in employee job satisfaction. The psychological state prediction analysis of charismatic leaders based on artificial intelligence affective computing on employees' work attitudes can improve the work efficiency of employees and the economic benefits of enterprises. (shrink)

Product market competitiveness is positively influenced by the aesthetic value of product form, which is closely related to product complexity. By measuring the cognitive complexity of the product, this research establishes the relationship between the complexity and aesthetics of the product using an artificial neural network. Hence the prediction of product beauty is achieved, which guides design decisions. In this article, the complexity of product form is first measured through a combination of hesitant-fuzzy theory and information axiom. Afterward, the (...) result is weighted by exponential entropy and dimensionally compressed. This method makes data more suitable for the prediction with small samples, obtaining an accuracy improvement of up to 40% compared with traditional approaches. Finally, the importance order of the design elements which affect morphological complexity is acquired. Results show that three of the six complexity features are more significant, impacting the aesthetic feeling of product form. The method increases the attractiveness of products to customers, providing valuable design support for enterprises and designers in the early days when a new product is designed, and reducing research and development risks. (shrink)

This study investigates the volatility risk premium on the emerging financial market. We also consider the expected return and ESG sentiment. Based on the SSE 50 ETF 5-minute high-frequency spots and daily options data from 2016 to 2021, we adopt nonparametric model-free approaches to calculate realized and implied volatilities. And the volatility risk premium is constructed by subtracting these volatility series. We examine the relations between the volatility risk premium and future excess returns as well as ESG sentiment through multifactor (...) specifications. We find that the volatility risk premium also exists in the Chinese market and is significantly negative. In addition, the statistically positive correlation between the volatility risk premium and aggregate returns is an outlier compared to the empirically negative pattern in developed markets. At last, ESG sentiment is positively associated with the volatility risk premium, especially the impact of environmental and social. This evidence supports the agency theory, which indicates that investors perceive ESG investments as waste resources in a short term and become potentially risky. (shrink)

As a brand-new marketing method, network marketing has gradually become one of the main ways and means for enterprises to improve profitability and competitiveness with its unique advantages. Using these marketing data to build a model can dig out useful information that the business is concerned about, and the company can then formulate marketing strategies based on this information. Sales forecasting is to speculate on the future based on historical sales. It is a tool for companies to determine production volume (...) and ensure the balance of product supply and sales. It can help companies make correct business decisions to maximize profits. The neural network can approximate the nonlinear function with arbitrary precision, and the time series prediction model based on the neural network can well reflect the nonlinear development trend of information. Based on the analysis of the shortcomings of the traditional BP network, this paper uses a genetic algorithm with good global search capabilities to improve the neural network. The thought and theory of optimizing the initial weight and threshold of the neural network of the GA algorithm are discussed in detail. While expounding the forecasting method, it uses specific examples to analyze the performance and characteristics of the GA-BP network in the enterprise network marketing forecasting. The results show that the GA-BP neural network is higher than the traditional BP neural network in terms of prediction accuracy and adaptability. (shrink)

This paper addresses the recent rise of the use of alternative medicine in Western countries. It offers a novel explanation of that phenomenon in terms of cognitive and economic factors related to the free-market and patient-centric approach to medicine that is currently in place in those countries, in contrast to some alternative explanations of this phenomenon. Moreover, the paper addresses this troubling trend in terms of the serious harms associated with the use of alternative medical modalities. The explanatory theory defended (...) here is then predicated on the idea that an extreme patient-centric model of medical practice that treats largely ignorant patients as consumers of medical products and services endowed with an essentially unrestricted power of freedom to choose treatments predictably leads serious and avoidable harms. Some important moral and epistemological consequences of this model are then articulated and corrective measures are suggested. (shrink)

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behaviour change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behaviour change scale. Structural equation modelling examined three progressive (...) models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behaviour change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behaviour change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behaviour change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behaviour change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behaviour change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behaviour change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. (shrink)

An implicit ambiguity in the field of prediction-based decision-making concerns the relation between the concepts of prediction and decision. Much of the literature in the field tends to blur the boundaries between the two concepts and often simply refers to ‘fair prediction’. In this paper, we point out that a differentiation of these concepts is helpful when trying to implement algorithmic fairness. Even if fairness properties are related to the features of the used prediction model, what (...) is more properly called ‘fair’ or ‘unfair’ is a decision system, not a prediction model. This is because fairness is about the consequences on human lives, created by a decision, not by a prediction. In this paper, we clarify the distinction between the concepts of prediction and decision and show the different ways in which these two elements influence the final fairness properties of a prediction-based decision system. As well as discussing this relationship both from a conceptual and a practical point of view, we propose a framework that enables a better understanding and reasoning of the conceptual logic of creating fairness in prediction-based decision-making. In our framework, we specify different roles, namely the ‘prediction-modeler’ and the ‘decision-maker,’ and the information required from each of them for being able to implement fairness of the system. Our framework allows for deriving distinct responsibilities for both roles and discussing some insights related to ethical and legal requirements. Our contribution is twofold. First, we offer a new perspective shifting the focus from an abstract concept of algorithmic fairness to the concrete context-dependent nature of algorithmic decision-making, where different actors exist, can have different goals, and may act independently. In addition, we provide a conceptual framework that can help structure prediction-based decision problems with respect to fairness issues, identify responsibilities, and implement fairness governance mechanisms in real-world scenarios. (shrink)

In _René Girard and Secular Modernity: Christ, Culture, and Crisis_, Scott Cowdell provides the first systematic interpretation of René Girard’s controversial approach to secular modernity. Cowdell identifies the scope, development, and implications of Girard’s thought, the centrality of Christ in Girard's thinking, and, in particular, Girard's distinctive take on the uniqueness and finality of Christ in terms of his impact on Western culture. In Girard’s singular vision, according to Cowdell, secular modernity has emerged thanks to the Bible’s exposure of the (...) cathartic violence that is at the root of religious prohibitions, myths, and rituals. In the literature, the psychology, and most recently the military history of modernity, Girard discerns a consistent slide into an apocalypse that challenges modern ideas of romanticism, individualism, and progressivism._ In the first three chapters, Cowdell examines the three elements of Girard’s basic intellectual vision and brings this vision to a constructive interpretation of “secularization” and “modernity,” as these terms are understood in the broadest sense today. Chapter 4 focuses on modern institutions, chiefly the nation state and the market, that function to restrain the outbreak of violence. And finally, Cowdell discusses the apocalyptic dimension of Girard's theory in relation to modern warfare and terrorism. Here, Cowdell engages with the most recent writings of Girard and applies them to further conversations in cultural theology, political science, and philosophy. Cowdell takes up and extends Girard’s own warning concerning an alternative to a future apocalypse: “What sort of conversion must humans undergo, before it is too late?” "Scott Cowdell's book is the first comprehensive study of modernity and secularity in René Girard's thought. Cowdell brings Girard's theory into a fruitful dialogue with leading approaches on secularization like those of Max Weber, Hans Blumenberg, Peter Berger, and Charles Taylor. Scholars and students of theology, philosophy, and sociology will benefit from this wide-ranging overview of the relationship between religion, modernity, and secularization." — Wolfgang Palaver, Institute of Systematic Theology, University of Innsbruck __ "In a stunning analysis, Cowdell shows that Girard’s sustained intellectual pursuit, which began in the 1960s with his mimetic analysis of modern realist fiction, has always been about the religiosity of the modern and postmodern social condition, even when it has dealt explicitly with the religious origins of antique culture. Cowdell demonstrates the 'highly explanatory and predictive' quality of Girard’s cultural anthropology, within which the 'secular' does not escape the 'religious.' This is a powerful book." — Ann W. Astell, University of Notre Dame __ "Scott Cowdell is one of the most interesting theological voices of his generation. The themes in Cowdell's work are always cosmic and vast in scope. This is a remarkable reading of our contemporary situation through the lens of René Girard. Accurate, informed, and illuminating, Cowdell has written a fabulous book. For the person needing a way into Girard and for the person who is already using Girard's work, Cowdell brings out the implications of Girard for the moment in which we live. An absolutely essential addition to your personal library." — The Very Rev Dr. Ian Markham, Virginia Theological Seminary_. (shrink)

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron, recurrent neural network, and autoregressive integrated moving average on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to predict the three stock (...) market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting. (shrink)

It is a well-documented phenomenon that individuals stop searching earlier than predicted by the optimal, risk-neutral stopping rule, leading to inefficient searches. Individuals' search behaviors during making investment decisions in financial markets can be easily affected by their peers. In this study, we designed a search game in a simplified experimental stock market in which subjects were required to search for the best sell prices for their stocks. By randomly assigning subjects into pairs and presenting them with real-time information (...) on their peers' searches, we investigated the effects of peers' decisions on search behaviors. The results showed that two subjects in the same group with real-time peer information learned and engaged in similar search behaviors. However, this peer effect did not exist when subjects had access to feedback information on the ex-post best response. In addition, we found that the presence of information about peers' decisions alone had no significant impact on search efficiency, whereas access to both information on peers' decisions and feedback information significantly improved subjects' search efficiency. (shrink)

This paper offers the first philosophical analysis of a form of artificial intelligence (AI) which the author calls facial profiling technology (FPT). FPT is a type of facial analysis technology designed to predict criminal behavior based solely on facial structure. Marketed for use by law enforcement, face classifiers generated by the program can supposedly identify murderers, thieves, pedophiles, and terrorists prior to the commission of crimes. At the time of this writing, an FPT company has a contract with the United (...) States federal government. After recounting how FPT resurrects the same moral problems associated with the pseudoscience of physiognomy, the author of this manuscript develops and defends the ‘Liberal Argument Against Facial Discrimination’ (LAAFD), which concludes that government use of FPT poses a significant risk of violating the classical liberal value of equality before the law by committing unjust discrimination against groups of people whose faces happen to match FPT classifiers. A key move in the argument suggests how a future scenario that results in widespread discrimination based solely on facial structure could be as unjustified and harmful, mutatis mutandis, as similar discrimination based solely on racial background. In the final section, the author of this paper develops prima facie policy proposals designed to protect classical liberal values if FPT is to be utilized by governments in liberal democratic societies. (shrink)

Discussion of marketing deception has mostly focused on two main areas: first are cases that involve the intentional deception of people who tend to have compromised intelligence, such as children or the elderly, and second are cases that involve intentional falsehoods or the withholding of vital information, such as Madoff’s exploits. This article will differ from most in the field by examining marketing practices that are generally truthful, but deceive almost everyone. These practices do not fool just small select groups, (...) but are fooling those usually assumed to be rational. For example, we love “free” merchandise so much that we are willing to irrationally settle for less to get the free product. Behavioral economists and psychologists are proving that, as Dan Ariely puts it, most all of us are “Predictably Irrational.” Is it wrong for marketers to take advantage of the mass’s foibles as it is wrong to take advantage of children? The article will look at some of the behavioral economists’ data, how that data affects the rational and ignorant person standards of marketing, and suggest the reflective rational person standard as a way to morally evaluate marketing techniques given this new data. (shrink)

In 1990, Gilles Deleuze publishedPostscript on the Societies of Control, an introduction to the potentially suffocating reality of the nascent control society. This thirty-year update details how Deleuze’s conception has developed from a broad speculative vision into specific economic mechanisms clustering around personal information, big data, predictive analytics, and marketing. The central claim is that today’s advancing control society coerces without prohibitions, and through incentives that are not grim but enjoyable, even euphoric because they compel individuals to obey their own (...) personal information. The article concludes by delineating two strategies for living that are as unexplored as control society itself because they are revealed and then enabled by the particular method of oppression that is control. (shrink)

Prediction markets are increasingly being considered as methods for gathering, summarizing and aggregating diffuse information by governments and businesses alike. Critics worry that these markets are susceptible to price manipulation by agents who wish to distort decision making. We study the effect of manipulators on an experimental market, and find that manipulators are unable to distort price accuracy. Subjects without manipulation incentives compensate for the bias in offers from manipulators by setting a different threshold at which they (...) are willing to accept trades. (shrink)

Branding is a magic weapon for enterprises to participate in international competition, and empowering enterprises through branding has become a national strategy in the new era. Economic and social development has won wide acclaim from the international community, but enterprises generally have the problem of being “big but not strong”, which is not matching with long history and great power influence. The brand bottleneck of Chinese enterprises has been highlighted. Recent brand theory research has been fruitful on the whole, but (...) there are also some weak links, among which “the mechanism of enterprise brand value formation” is a research theme to be strengthened. This paper presents a number of suggestions for the formation of corporate brand value. The empirical analysis was conducted using valid data. The results found that: customer involvement behavior has a significant positive influence on customer citizenship behavior and customer experience value. Customer experience value has a significant positive influence on customer satisfaction and customer commitment. It plays a mediating effect in the relationship between the influence of customer involvement behavior on customer satisfaction and customer commitment, respectively. Customer satisfaction has a significant positive influence on customer commitment, and plays a mediating customer commitment has a significant positive effect on customer citizenship behavior and mediates the effect of customer experience value on customer citizenship behavior. The experimental results show that: the accuracy of crop color recognition by this method is high, and it has the advantages of faster computational efficiency and higher computational accuracy compared with other algorithms, thus verifying the reliability of the algorithm. Based on the fuzzy sentiment of online reviews, this paper improves the continuous use model ECM-ISC and formulates the inference rules of fuzzy affiliation function, and verifies the brand conversion intention and brand conversion type of cell phones by example calculation, which has good accuracy and generality and has important practical significance for brand marketing and early warning management. In addition, the use of brand economics in the study of corporate brand positioning is a development and innovation of brand economics. (shrink)

This paper conducts an ethical analysis of the 2008 closure of a US money market fund entitled the reserve primary fund, which triggered the first run in the money market sector and a resultant liquidity crisis that harmed the entire US financial system. Although many academics and regulators have studied and written about RPF, the question whether the decision that caused the fund to collapse represented any ethical dilemma, has not been addressed to date. With this purpose in mind, the (...) paper will examine the events that culminated in the closure of RPF according to Alasdair MacIntyre’s virtue ethics approach. In so doing, the paper aims to extend the applicability of MacIntyre’s concepts to the finance industry in general, and to provide a framework to predict and so potentially prevent crises like that exemplified by the RPF case. (shrink)

As the stock market is an important part of the national economy, more and more investors have begun to pay attention to the methods to improve the return on investment and effectively avoid certain risks. Many factors affect the trend of the stock market, and the relevant information has the nature of time series. This paper proposes a composite model CNN-BiSLSTM to predict the closing price of the stock. Bidirectional special long short-term memory improved on bidirectional long short-term memory adds (...) 1 − tanh function in the output gate which makes the model better predict the stock price. The model extracts advanced features that influence stock price through convolutional neural network, and predicts the stock closing price through BiSLSTM after the data processed by CNN. To verify the effectiveness of the model, the historical data of the Shenzhen Component Index from July 1, 1991, to October 30, 2020, are used to train and test the CNN-BiSLSTM. CNN-BiSLSTM is compared with multilayer perceptron, recurrent neural network, long short-term memory, BiLSTM, CNN-LSTM, and CNN-BiLSTM. The experimental results show that the mean absolute error, root-mean-squared error, and R-square evaluation indicators of the CNN-BiSLSTM are all optimal. Therefore, CNN-BiSLSTM can accurately predict the closing price of the Shenzhen Component Index of the next trading day, which can be used as a reference for the majority of investors to effectively avoid certain risks. (shrink)

Sociopolitical attitudes are often the root cause of conflicts between individuals, groups, and even nations, but little is known about the origin of individual differences in sociopolitical orientation. We test a combination of economic and evolutionary ideas about the degree to which the mating market, sex, age, and income affect sociopolitical orientation. We collected data online through Amazon’s Mechanical Turk from 1108 US participants who were between 18 and 60, fluent in English, and single. While ostensibly testing a new online (...) dating website, participants created an online dating profile and described people they would like to date. We manipulated the participants’ popularity in the mating market and the size of the market and then measured participants’ sociopolitical attitudes. The sociopolitical attitudes were reduced to five dimensions via Principal Components Analysis. Both manipulations affected attitudes toward wealth redistribution but were largely not significant predictors of the other dimensions. Men reported more unrestricted sociosexual attitudes, and more support for benevolent sexism and traditional family values, than women did, and women supported wealth redistribution more than men did. There was no sex difference in accepting nonconforming behaviors. Younger people and people with lower incomes were more liberal than older people and people with higher incomes, respectively, regardless of sex. Overall, effects were largely not interactive, suggesting that individual differences in sociopolitical orientation may reflect strategic self-interest and be more straightforward than previously predicted. (shrink)

With the rapid development of the Internet information age, social networks, mobile Internet, and e-commerce have expanded the scope of Internet applications. The “big data” era is a challenge and chance for companies and has a great impact on social economy, politics, culture, and people’s lives. An accurate marketing system is developed based on J2EE, and the architecture is selected from the user layer, business logic layer, and data layer and the B/S3 layer application, including three layers of crip-dm and (...) semma. And, other process methods are used. Data-mining-based marketing system information solutions consist of several parts, such as requirement analysis, design, implementation, and testing. This paper introduces data mining technology to the marketing business based on the practical use and design IT solutions for precision marketing, attribute selection tools, attribute analysis tools, modeling prediction tools, and others. This paper introduces a precision marketing system based on data mining technology. The system passes the actual test and the deployment and the operation of this system are confirmed. The system, which can improve marketing activity, is tested, and the development and operation of this system markedly increase the company’s earnings. (shrink)

In the past two decades, especially after the financial crisis of 2007–09, the literature for examining the availability of integration between the stock exchanges in developed and developing markets has grown. The importance of this topic stems from the significant implications of the linkage between exchange markets on various decisions taken by interested parties, such as policymakers and investors, in the decisions for portfolio diversification. This study examines the relationship between a developing stock exchange index, Amman Stock Exchange (...) Index, and the number of international indices, including S&P 500, NASDAQ, Nikkei, DAX, CAC, and HSI for 2008-2019. To validate the availability of the linkage between the indices, the author includes various tests of a correlation coefficient, stepwise regression analysis, and artificial neural network. Despite the results indicating that the ANN is more efficient than linear regression in investigating the availability of the relationship between ASEI and international indices, stepwise regression and neural network support this relationship. Furthermore, ANN results revealed that the S&P 500 index and year have the most substantial relationship with ASEI. Our research is theoretically and practically important; policymakers and investors can benefit from our findings. Future studies may explore the effect of different international stock market indices on ASEI or other developing markets. Further studies can use macroeconomic factors to build prediction models for stock market indices. (shrink)

Since the opening of the economy, China’s regional economy has developed rapidly, the overall national strength has been increasing, and the people’s living standards have been continuously improved. The issue of coordinated regional development has become an important issue in today’s society. Genetic algorithm is a kind of prediction algorithm that has developed rapidly in recent years and is widely used. However, when solving engineering prediction problems, there are often problems such as premature convergence and easiness to fall (...) into local optimal solutions. Therefore, on the basis of studying the related theories of genetic algorithm and artificial immune algorithm, this paper uses the advantages of the two algorithms, combines the two algorithms, and proposes an improved algorithm for genetic algorithm-adaptive immune genetic algorithm. Taking genetic algorithm as the basic framework, the operators and selection methods of artificial immune algorithm are integrated. Using the adaptive concept, the formulas of adaptive crossover probability and mutation probability are innovatively designed. Compared with the fixed value of the immune genetic algorithm, the introduction of the adaptive concept can intelligently adjust the optimization process and increase the optimization speed. Considering the double uncertain factors of product market demand and waste product recycling in the remanufacturing supply chain system, the maximization of logistics network operating profit, the minimization of environmental impact, and the maximization of customer satisfaction are the forecast goals. The market demand of uncertain products is effectively controlled through the option contract mechanism, and a multiobjective forecasting model based on the option contract mechanism is established. According to the characteristics of the model, an improved immune genetic algorithm is designed to solve the problem, and the effectiveness of the immune genetic algorithm is verified through an example. (shrink)

Globalization has been one of the most hotly contested phenomena of the past two decades. It has been a primary attractor of books, articles, and heated debate, just as postmodernism was the most fashionable and debated topic of the 1980s. A wide and diverse range of social theorists have argued that today's world is organized by accelerating globalization, which is strengthening the dominance of a world capitalist economic system, supplanting the primacy of the nation-state by transnational corporations and organizations, and (...) eroding local cultures and traditions through a global culture. Contemporary theorists from a wide range of political and theoretical positions are converging on the position that globalization is a distinguishing trend of the present moment, but there are hot debates concerning its nature, effects, and future.2 Moreover, advocates of a postmodern break in history argue that developments in transnational capitalism are producing a new global historical configuration of post- Fordism, or postmodernism as an emergent cultural logic of capitalism (Harvey 1989; Soja 1989; Jameson 1991; and Gottdiener 1995). Others define the emergent global economy and culture as a "network society" grounded in new communications and information technology (Castells 1996, 1997, and 1998). For its defenders, globalization marks the triumph of capitalism and its market economy (see apologists such as Fukuyama 1992 and Friedman 1999 who perceive this process as positive), while its critics portray globalization as negative (see, for example, Mander and Goldsmith 1996; Eisenstein 1998; and Robins and Webster 1999). Some theorists see the emergence of a new transnational ruling elite and the universalization of consumerism (Sklair 2001), while others stress global fragmentation of “the clash of civilizations” (Huntington 1996). Driving “post” discourses into novel realms of theory and politics, Hardt and Negri (2000) present the emergence of “Empire” as producing evolving forms of sovereignty, economy, culture, and political struggle that unleash an unforeseeable and unpredictable flow of novelties, surprises, and upheavals. Discourses of globalization initially were polarized into pro or con celebrations or attacks.. (shrink)

The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In (...) actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically evaluates models of such inefficient markets. Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets. (shrink)

In today’s postmodern world with the latest and top notch internet technologies in the market, if it has become easy and accessible for everyone to communicate with others sitting at the other corner of the world, it has also given rise to the cybercrimes including cyber terro rism which has not only provided grave threats to the whole world but also posed a question of whether with the manipulation of cyber space, cyber terrorists can damage or destroy the physical infrastructure (...) of its target. Owing to easy access to everyone and strong damage done as compared to traditional terrorism, today terrorists are relying on cyber terrorism as well. The Islamic State has emerged as one of the brutal and violent terrorist organization s which hired cyber experts and manipulated cyber space to the extent that today they are most active and professional cyber users’ terrorist organization of the world. The main focus of the paper is to highlight the basic definition of cyber terrorism, how often it is different from traditional terrorism, use of cyber terrorism, how cyber terrorism can be manipulated through various latest tools and techniques and how Islamic State is using cyber space to spread its message. (shrink)

Marketing research interviewers often feel that they must compromise their own moral principles while executing work-related activities. This finding is based on analysis of data obtained from three focus group interviews and a mail survey of 173 telephone survey interviewers. Data from the mail survey were used to construct scales measuring interviewers' perceived necessity of moral compromise, moral character, and job satisfaction. The three scales then were used in a hierarchical regression analysis to predict incidences of interviewers' self-reported proscribed behaviors (...) on the job, the latter being an index of behaviors known by interviewers to be wrong. Results support all hypothesized relationships. (shrink)

This paper outlines and criticises two models of terrorism, the Rational Agent Model (RAM) and the Radicalisation Model (RAD). A different and more plausible conception of the turn to violence is proposed. The proposed account is Moderate Epistemic Particularism (MEP), an approach partly inspired by Karl Jaspers’ distinction between explanation and understanding. On this account there are multiple idiosyncratic pathways to cognitive and behavioural radicalisation, and the actions and motivations of terrorists can only be understood (rather than explained) by (...) engaging with their subjectivity in a way that depends on a degree of empathy. Scepticism is expressed about attempts to model radicalisation and predict political violence. This scepticism is based on reflections concerning the nature of complex particulars. The implications of MEP for counterterrorism are briefly discussed. (shrink)

The efficient markets hypothesis has been the central proposition in finance for nearly thirty years. It states that securities prices in financial markets must equal fundamental values, either because all investors are rational or because arbitrage eliminates pricing anomalies. This book describes an alternative approach to the study of financial markets: behavioral finance. This approach starts with an observation that the assumptions of investor rationality and perfect arbitrage are overwhelmingly contradicted by both psychological and institutional evidence. In (...) actual financial markets, less than fully rational investors trade against arbitrageurs whose resources are limited by risk aversion, short horizons, and agency problems. The book presents and empirically evaluates models of such inefficient markets. Behavioral finance models both explain the available financial data better than does the efficient markets hypothesis and generate new empirical predictions. These models can account for such anomalies as the superior performance of value stocks, the closed end fund puzzle, the high returns on stocks included in market indices, the persistence of stock price bubbles, and even the collapse of several well-known hedge funds in 1998. By summarizing and expanding the research in behavioral finance, the book builds a new theoretical and empirical foundation for the economic analysis of real-world markets. (shrink)

Following the bloodshed of 11th March 2004 in Madrid, a number of questions have arisen, questions that, according to our continental understanding of democracy, require prompt answers. A number of these questions have not even been asked yet by the intellectuals of Europe in general and those of Spain in particular. How can a democracy fight terrorism? This is deliberately referred to as the continental-European tradition in contrast to the Anglo-Saxon tradition. The latter has, yet again, embraced Hobbes’s old (...) question and pleads for security at the expense of freedom in all uncertain cases. 11th March in Madrid demonstrated that the terrorist scene has been organising its finances through the trafficking of drugs and arms. Can the systems of democracy with their policies that rest on careful management measures control this black market at all? All these questions are linked closely to the good old question of the limits of freedom. How do we define freedom in a society that must arm itself for the fight against all forms of arbitrary acts of terror, authoritarian rules and various forms of fanaticism? (shrink)

On traditional information markets, rewards are tied to the occurrence of events external to the market, such as some particular candidate winning an election. For that reason, they can only be used when it is possible to wait for some external event to resolve the market. In cases involving long time-horizons or counterfactual events, this is not an option. Hence, the need for a self-resolving information market, resolved with reference to factors internal to the market itself. In the present (...) paper, we first offer some theoretical reasons for thinking that, since the only thing that can be expected to be salient to all participants on a SRIM is the content of the question bet on, a convention will arise of taking that question at face value, and betting accordingly, in which case trading behaviour on SRIMs can be expected to be identical to that on TIMs. This is the ‘face value’ hypothesis. If this hypothesis holds, SRIMs have the potential of incorporating the accuracy of TIMs while shedding their limitations in relation to long-term predictions and the evaluation of counterfactuals. We then report on a laboratory experiment that demonstrates that trading behaviour can indeed come out highly similar across SRIMs and TIMs. As such, the study can be thought of as an experimental case study on SRIMs. Finally, we discuss some limitations of the study, and also points towards fruitful areas of future research in light of our results. (shrink)

The construction of a financial risk prediction model has become the need of the hour due to long-term and short-term violations in the financial market. To reduce the default risk of peer-to-peer companies and promote the healthy and sustainable development of the P2P industry, this article uses a model based on the LightGBM algorithm to analyze a large number of sample data from Renrendai, which is a representative platform of the P2P industry. This article explores the base LightGBM model (...) along with the integration of linear blending to build an optimal default risk identification model. The proposed approach is applicable for a large number of multi-dimensional data samples. The results show that the prediction accuracy rate of the LightGBM algorithm model on the test set reaches 80.25%, which can accurately identify more than 80% of users, and the model has the best prediction performance in terms of different performance evaluation indicators. The integration of LightGBM and the linear blending approach yield a precision value of 91.36%, a recall of 75.90%, and an accuracy of 84.36%. The established LightGBM algorithm can efficiently identify the default of the loan business on the P2P platform compared to the traditional machine learning models, such as logistic regression and support vector machine. For a large number of multi-dimensional data samples, the LightGBM algorithm can effectively judge the default risk of users on P2P platforms. (shrink)

Key words: code of ethics; rejected patients; terrorism; terrorist victims; terrorists; values.

A legal system is any institution or set of institutions in a given society that provides dispute resolution in a systematic and reasonably predictable way. it does so through the exercise of three functions: the judicial, the legislative, and the executive. The judicial function, the adjudication of disputes, is the core of any legal system; the other two are ancillary to this. The legislative function is to determine the rules that will govern the process of adjudication (this function may be (...) merged with the judicial function, as when case law arises through precedents, or it may be exercised separately), while the executive function is to secure submission (through a variety of means, which may or may not include violence) to the adjudicative process and compliance with its verdicts. A government or state (for present purposes i shall use these terms interchangeably) is any organisation that claims, and in large part achieves, a forcibly maintained monopoly, within a given geographical territory, of these legal functions, and in particular of the use of force in the executive function. now the market anarchist objection to government is simply a logical extension of the standard libertarian objection to coercive monopolies in general.1 First, from a moral point of view, among people regarded as equals2 it cannot be legitimate for some to claim a certain line of work as their own privileged preserve from which others are to be forcibly excluded; we no longer believe in the divine right of kings, and on no other basis could such inequality of rights be justified. Second, from an economic point of view, because monopolies are insulated from market competition and hold their customers by force, they lack both the information and the incentive to provide consumers with fair, efficient, and inexpensive service. The anarchist accepts these arguments, and merely asks why they should apply with any less force to the provision of legal services. (shrink)

Motivated by a large literature on how firm-specific resources drive firm performance, we propose and find that heterogeneity in investor optimism regarding firm-specific attributes plays a very important role in influencing the managerial propensity to manipulate financial statements. When firm-level investor optimism is moderate, the incidence of accounting misconduct increases, but it decreases when investors are highly optimistic. Further, market reaction to the announcement of financial restatements is more negative when investors held more optimistic firm-specific beliefs at the time of (...) initial misstatement. These findings are robust to alternative firm-specific optimism measures linked to analysts, general investors and unsophisticated individual investors, controls for market-wide consumer sentiment unexplained by macroeconomic factors, economy-wide and industry-level optimism, potential selection bias and reverse causality. Our analysis highlights the importance of firm-level investor optimism in predicting, preventing and detecting accounting misconduct. (shrink)