The prospective introduction of autonomous cars into public traffic raises the question of how such systems should behave when an accident is inevitable. Due to concerns with self-interest and liberal legitimacy that have become paramount in the emerging debate, a contractarian framework seems to provide a particularly attractive means of approaching this problem. We examine one such attempt, which derives a harm minimisation rule from the assumptions of rational self-interest and ignorance of one’s position in a future accident. We contend, (...) however, that both contractarian approaches and harm minimisation standards are flawed, due to a failure to account for the fundamental difference between those ‘involved’ and ‘uninvolved’ in an impending crash. Drawing from classical works on the trolley problem, we show how this notion can be substantiated by reference to either the distinction between negative and positive rights, or to differences in people’s claims. By supplementing harm minimisation with corresponding constraints, we can develop crash algorithms for autonomous cars which are both ethically adequate and promise to overcome certain significant practical barriers to implementation. (shrink)

Purpose Fully autonomous self-driving cars not only hold the potential for significant economic and environmental advantages but also introduce complex ethical dilemmas. One of the highly debated issues, known as the “trolley problems,” revolves around determining the appropriate actions for a self-driving car when faced with an unavoidable crash. Currently, the discourse on autonomous vehicle (AV) crash algorithms is primarily shaped by Western ethical traditions, resulting in a Eurocentric bias due to the dominant economic and political influence (...) of the West. However, considering that AV technology will be deployed across diverse cultural and religious contexts, this paper aims to contribute to the discourse by providing an Islamic perspective on programming the response of AVs in the event of an imminent crash. Design/methodology/approach This study proposes a novel methodology based on the Islamic concept of maṣlaḥa for the normative assessment of ethical decisions related to AV programming. Findings Drawing upon the works of classic Islamic jurists, this study highlights two distinct normative visions within Islamic traditions (akin to deontology and consequentialism) concerning the preservation of human lives in the context of AVs. This study explores the shared and divergent elements between Islamic and Western ethical approaches proposed for AVs. Originality/value This pioneering work examines AV crash algorithms from an Islamic perspective, filling a void in the global ethical discourse. This work will also serve an important role to bridge the gap between the theoretical Islamic ethical principles and their practical application in the realm of AVs. (shrink)

‘@AP: Breaking: Two Explosions in the White House and Barack Obama is injured’. So read a tweet sent from a hacked Associated Press Twitter account @AP, which affected financial markets, wiping out $136.5 billion of the Standard & Poor’s 500 Index’s value. While the speed of the Associated Press hack crash event and the proprietary nature of the algorithms involved make it difficult to make causal claims about the relationship between social media and trading algorithms, we argue (...) that it helps us to critically examine the volatile connections between social media, financial markets, and third parties offering human and algorithmic analysis. By analyzing the commentaries of this event, we highlight two particular currents: one formed by computational processes that mine and analyze Twitter data, and the other being financial algorithms that make automated trades and steer the stock market. We build on sociology of finance together with media theory and focus on the work of Christian Marazzi, Gabriel Tarde and Tony Sampson to analyze the relationship between social media and financial markets. We argue that Twitter and social media are becoming more powerful forces, not just because they connect people or generate new modes of participation, but because they are connecting human communicative spaces to automated computational spaces in ways that are affectively contagious and highly volatile. (shrink)

What is a financial crash, and why does it happen? The answers to these fundamental questions require an investigation of the ontological and epistemic state of the financial markets which will identify the causes of a financial crash, the entities involved, and the relations between them.To this end, I examine several theories on financial systems which have conceptualized financial crashes. I analyze how these theories: a) identify different causes of a crash; b) deal with the basic entities (...) and units of analysis; c) define what we can know about those causes and entities, and what they can reveal about an impending crash. On this basis, I outline some ontological and epistemic preconditions that are necessary for a financial crash to occur. I also examine an example of a price drop on the stock market and the role played by the epistemic and ontic states of the market in that event. (shrink)

Self‐driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, they need to be programmed for how to deal with crash scenarios. Should cars be programmed to always prioritize their owners, to minimize harm, or to respond to crashes on the basis of some other type of principle? The article first discusses whether everyone should have the same “ethics settings.” Next, the oft‐made analogy with the trolley problem is examined. (...) Then follows an assessment of recent empirical work on lay‐people's attitudes about crash algorithms relevant to the ethical issue of crash optimization. Finally, the article discusses what traditional ethical theories such as utilitarianism, Kantianism, virtue ethics, and contractualism imply about how cars should handle crash scenarios. The aim of the article is to provide an overview of the existing literature on these topics and to assess how far the discussion has gotten so far. (shrink)

Self‐driving cars hold out the promise of being much safer than regular cars. Yet they cannot be 100% safe. Accordingly, they need to be programmed for how to deal with crash scenarios. Should cars be programmed to always prioritize their owners, to minimize harm, or to respond to crashes on the basis of some other type of principle? The article first discusses whether everyone should have the same “ethics settings.” Next, the oft‐made analogy with the trolley problem is examined. (...) Then follows an assessment of recent empirical work on lay‐people's attitudes about crash algorithms relevant to the ethical issue of crash optimization. Finally, the article discusses what traditional ethical theories such as utilitarianism, Kantianism, virtue ethics, and contractualism imply about how cars should handle crash scenarios. The aim of the article is to provide an overview of the existing literature on these topics and to assess how far the discussion has gotten so far. (shrink)

: Accidents will survive the outbreak of driverless cars, but their moral implications will suffer substantial changes. The decision made today by a human in a fraction of a second will eventually be replaced by an algorithm subject to moral scrutiny. This not only raises the question of how the algorithm should work, or whether alternatives solutions are indeed comparable, but also changes the essence of the problem: from ascertaining liability to defining desired outcomes. In this paper, I first contest (...) two possible approaches to resolving the driverless car dilemma – which I call statistical and nominal – to conclude that neither is morally sound. I then propose an alternative solution based on “time-relative equality”, or always sparing younger people. This follows from seeking an egalitarian solution, that is the least intrusive – a position I defend from a possible ageist critique. Keywords: Driverless Cars; Accident; Algorithm; Age-relative Equality Condotti verso un incidente morale Riassunto: Vi saranno incidenti anche dopo la diffusione delle auto a guida autonoma, ma le loro implicazioni morali subiranno mutamenti sostanziali. Le decisioni prese oggi in una frazione di secondo dagli esseri umani saranno alla fine sostituite da un algoritmo soggetto a controllo morale. Sorge non solo il problema di come dovrebbe funzionare questo algoritmo – o se vi siano soluzioni alternative comparabili –, ma cambia anche la sostanza del problema: dall’accertamento dell’imputabilità alla definizione dell’esito auspicato. In questo lavoro discuterò due possibili approcci per risolvere il dilemma – che chiamerò “statistico” e “nominale” –, per concluderne che non sono moralmente corretti. Proporrò quindi una soluzione alternativa, basata sulla “eguaglianza tempo-relativa”, il principio per cui bisogna sempre salvare il più giovane. Questo segue dal cercare una soluzione egalitarista, che sia la meno intrusiva – una posizione che difenderò da una possibile critica che la vede come discriminatoria verso gli anziani. Parole chiave: Automobili a guida automatica; Incidenti; Algoritmo; Eguaglianza relativa all’età. (shrink)

In cinematic experience, a view from nowhere appears in an instituting moment – neither in time nor out of time, but part of time itself – when a camera reflex lifts the viewer’s perception out of somewhere and into the infinite time of the film. We argue that the view from nowhere found in Birt Acres’s film Rough Sea at Dover – a fifteen-second shot of waves breaking against a sea wall in Dover, England in 1895 – transcends all attempts (...) to turn it into a view from somewhere, as an empty space that carries the auratic trace of the past into the present through phase shifts of technical mediation. In Simondon’s terms, the view from nowhere opens up possibilities of becoming all ways at once in the reflexive capacity of the human organon. Following Stiegler’s organological technics, we identify the capture of perception by the apparatus of recording and playback in the digitally automated algorithm as a threat to the reflexive capability of the organon to see otherwise in the creative individuation opened up in the phase-shifting process. Our analysis triggers a switch from an anthropocentric to a neganthropic-ecological mode of seeing in which the auratic trace of the event of waves crashing against the pier is seen in an inhuman view from nowhere that carries the threat of automatized systems in which human noesis – self-reflexive capacity – is eclipsed by machines. By seeing otherwise, the eclipse by machines is reversed to reveal the complex becoming of the film in its materiality as a work of creative individuation. (shrink)

How should driverless vehicles respond to situations of unavoidable personal harm? This paper takes up the case of self-driving cars as a prominent example of algorithmic moral decision-making, an emergent type of morality that is evolving at a high pace in a digitised business world. As its main contribution, it juxtaposes dilemma decision situations relating to ethical crash algorithms for autonomous cars to two edge cases: the case of manually driven cars facing real-life, mundane accidents, on the one (...) hand, and the dilemmatic situation in theoretically constructed trolley cases, on the other. The paper identifies analogies and disanalogies between the three cases with regard to decision makers, decision design, and decision outcomes. The findings are discussed from the angle of three perspectives: aspects where analogies could be found, those where the case of self-driving cars has turned out to lie in between both edge cases, and those where it entirely departs from either edge case. As a main result, the paper argues that manual driving as well as trolley cases are suitable points of reference for the issue of designing ethical crash algorithms only to a limited extent. Instead, a fundamental epistemic and conceptual divergence of dilemma decision situations in the context of self-driving cars and the used edge cases is substantiated. Finally, the areas of specific need for regulation on the road to introducing autonomous cars are pointed out and related thoughts are sketched through the lens of the humanistic paradigm. (shrink)

This article puts forward solutions to some of the ethical and legal dilemmas posed in the current discussion on how to program crash algorithms in autonomous or self-driving cars. The first part of the paper defines the scope of the problem in the criminal legal field, and the next section gives a critical analysis of the proposal to always prioritise the interest of the occupant of the vehicle in situations with conflict of interests. The principle of minimizing social (...) damage as a model for configuring self-driving cars is examined in the third section. Despite its apparent plausibility, within the framework of a liberal legal system that recognises humans as free agents who have rights and responsibilities, maximizing the function of social utility does not justify harmful interference into a person’s legal sphere. Therefore, in the fourth part, the author argues the need to program the crash algorithms of autonomous cars based on a deontological understanding of the system of justifications in criminal law. The solution to the dilemma lies in a prior analysis of the legal positions of all agents involved in the conflict, from a perspective of the principles of autonomy and solidarity as the core of the system of justifications. (shrink)

How should driverless vehicles respond to situations of unavoidable personal harm? This paper takes up the case of self-driving cars as a prominent example of algorithmic moral decision-making, an emergent type of morality that is evolving at a high pace in a digitised business world. As its main contribution, it juxtaposes dilemma decision situations relating to ethical crash algorithms for autonomous cars to two edge cases: the case of manually driven cars facing real-life, mundane accidents, on the one (...) hand, and the dilemmatic situation in theoretically constructed trolley cases, on the other. The paper identifies analogies and disanalogies between the three cases with regard to decision makers, decision design, and decision outcomes. The findings are discussed from the angle of three perspectives: aspects where analogies could be found, those where the case of self-driving cars has turned out to lie in between both edge cases, and those where it entirely departs from either edge case. As a main result, the paper argues that manual driving as well as trolley cases are suitable points of reference for the issue of designing ethical crash algorithms only to a limited extent. Instead, a fundamental epistemic and conceptual divergence of dilemma decision situations in the context of self-driving cars and the used edge cases is substantiated. Finally, the areas of specific need for regulation on the road to introducing autonomous cars are pointed out and related thoughts are sketched through the lens of the humanistic paradigm. (shrink)

Wie sollen sich autonome Fahrzeuge verhalten, wenn ein Unfall nicht mehr abwendbar ist? Die Komplexität spezifischer moralischer Dilemmata, die in diesem Kontext auftreten können, lässt bewährte ethische Denktraditionen an ihre Grenzen stoßen. Dieser Aufsatz versteht sich als Versuch, neue Lösungsperspektiven mithilfe einer risikoethischen Sichtweise auf die Problematik zu eröffnen und auf diese Weise deren Relevanz für die Programmierung von ethischen Unfallalgorithmen aufzuzeigen. Im Zentrum steht dabei die Frage, welche Implikationen sich aus einer Auffassung von Dilemma-Situationen als risikoethische Verteilungsprobleme im Hinblick (...) auf die Zulässigkeit von entsprechenden Risikoübertragungen ergeben. Dabei wird zunächst eine risikoethische Interpretation des zugrundeliegenden Entscheidungsproblems skizziert, welches durch seine dilemmatische Struktur eine besondere Risikokonstellation begründet. Ausgehend von den Positionen von Sven Ove Hansson und Julian Nida-Rümelin wird für einen deontologisch-risikoethischen Ansatz argumentiert, der auf Individualrechten einerseits und einer interpersonell gerechten Verteilung der entstehenden Schadensrisiken anderseits basiert. Diese beiden Kriterien werden für den Anwendungskontext des autonomen Fahrens konkretisiert. Zum einen wird in Bezug auf das erste Kriterium argumentiert, dass individuelle Rechte genau dann als angemessen gewahrt gelten können, wenn die resultierenden Risikoübertragungen auf die Einzelnen in ihrer absoluten Höhe jeweils zumutbar sind. Zum anderen werden Schwierigkeiten skizziert, die sich hinsichtlich der konkreten Umsetzung des zweiten Kriteriums der Verteilungsgerechtigkeit ergeben. In diesem Zusammenhang werden beispielsweise ethische Herausforderungen in Bezug auf einen möglichen Vorteilsausgleich, das Prinzip der Schadensminimierung sowie individuell unterschiedliche Ausgangsbedingungen der persönlichen Schadensreduktion kritisch in den Blick genommen. (shrink)

Through modern driver assistant systems, algorithmic decisions already have a significant impact on the behavior of vehicles in everyday traffic. This will become even more prominent in the near future considering the development of autonomous driving functionality. The need to consider ethical principles in the design of such systems is generally acknowledged. However, scope, principles and strategies for their implementations are not yet clear. Most of the current discussions concentrate on situations of unavoidable crashes in which the life of human (...) beings is existentially affected. In this paper, we argue that ethical considerations should be mandatory for any algorithmic decision of autonomous vehicles, instead of a limitation to hazard situations. Such an ethically aligned behavior is relevant because autonomous vehicles, like any other traffic participants, operate in a shared public space, where every behavioral decision impacts the operational possibilities of others. These possibilities concern the fulfillment of a road-user’s safety, utility and comfort needs. We propose that, to operate ethically in such space, an autonomous vehicle will have to take its behavior decisions according to a just distribution of operational possibilities among all traffic participants. Using an application on a partially-autonomous prototype vehicle, we describe how to apply and implement concepts of distributive justice to the driving environment and demonstrate the impact on its behavior in comparison to an advanced but egoistic decision maker. (shrink)

Twenty-five years after the end of the Cold War, a new Cold War is being waged in our societies. During the Cold War a theoretical model of man was developed by economists and the military, an egotistical being interested only in his own benefit and in duping his opponents to achieve his ends: a modern homo oeconomicus. After his career in the Cold War ended, he was not scrapped but adapted to the needs of the twenty-first century. He became the (...) ringmaster of a new era of information capitalism. He sought to read, control and influence thoughts; to predict, price and eliminate risks. Today stock-market trading is guided by him. He uses computer algorithms and Big Data to build up detailed pictures of our preferences and then suggest and sell goods to us. The model has become a self-fulfilling prophecy. We are no longer the masters of our own fate. The Game of Life runs without us. Schirrmacher traces the progress of this extreme rationalization of social life from the Cold War games of the 1950s Rand Corporation to the stock-market trading techniques that brought about the financial crash of 2008, showing how these developments were interwoven with the rise of game theory, rational choice theory and neoliberal economics. The state and politics increasingly submitted themselves to the logic of computerized game theory and an economistic view of the world, evading real decision-making in the process. In this brave new world individuals, alone in front of their computers, may think they are constructing a reality of their own choosing, but in fact they are being manipulated all along by others who are setting the rules of the game. This international bestseller by one of Germanys most distinguished journalists is a powerful indictment of a way of thinking that has become pervasive and threatens to undermine not only parliaments and constitutions but also the sovereignty of the individual to be the person he or she wants to be. (shrink)

Self-driving cars currently face a lot of technological problems that need to be solved before the cars can be widely used. However, they also face ethical problems, among which the question of crash-optimization algorithms is most prominently discussed. Reviewing current debates about whether we should use the ethics of the Trolley Dilemma as a guide towards designing self-driving cars will provide us with insights about what exactly ethical research does. It will result in the view that although we (...) need the ethics of the Trolley Dilemma as important input for self-driving cars, the route towards simply implementing it into automated cars is blocked. (shrink)

The philosophy of blockchain technology is concerned, among other things, with blockchain ontology, how it might be characterised, how it is being created, implemented, and adopted, how it operates in the world, and how it evolves over time. This paper concentrates on whether Bitcoin/blockchain can be considered a complex system and, if so, whether it is a chaotic one. Beyond mere academic curiosity, a positive response would raise concerns about the likelihood of Bitcoin/blockchain entering a 2010-Flash-Crash-type of chaotic regime, (...) with catastrophic consequences for financial systems based on it. The paper starts by highlighting the relevant details of the Bitcoin/blockchain ecosystem formed by the blockchain itself, bitcoin end users, capital gains seekers, miners, full nodes maintainers, and developers, and their interactions. Then the Information Theory of Complex Systems is briefly discussed for later use. Finally, the blockchain is investigated with the help of Crutchfield's Statistical Complexity measure. The low non-null statistical complexity value obtained suggests that the blockchain may be considered algorithmically complicated but hardly a complex system and unlikely to enter a chaotic regime. (shrink)

With the rapid development of science and technology, UAVs have become a new type of weapon in the informatization battlefield by their advantages of low loss and zero casualty rate. In recent years, UAV navigation electromagnetic decoy and electromagnetic interference crashes have activated widespread international attention. The UAV LiDAR detection system is susceptible to electromagnetic interference in a complex electromagnetic environment, which results in inaccurate detection and causes the mission to fail. Therefore, it is very necessary to predict the effects (...) of the electromagnetic environment. Traditional electromagnetic environment effect prediction methods mostly use a single model of mathematical model and machine learning, but the traditional prediction method has poor processing nonlinear ability and weak generalization ability. Therefore, this paper uses the Stacking fusion model algorithm in machine learning to study the electromagnetic environment effect prediction. This paper proposes a Stacking fusion model based on machine learning to predict electromagnetic environment effects. The method consists of Extreme Gradient Boosting algorithm, Gradient Boosting Decision Tree algorithm, K Nearest Neighbor algorithm, and Decision Tree algorithm. Experimental results show that, comprising with the other seven machine learning algorithms, the Stacking fusion model has a better classification prediction accuracy of 0.9762, a lower Hamming code distance of 0.0336, and a higher Kappa coefficient of 0.955. The fusion model proposed in this paper has a better predictive effect on electromagnetic environment effects and is of great significance for improving the accuracy and safety of UAV LiDAR detection systems under the complex electromagnetic environment on the battlefield. (shrink)

Algorithms wield increasing control over our lives—over which jobs we get, whether we're granted loans, what information we're exposed to online, and so on. Algorithms can, and often do, wield their power in a biased way, and much work has been devoted to algorithmic bias. In contrast, algorithmic neutrality has gone largely neglected. I investigate three questions about algorithmic neutrality: What is it? Is it possible? And when we have it in mind, what can we learn about algorithmic (...) bias? (shrink)

This article explores how the Crash Course video series are being used as a content-focused resource in the social studies classroom. It argues that the Crash Course series, alongside its YouTube competitors, has significantly stepped in to fill a vacuum left by criticisms and the unpopularity of lectures, textbooks, and feature films. With over 15 million subscribers and accumulated views over 1.9 billion, Crash Course has become an important and ubiquitous force in history and social studies classrooms (...) and represents a new genre of educational media found on YouTube. However, the dramatic rise in the popularity of educational videos online has not coincided with a growth in educational research, particularly in social studies and history education. This article explores the findings of a mixed-methods study that examines how and why history and social studies teachers are using Crash Course videos in their teaching and planning. In particular, it analyses descriptive statistics derived from the results of a teacher survey ( n = 181) and semi-structured interviews with seven social studies teachers who have used Crash Course in their classrooms. The authors found that teachers in the study are regularly using the Crash Course video series to deliver content which is clearly meeting a need many social studies teachers have. The videos–short, easily accessible, and fun–fit nicely with demands to keep students engaged, reduce reliance on textbooks, and explore new content that teachers have little time to learn themselves. This study also found that rarely, if ever, are teachers inviting students to evaluate or assess the content, trustworthiness, or perspective of Crash Course videos. This article discusses what is gained and what are the risks of embracing Crash Course in the social studies and history classroom. (shrink)

Should decision-making algorithms be held to higher standards of transparency than human beings? The way we answer this question directly impacts what we demand from explainable algorithms, how we govern them via regulatory proposals, and how explainable algorithms may help resolve the social problems associated with decision making supported by artificial intelligence. Some argue that algorithms and humans should be held to the same standards of transparency and that a double standard of transparency is hardly justified. (...) We give two arguments to the contrary and specify two kinds of situations for which higher standards of transparency are required from algorithmic decisions as compared to humans. Our arguments have direct implications on the demands from explainable algorithms in decision-making contexts such as automated transportation. (shrink)

Ancient algorithms -- Sorting -- Graph algorithms -- Primality testing -- Solution of linear equations -- Newton's method -- Linear programming -- Eigenvalues and eigenvectors -- MM algorithms -- Data mining -- The fast Fourier transform -- Monte Carlo methods -- Mathematical review.

As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are hampered (...) by conflations of various understandings of bias, ranging from neutral deviations from a standard to morally problematic instances of injustice due to prejudice, discrimination, and disparate treatment. This terminological confusion impedes efforts to address clear cases of discrimination. -/- In this paper, we examine the promises and challenges of different approaches to disambiguating bias and designing for justice. While both approaches aid in understanding and addressing clear algorithmic harms, we argue that they also risk being leveraged in ways that ultimately deflect accountability from those building and deploying these systems. Applying this analysis to recent examples of generative AI, our argument highlights unseen dangers in current methods of evaluating algorithmic bias and points to ways to redirect approaches to addressing bias in generative AI at its early stages in ways that can more robustly meet the demands of justice. (shrink)

Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on the (...) difficult task of operationalizing the principles of beneficence, non-maleficence and patient autonomy, and describe how we selected suitable input parameters that we extracted from a training dataset of clinical cases. The first performance results are promising, but an algorithmic approach to ethics also comes with several weaknesses and limitations. Should one really entrust the sensitive domain of clinical ethics to machine intelligence? (shrink)

This unique volume is an introduction for computer scientists, including a formal study of theoretical algorithms for Big Data applications, which allows them to work on such algorithms in the future. It also serves as a useful reference guide for the general computer science population, providing a comprehensive overview of the fascinating world of such algorithms. To achieve these goals, the algorithmic results presented have been carefully chosen so that they demonstrate the important techniques and tools used (...) in Big Data algorithms, and yet do not require tedious calculations or a very deep mathematical background. (shrink)

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, (...) and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language. Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals. (shrink)

Drones deployed to monitor endangered species often crash. These crashes teach us that using drones for conservation is a contingent practice ensnaring humans, technologies, and animals. This article advances a crash theory in which pilots, conservation drones, and endangered megafauna are relata, or related actants, that intra-act, cocreating each other and a mutually constituted phenomena. These phenomena are entangled, with either reciprocal dependencies or erosive entrapments. The crashing of conservation drones and endangered species requires an ethics of care, (...) repair, or reworlding. Diffractions, disruptions that expose difference, result from crashes and reveal the precarious manner by which technologies, laws, and discourses bring nature and culture together. To support crash theory, this article presents three ethnographic cases. A drone crash in the United Kingdom near white rhinoceroses while building machine learning training data exhibits the involvement of the electromagnetic spectrum; the threat of crashes in the Pacific Northwest near Puget Sound orcas discloses the impacts of drone laws; and drone crashes in Sri Lanka among Asian elephants presents the problems of technoliberal ideals around programming natural worlds. Throughout the article, a methodology is developed, parallelism, which attends to the material similarities in lateral phenomena. (shrink)

We study the Johansen–Ledoit–Sornette model of financial market crashes :219–255, 2000). On our view, the JLS model is a curious case from the perspective of the recent philosophy of science literature, as it is naturally construed as a “minimal model” in the sense of Batterman and Rice :349–376, 2014) that nonetheless provides a causal explanation of market crashes, in the sense of Woodward’s interventionist account of causation.

Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a (...) variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as (...) biased. While researchers have taken the problem of algorithmic bias seriously, but the current discussion on algorithmic fairness tends to conceptualize ‘fairness’ in algorithmic fairness primarily as a technical issue and attempts to implement pre-existing ideas of ‘fairness’ into algorithms. In this paper, I show that such a view of algorithmic fairness as technical issue is unsatisfactory for the type of problem algorithmic fairness presents. Since decisions on fairness measure and the related techniques for algorithms essentially involve choices between competing values, ‘fairness’ in algorithmic fairness should be conceptualized first and foremost as a political issue, and it should be (re)solved by democratic communication. The aim of this paper, therefore, is to explicitly reconceptualize algorithmic fairness as a political question and suggest the current discussion of algorithmic fairness can be strengthened by adopting the accountability for reasonableness framework. (shrink)

This comprehensive compendium provides a rigorous framework to tackle the daunting challenges of designing correct and efficient algorithms. It gives a uniform approach to the design, analysis, optimization, and verification of algorithms. The volume also provides essential tools to understand algorithms and their associated data structures. This useful reference text describes a way of thinking that eases the task of proving algorithm correctness. Working through a proof of correctness reveals an algorithm's subtleties in a way that a (...) typical description does not. Algorithm analysis is presented using careful definitions that make the analyses mathematically rigorous. (shrink)

Based on a deliberative democracy, this book uses a hermeneutic-critical methodology to study bibliographical sources and practical issues in order to analyse the possibilities, limits and consequences of the digital transformation of democracy. Drawing on a two-way democracy, the aim of this book is intended as an aid for thinking through viable alternatives to the current state of democracy with regard to its ethical foundations and the moral knowledge implicit in or assumed by the way we perceive and understand democracy. (...) It is intended to stimulate reflection and discussion on the basis that, by addressing what we understand as democracy, we can inevitably influence the reality known as democracy. Democracy’s evident regression in today’s world makes this all too apparent: it has become a hostage to all kinds of autocracies and technopopulisms, which are supported to a greater or lesser extent by the current algorithmic revolution. (shrink)

Why do organizations conduct job interviews? The traditional view of interviewing holds that interviews are conducted, despite their steep costs, to predict a candidate’s future performance and fit. This view faces a twofold threat: the behavioral and algorithmic threats. Specifically, an overwhelming body of behavioral research suggests that we are bad at predicting performance and fit; furthermore, algorithms are already better than us at making these predictions in various domains. If the traditional view captures the whole story, then interviews (...) seem to be a costly, archaic human resources procedure sustained by managerial overconfidence. However, building on T. M. Scanlon’s work, we offer the value of choice theory of interviewing and argue that interviews can be vindicated once we recognize that they generate commonly overlooked kinds of noninstrumental value. On our view, interviews should thus not be entirely replaced by algorithms, however sophisticated algorithms ultimately become at predicting performance and fit. (shrink)

The inspiring true story of a teacher's experiences with her students and the life lessons she learned that can help others find joy and success. Crash Course chronicles the life lessons that Kim Bearden has learned during an award-winning career in education that has spanned three decades. Kim has taught more than 2,000 students, and each has shown her something about the world and the abundant capacity for love, resilience, and appreciation that we all possess. By sharing her students' (...) stories, she teaches their inspiring lessons to us all. Throughout the ups and downs of her professional and personal life, Kim found that her students were the light that illuminated her path; they were her sanctuary in the storm. From her challenges as a first year teacher, to her triumphs as the cofounder of the highly acclaimed Ron Clark Academy, Kim shares how children can teach each of us the importance of building relationships, abandoning fear, embracing one's unique gifts, and living with passion. Full of honesty, humor, heartbreak, and humanity, Kim's experiences show how children can help any one of us, despite life's obstacles, find the joy and significance in both our personal and professional lives. (shrink)

Polyhedral functions provide a model for an important class of problems that includes both linear programming and applications in data analysis. General methods for minimizing such functions using the polyhedral geometry explicitly are developed. Such methods approach a minimum by moving from extreme point to extreme point along descending edges and are described generically as simplicial. The best-known member of this class is the simplex method of linear programming, but simplicial methods have found important applications in discrete approximation and statistics. (...) The general approach considered in this text, first published in 2001, has permitted the development of finite algorithms for the rank regression problem. The key ideas are those of developing a general format for specifying the polyhedral function and the application of this to derive multiplier conditions to characterize optimality. Also considered is the application of the general approach to the development of active set algorithms for polyhedral function constrained problems and associated Lagrangian forms. (shrink)

Crash Course in Logic is a booklet designed to introduce basic principles of logic and critical thinking to students so they can better express their ideas. Many high school and college students have trouble constructing theoretical arguments and writing clearly because they are not acquainted with the forms of reasoning that are presented in this booklet. Intended as a supplement to other instructional material for a variety of courses, this booklet will guide students through a mini-course on logic that (...) includes many examples and exercises. With knowledge of the basic forms of reasoning, students will have the tools necessary to solve problems and evaluate arguments as well as articulate their own ideas and insights clearly. Crash Course in Logic will be of great value to teachers of any subject who are searching for an accessible way to teach critical thinking and reasoning to their students. (shrink)

It is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate (...) how the philosophical conceptual framework of epistemic injustice can help pinpoint potential, systematic harms from algorithmic profiling, but we also identify a novel source of hermeneutical injustice that to date has received little attention in the relevant literature: epistemic fragmentation. Epistemic fragmentation is a structural characteristic of algorithmically-mediated environments that isolate individuals, making it more difficult to develop, uptake and apply new epistemic resources. This, in turn, can impede the identification and conceptualisation of emerging harms in these environments. We trace the occurrence of hermeneutical injustice back to the fragmentation of the epistemic experiences of individuals, who are left more vulnerable by the inability to share, compare, and learn from shared experiences. (shrink)

Ethnographic study of the constitution of algorithms.

Algorithms: Design and Analysis is a textbook designed for undergraduate and postgraduate students of computer science engineering, information technology, and computer applications. The book offers adequate mix of both theoretical and mathematical treatment of the concepts. It covers the basics, design techniques, advanced topics and applications of algorithms. The book will also serve as a useful reference for researchers and practising programmers whointend to pursue a career in algorithm designing. The book is also indented for students preparing for (...) campus interviews and competitive examinations. (shrink)

The rhetoric of algorithmic neutrality is more alive than ever-why? This volume explores key moments in the historical emergence of algorithmic practices and in the constitution of their credibility and authority since 1500. If algorithms are historical objects and their associated meanings and values are situated and contingent-and if we are to push back against rhetorical claims of otherwise-then the genealogical investigation this book offers is essential to understand the power of the algorithm. The fact that algorithms create (...) the conditions for many of our encounters with social reality contrasts starkly with their relative invisibility. More than other artifacts, algorithms are easily black-boxed. Rather than contingent and modifiable, they are widely seen as obvious and unproblematic-without context and without history. As an antidote, this volume keeps a clear focus on the emergence and continuous reconstitution of algorithmic practices alongside the ascendance of modernity. Its essays highlight the trajectory of an algorithmic modernity, one characterized by attitudes and practices that are best emblematized by the modernist aesthetic and inhuman efficacy of the algorithm. The volume moves from early modern algorithmic practices, centered on heuristics for arithmetic operations, emphasizing ruptures, shifts, and variations across times and cultures. By the age of Enlightenment, the term algorithm had come to signify any process of systematic calculation that could be carried out mechanically, but its meaning and implications are still distant from those familiar to us. It's in the nineteenth and twentieth century that the meaning of algorithm is sharpened through a new discipline and by adding sets of specific conditions-such as the condition of finiteness-which acquire new and crucial significance in the age of digital computing. Throughout, the connection between algorithms and modernity is one of our central concerns. Through detailed historical reconstructions of specific moments, thinkers, and cultural phenomena over the last five hundred years, these essays lead us to the definitions of algorithm most legible today and to the pervasiveness of both algorithmic procedures and rhetoric. This volume contributes a multi-faceted exploration of the genealogies of algorithms, of algorithmic thinking, and of the distinctly modernist faith in algorithms as neutral tools that merely illuminate the natural and social world. (shrink)

Algorithms influence every facet of modern life: criminal justice, education, housing, entertainment, elections, social media, news feeds, work… the list goes on. Delegating important decisions to machines, however, gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference. (...) Using these case studies, the authors provide a better understanding of machine fairness and algorithmic transparency. They explain why interventions in algorithmic systems are necessary to ensure that algorithms are not used to control citizens' participation in politics and undercut democracy. This title is also available as Open Access on Cambridge Core. (shrink)

Introduction -- Direct algorithms of decompositions of matrices by non-orthogonal transformations -- Direct algorithms of decompositions of matrices by orthogonal transformations -- Direct algorithms of solution of linear equations -- Iterative algorithms of solution of linear equations -- Direct algorithms of solution of eigenvalue problem -- Iterative algorithms of solution of eigenvalue problem -- Algorithms of solution of singular value decomposition.

A best-seller in its French edition, the construction of this book is original and its success in the French market demonstrates its appeal. It is based on three principles: 1. An organization of the chapters by families of algorithms : exhaustive search, divide and conquer, etc. At the contrary, there is no chapter only devoted to a systematic exposure of, say, algorithms on strings. Some of these will be found in different chapters. 2. For each family of (...) class='Hi'>algorithms, an introduction is given to the mathematical principles and the issues of a rigorous design, with one or two pedagogical examples. 3. For its most part, the book details 150 problems, spanning on seven families of algorithms. For each problem, a precise and progressive statement is given. More important, a complete solution is detailed, with respect to the design principles that have been presented ; often, some classical errors are pointed at. Roughly speaking, two thirds of the book are devoted to the detailed rational construction of the solutions. (shrink)

Algorithmic systems and predictive analytics play an increasingly important role in various aspects of modern life. Scholarship on the moral ramifications of such systems is in its early stages, and much of it focuses on bias and harm. This paper argues that in understanding the moral salience of algorithmic systems it is essential to understand the relation between algorithms, autonomy, and agency. We draw on several recent cases in criminal sentencing and K–12 teacher evaluation to outline four key ways (...) in which issues of agency, autonomy, and respect for persons can conflict with algorithmic decision-making. Three of these involve failures to treat individual agents with the respect they deserve. The fourth involves distancing oneself from a morally suspect action by attributing one’s decision to take that action to an algorithm, thereby laundering one’s agency. (shrink)

Since Princess Diana's car crash in 1997, media interest in the crash as an event needing explanation has proliferated. The purpose of this collection is to subject texts or films, within which crashes figure, to well-defined cultural study.

The aim of this paper is both to use Kindleberger’s thesis to analyse banking crashes of the Middle Age and to give proof of whether the medieval banks do or do not raise the same theoretical analysis as the modern banks. This is of importance, because the theories that are invoked by Kindleberger concern banks very different from the medieval banks. If the financial instability of the 14th century is similar to that of the 19th or the 20th century, this (...) leads to amend the impact and generality of Kindleberger’s instability model.L’objet de cet article est d’utiliser la théorie de Kindleberger pour analyser les krachs bancaires du Moyen Age et vérifier si les banques médiévales relèvent ou non du même appareil théorique que les banques modernes. Cela représente un enjeu important car les banques médiévales sont très différentes de celles qu’étudie Kindleberger. Si l’instabilité financière du XIVe siècle est comparable à celle des XIXe et XXe siècles, cela nous amène à reconsidérer l’impact et la généralité du modèle de Kindleberger. (shrink)

As government pressure on major technology companies builds, both firms and legislators are searching for technical solutions to difficult platform governance puzzles such as hate speech and misinformation. Automated hash-matching and predictive machine learning tools – what we define here as algorithmic moderation systems – are increasingly being deployed to conduct content moderation at scale by major platforms for user-generated content such as Facebook, YouTube and Twitter. This article provides an accessible technical primer on how algorithmic moderation works; examines some (...) of the existing automated tools used by major platforms to handle copyright infringement, terrorism and toxic speech; and identifies key political and ethical issues for these systems as the reliance on them grows. Recent events suggest that algorithmic moderation has become necessary to manage growing public expectations for increased platform responsibility, safety and security on the global stage; however, as we demonstrate, these systems remain opaque, unaccountable and poorly understood. Despite the potential promise of algorithms or ‘AI’, we show that even ‘well optimized’ moderation systems could exacerbate, rather than relieve, many existing problems with content policy as enacted by platforms for three main reasons: automated moderation threatens to further increase opacity, making a famously non-transparent set of practices even more difficult to understand or audit, further complicate outstanding issues of fairness and justice in large-scale sociotechnical systems and re-obscure the fundamentally political nature of speech decisions being executed at scale. (shrink)

Do you have a problem? Maybe you can use an algorithm to fix it! Learn about the codes all around us in Algorithms: Solve a Problem! Sing along as you learn to Code It!