I want to focus on some of the limits of decision theory that are of interest to the philosophical concern with practical reasoning and rational choice. These limits should also be of interest to the social-scientists’ concern with Rational Choice.

The primate brain is able to guide complex decisions that can rapidly be adapted to changing constraints. Unfortunately, the vast numbers of highly interconnected neurons that seem to be needed make it difficult to study the cellular mechanisms that underlie the flexible combination of stored and acute information during a decision. Established simpler networks, particularly with few and identified neurons, would lend themselves more readily to such a dissection. But can simple networks implement complex and flexible decisions similarly? After (...) a brief overview of complex decisions in primates and of decision‐making in simple networks, I argue that simpler systems can combine complexity with accessibility at the cellular level. Indeed, examination of a network in fish may help in dissecting key mechanisms of complex and flexible decision‐making in an established model of synaptic plasticity at the level of identified neurons. (shrink)

Journal of Political Philosophy, EarlyView.

Big decisions in a person’s life often affect the preferences and standards of a good life which that person’s future self will develop after implementing her decision. This paper argues that in such cases the person might lack any reasons to choose one way rather than the other. Neither preference-based views nor happiness-based views of justified choice offer sufficient help here. The available options are not comparable in the relevant sense and there is no rational choice to make. Thus, (...) ironically, in many of a person’s most important decisions the idea of that person’s good seems to have no application. (shrink)

Three partners founded the Grenada Chocolate Company in 1999: Mott Green, Doug Browne and Edmond Brown. Several years ago Doug passed away of cancer and in June 2013 Mott suffered a fatal electrocution while repairing a piece of equipment. Edmond was now thrust into the leadership position and left to decide what direction GCC should take. The GCC product line was becoming increasingly popular both on the island and internationally and demand was high,but the original vision for the company was (...) to produce bean-to-bar chocolates while providing a fair wage to the local employees and farmers. Expansion could be an option for Edmond and GCC, but was it possible to expand and stay true to the ideas on which GCC was founded? (shrink)

Three partners founded the Grenada Chocolate Company (GCC) in 1999: Mott Green, Doug Browne and Edmond Brown. Several years ago Doug passed away of cancer and in June 2013 Mott suffered a fatal electrocution while repairing a piece of equipment. Edmond was now thrust into the leadership position and left to decide what direction GCC should take. The GCC product line was becoming increasingly popular both on the island and internationally and demand was high,but the original vision for the company (...) was to produce bean-to-bar chocolates while providing a fair wage to the local employees and farmers. Expansion could be an option for Edmond and GCC, but was it possible to expand and stay true to the ideas on which GCC was founded? (shrink)

We will argue here that after more than 30 years of talk, theory, and clinical practice, we bioethicists still know far too little about what patients, subjects, and healthcare professionals are up to, morally. Bioethics is still near the beginning in grasping what it means to understand, much less to honor fully, the moral power and perspicacity of those bioethics is designed to serve. This is, of course, a serious charge, but one we will endeavor to show has merit. However, (...) we want to be clear from the start that we do not gainsay the important work that has been done in and through the influence of bioethics, both as a field of practical engagement and as a cultural movement, in improving how healthcare is delivered and how human subjects are treated. Thirty or 40 years—depending on how one marks the beginning point—is a very short time, and it is hard to imagine that wholesale changes, all of them in the right direction, could be the outcome for a field this young. Hence, we do not intend the title, “One Cheer for Bioethics,” as a wholesale indictment, but as an indication that there is a great deal of work yet to be done, and that following the currently dominant direction of the field is not likely to get us there. Our aim is to indicate just where future work should be focused, and to do so we will need to be critical of some of the preoccupations of the last three decades. a. (shrink)

We will argue here that after more than 30 years of talk, theory, and clinical practice, we bioethicists still know far too little about what patients, subjects, and healthcare professionals are up to, morally. Bioethics is still near the beginning in grasping what it means to understand, much less to honor fully, the moral power and perspicacity of those bioethics is designed to serve. This is, of course, a serious charge, but one we will endeavor to show has merit. However, (...) we want to be clear from the start that we do not gainsay the important work that has been done in and through the influence of bioethics, both as a field of practical engagement and as a cultural movement, in improving how healthcare is delivered and how human subjects are treated. Thirty or 40 years—depending on how one marks the beginning point—is a very short time, and it is hard to imagine that wholesale changes, all of them in the right direction, could be the outcome for a field this young. Hence, we do not intend the title, “One Cheer for Bioethics,” as a wholesale indictment, but as an indication that there is a great deal of work yet to be done, and that following the currently dominant direction of the field is not likely to get us there. Our aim is to indicate just where future work should be focused, and to do so we will need to be critical of some of the preoccupations of the last three decades. a. (shrink)

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

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

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

Big social data have enabled new opportunities for evaluating the applicability of social science theories that were formulated decades ago and were often based on small- to medium-sized samples. Big Data coupled with powerful computing has the potential to replace the statistical practice of sampling and estimating effects by measuring phenomena based on full populations. Preparing these data for analysis and conducting analytics involves a plethora of decisions, some of which are already embedded in previously collected data and built tools. (...) These decisions refer to the recording, indexing and representation of data and the settings for analysis methods. While these choices can have tremendous impact on research outcomes, they are not often obvious, not considered or not being made explicit. Consequently, our awareness and understanding of the impact of these decisions on analysis results and derived implications are highly underdeveloped. This might be attributable to occasional high levels of over-confidence in computational solutions as well as the possible yet questionable assumption that Big Data can wash out minor data quality issues, among other reasons. This article provides examples for how to address this issue. It argues that checking, ensuring and validating the quality of big social data and related auxiliary material is a key ingredient for empowering users to gain reliable insights from their work. Scrutinizing data for accuracy issues, systematically fixing them and diligently documenting these processes can have another positive side effect: Closely interacting with the data, thereby forcing ourselves to understand their idiosyncrasies and patterns, can help us to move from being able to precisely model and formally describe effects in society to also understand and explain them. (shrink)

Let F be the set of functions from an infinite set, S, to an ordered ring, R.

Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Can transparency contribute to restoring accountability for such systems? Several objections are examined: the loss of privacy when data sets become public, the perverse effects of disclosure of the very algorithms themselves, the potential loss of competitive edge, and the limited gains in answerability to be expected since sophisticated algorithms are inherently opaque. It is concluded that transparency (...) is certainly useful, but only up to a point: extending it to the public at large is normally not to be advised. Moreover, in order to make algorithmic decisions understandable, models of machine learning to be used should either be interpreted ex post or be interpretable by design ex ante. (shrink)

Artificial intelligence is set to transform healthcare. Key ethical issues to emerge with this transformation encompass the accountability and transparency of the decisions made by AI-based systems, the potential for group harms arising from algorithmic bias and the professional roles and integrity of clinicians. These concerns must be balanced against the imperatives of generating public benefit with more efficient healthcare systems from the vastly higher and accurate computational power of AI. In weighing up these issues, this paper applies the deliberative (...) balancing approach of the Ethics Framework for Big Data in Health and Research. The analysis applies relevant values identified from the framework to demonstrate how decision-makers can draw on them to develop and implement AI-assisted support systems into healthcare and clinical practice ethically and responsibly. Please refer to Xafis et al. in this special issue of the Asian Bioethics Review for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end of this paper. (shrink)

There is no well-built theory on credit risk measurement and decision analysis for financial big data, and an effective and scientific evaluation system for them has not been formed. A review of them can contribute to grasping the abovementioned topics, understanding current issues, analyzing research problems, mastering research challenges, and predicting future research directions. Besides, this paper points out four research directions of credit risk measurement and decision analysis for financial big data. Moreover, this paper can provide some (...) guidance directions and insights for practitioners, researchers, financial institutions, and government departments who have an interest in complex decision-making in big data. (shrink)

Pastor and influencer Noah Herrin gives you ten simple, powerful choices you can make each day that will lead to life-changing purpose, freedom, and impact. When you shift your relationship with Jesus from duty to delight, you will rest where you once were striving, stand firm in faith, rise in influence, and make an impact that echoes into eternity.

Purpose The purpose of this paper is to explore the epistemological tensions embedded within big data and data-driven technologies to advance a socio-political reconsideration of the public dimension in the assessment of their implementation. Design/methodology/approach This paper builds upon (and revisits) the European Union’s (EU) normative understanding of artificial intelligence (AI) and data-driven technologies, blending reflections rooted in philosophy of technology with issues of democratic participation in tech-related matters. Findings This paper proposes the conceptual design of sectorial and/or local-level e-participation (...) platforms to ignite an ongoing discussion – involving experts, private actors, as well as cognizant citizens – over the implementation of data-driven technologies, to avoid siloed, tech-solutionist decisions. Originality/value This paper inscribes the EU’s normative approach to AI and data-driven technologies, as well as critical work on the governance of these technologies, into a broader political dimension, suggesting a way to democratically and epistocratically opening up the decisional processes over the development and implementation of these technologies and turn such processes into a systemic civic involvement. (shrink)

: In this commentary we engage with Paul’s Transformative Experience as it relates to decision making. We consider why deciding whether to undergo a transformative experiences can feel so agonizing yet also be so fun, whether people have any preferences to decide over in the first place, and who people even think they are. Keywords: Transformative Experience; Big Decisions; Preference Construction; Theory of Self; Mental Effort Decisioni trasformative e relative insoddisfazioni Riassunto: In questo commento ci concentreremo su come il (...) volume di L.A. Paul Transformative Experience affronta i processi decisionali. Esamineremo perché la decisione se intraprendere un’esperienza trasformativa possa risultare così struggente ed essere altresì divertente; se le persone abbiano in assoluto qualche preferenza nel prendere decisioni definitive e chi le persone persone ritengono di essere. Parole chiave: Esperienza trasformativa; Grandi decisioni; Costruzione delle preferenze; Teoria del sé; Sforzo mentale. (shrink)

Some important and decisive observations allowed a widespread and almost unquestionable acceptance of the big bang cosmology, but we can admit and search other factors that have contributed and continue to contribute to the enormous acceptance and great popularity of this cosmological conception, not only inside but also outside of cosmology and even in numerous no scientific contexts. To find some of those factors, a case study was undertaken based on thematic analysis, an analytical tool which is based on the (...) idea that the scientific activity, in addition to a theoretical and an experimental dimensions, has a third dimension with psychological and cultural elements called themata that strongly influence the construction of scientific theories and also their acceptance or rejection. This case study focused on the most important founding texts of big bang cosmology, namely articles and books of Alexandre Friedmann, Georges Lemaître, and George Gamow, covering three decades of important developments, and the founding texts of its great rival, the steady-state cosmology. This article presents a summary of the main results of this case study, which allowed to identify several themata with a very important role in the big bang cosmology: differentiation and unification ; unity, creation, change, evolution, constancy, simplicity, life cycle, circularity, and disorder. All these themata form a methodological and conceptual matrix—with a triple dimension: historical, transversal/cultural, and psychological—that can help explain the acceptance and popularity of the big bang cosmology within and beyond its disciplinary boundaries. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

Xenophon’s anecdote concerning the exchange of clothes between a big boy and a little boy in Cyropaedia offers a valuable framework for understanding his conception of justice and the problematics of administering it. Interpreters have erred by assuming that Cyrus’ teacher, as well as Socrates in Memorabilia, simply identifies the just with the lawful. Rather than identifying the two, both characters argue that the law is just; but they differ widely in their explanations of what makes the law just. For (...) Cyrus’ teacher, the obligation to observe the law rests on a universal pre-legal ban on violence; for Socrates statutory law is to be obeyed for utilitarian reasons. Socrates’ view thus justifies both the teacher’s insistence that Cyrus obey the law—since the law is of benefit to the community—and also Cyrus’ decision to violate the law to achieve a just and beneficial redistribution. But it offers no justification for a universal ban on violence. In conformity with the Socratic principle, Cyrus avoids violence as far as possible, but only for the prudential reasons expressed by his mother. Once he acquires the power to coerce, Cyrus uses it to enforce the principle of proportional equality and meritorious redistribution he had approved in his judgment of the actions of the big boy. (shrink)

The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and their knock-on effects. We are moving towards changes in how ethics has to be perceived: away from individual decisions with specific and knowable outcomes, towards actions by many unaware that they may have taken actions with unintended consequences for anyone. Responses will require a rethinking of ethical choices, the lack thereof and (...) how this will guide scientists, governments, and corporate agencies in handling Big Data. This essay elaborates on the ways Big Data impacts on ethical conceptions. (shrink)

Evidential Decision Theory is a radical theory of rational decision-making. It recommends that instead of thinking about what your decisions *cause*, you should think about what they *reveal*. This Element explains in simple terms why thinking in this way makes a big difference, and argues that doing so makes for *better* decisions. An appendix gives an intuitive explanation of the measure-theoretic foundations of Evidential Decision Theory.

Agricultural Big Data analytics (ABDA) is being proposed to ensure better farming practices, decision-making, and a sustainable future for humankind. However, the use and adoption of these technologies may bring about potentially undesirable consequences, such as exercises of power. This paper will analyse Brey’s five distinctions of power relationships (manipulative, seductive, leadership, coercive, and forceful power) and apply them to the use agricultural Big Data. It will be shown that ABDA can be used as a form of manipulative power (...) to initiate cheap land grabs and acquisitions. Seductive power can be exercised by pressuring farmers into situations they would not have otherwise chosen (such as installing monitors around their farm and limited access to their farm and machinery). It will be shown that agricultural technology providers (ATPs) demonstrate leadership power by getting farmers to agree to use ABDA without informed consent. Coercive power is exercised when ATPs threaten farmers with the loss of ABDA if they do not abide by the policies and requirements of the ATP or are coerced to remain with the ATP because of fear of legal and economic reprisal. ATPs may use ABDA to determine willingness-to-pay rates from farmers, using this information to force farmers into precarious and vulnerable positions. Altogether, this paper will apply these five types of power to the use and implementation of ABDA to demonstrate that it is being used to exercise power in the agricultural industry. (shrink)

Some important and decisive observations allowed a widespread and almost unquestionable acceptance of the big bang cosmology, but we can admit and search other factors that have contributed and continue to contribute to the enormous acceptance and great popularity of this cosmological conception, not only inside but also outside of cosmology and even in numerous no scientific contexts. To find some of those factors, a case study was undertaken based on thematic analysis, an analytical tool which is based on the (...) idea that the scientific activity, in addition to a theoretical and an experimental dimensions, has a third dimension with psychological and cultural elements called themata that strongly influence the construction of scientific theories and also their acceptance or rejection. This case study focused on the most important founding texts of big bang cosmology, namely articles and books of Alexandre Friedmann, Georges Lemaître, and George Gamow, covering three decades of important developments, and the founding texts of its great rival, the steady-state cosmology. This article presents a summary of the main results of this case study, which allowed to identify several themata with a very important role in the big bang cosmology: differentiation and unification ; unity, creation, change, evolution, constancy, simplicity, life cycle, circularity, and disorder. All these themata form a methodological and conceptual matrix—with a triple dimension: historical, transversal/cultural, and psychological—that can help explain the acceptance and popularity of the big bang cosmology within and beyond its disciplinary boundaries. (shrink)

Sustainability is typically viewed as consisting of three forces, economic, social, and ecological, in tension with one another. In this paper, we address the dangers posed to societal sustainability. The concern being addressed is the very survival of societies where the rights of individuals, personal and collective freedoms, an independent judiciary and media, and democracy, despite its messiness, are highly valued. We argue that, as a result of various technological innovations, a range of dysfunctional impacts are threatening social and political (...) stability. For instance, robotics and automation are replacing human labor and decision-making in a range of industries; search engines, monetized through advertising, have access to, and track, our interests and preferences; social media, in connecting us to one another often know more about us than we ourselves do, enabling them to profit in ways which may not coincide with our well-being; online retailers have not only acquired the ability to track and predict our buying choices, but also they can squeeze vendors based on their outsize bargaining power; and, in general, virtual technologies have changed both the way we think and our sense of self. With the rising deployment of the Internet of Things, and developments in machine learning and artificial intelligence, the threats to individual freedoms and rights, societal cohesion and harmony, employment and economic well-being, and trust in democracy are being ratcheted up. This paper lauds the benefits and addresses the harm wrought by the high tech giants in Information and Communication Technologies. The search for rapidly growing revenues drives firms to accelerate product innovation without fully investigating the entire gamut of their impacts. As greater wealth accrues to the leaders of tech firms, inequalities within firms and societies are widening, creating social tensions and political ferment. We explore the ethical nature of the challenge employing a simple utilitarian calculus, complemented by approaches rooted in rights, justice, and the common good. Various options to address the challenges posed by ICTs are considered and evaluated. We argue that regulation may do little more than slow down the damage to society, particularly since societal values and political preferences vary internationally. Firms need to establish ethical standards, imbuing the upholders of these standards with sufficient authority, while creating a culture of morality. User involvement and activism, and shareholders’ concerns for the sustainability of societies on whose continued prosperity they depend, are imperative to humanity’s ability to decide the future direction of technology. (shrink)

This article argues that the fact that an action will compound a prior injustice counts as a reason against doing the action. I call this reason The Anti-Compounding Injustice principle or aci. Compounding injustice and the aci principle are likely to be relevant when analyzing the moral issues raised by “big data” and its combination with the computational power of machine learning and artificial intelligence. Past injustice can infect the data used in algorithmic decisions in two distinct ways. Sometimes prior (...) injustice undermines the accuracy of the data itself. In these contexts, improving accuracy will also help to avoid compounding injustice. Other times, past injustice produces real-world differences among people with regard to skills, health, wealth, and other traits that employers, lenders, and others seek to measure. When decisions are based on accurate data that itself results from prior injustice, these decisions can also compound injustice. This second dynamic has received less attention than the first but is especially important because improving the accuracy of data will not mitigate this unfairness. (shrink)

Xenophon's anecdote concerning the exchange of clothes between a big boy and a little boy in Cyropaedia offers a valuable framework for understanding his conception of justice and the problematics of administering it. Interpreters have erred by assuming that Cyrus' teacher, as well as Socrates in Memorabilia, simply identifies the just with the lawful. Rather than identifying the two, both characters argue that the law is just; but they differ widely in their explanations of what makes the law just. For (...) Cyrus' teacher, the obligation to observe the law rests on a universal pre-legal ban on violence; for Socrates statutory law is to be obeyed for utilitarian reasons. Socrates' view thus justifies both the teacher's insistence that Cyrus obey the law -- since the law is of benefit to the community -- and also Cyrus' decision to violate the law to achieve a just and beneficial redistribution. But it offers no justification for a universal ban on violence. In conformity with the Socratic principle, Cyrus avoids violence as far as possible, but only for the prudential reasons expressed by his mother. Once he acquires the power to coerce, Cyrus uses it to enforce the principle of proportional equality and meritorious redistribution he had approved in his judgment of the actions of the big boy. (shrink)

In Homo Deus, Yuval Noah Harari argues that technological advances of the twenty-first century will usher in a significant shift in how humans make important life decisions. Instead of turning to the Bible or the Quran, to the heart or to our therapists, parents, and mentors, people will turn to Big Data recommendation algorithms to make these choices for them. Much as we rely on Spotify to recommend music to us, we will soon rely on algorithms to decide our careers, (...) spouses, and commitments. Harari also predicts that next, the state will take away individuals’ rights to make their own choices about their lives. If Google knows where your children would flourish best in school, why should the state allow a fallible human parent to decide? Liberalism—which, as Harari uses this term, refers to a state of society in which human freedom to choose is respected and championed—will collapse. In this paper, I argue that Harari’s conception of the future implications of recommendation algorithms is deeply flawed, for two reasons. First, users will not rely on algorithms to make decisions for them because they have no reason to trust algorithms, which are developed by companies with their own incentives, such as profit. Second, for most of our life decisions, algorithms will not be able to be developed, because the factors relevant to the decisions we face are unique to our situation. I present an alternative depiction of the future: instead of relying on algorithms to make decisions for us, humans will use algorithms to enhance our decision-making by helping us consider the most relevant choices first and notice information we might not otherwise. Finally, I will also argue that even if computers could make many of our decisions for us, liberalism as a political system would emerge unscathed. (shrink)

Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health (...) and Policy-relevant Ethics in Singapore Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data. (shrink)

“Big Data” in health and medicine in the 21st century differs from “Big Data” used in health and medicine in the 1700s and 1800s. However, the old data sets share one key component: large numbers. The term “Big Data” is not synonymous with large numbers. Large numbers are a key component of Big Data in health and medicine, both for understanding the full range of how a disease presents in a human for diagnosis, and for understanding if one treatment of (...) a disease is better than another treatment or better than just leaving the patient on his or her own without therapy. In this paper, we examine the first considerations of Big Data in medicine in Paris in the early 1800s when urologic surgeon Jean Civiale collected the first large numbers. Civiale collected the large numbers to defend the efficacy of his urologic instrument, the lithotrite, and the surgical procedure he developed, lithotrity, for the removal of bladder stones compared with earlier, more invasive surgical approaches. We examine how large numbers were adjudicated in social decision-making in the Académie des sciences, Paris, when a dispute arose among French urologic surgeons about the importance of large numbers in surgical science. After Civiale’s successful defense of his instrument and procedure in Paris, we examine how his approach to Big Data impacted data collection by George Buchanan in his use of the procedure at the Royal Hospital Infirmary in Glasgow. (shrink)

Classic conceptions of model simplicity for machine learning are mainly based on the analysis of the structure of the model. Bayesian, Frequentist, information theoretic and expressive power concepts are the best known of them, which are reviewed in this work, along with their underlying assumptions and weaknesses. These approaches were developed before the advent of the Big Data deluge, which has overturned the importance of structural simplicity. The computational simplicity concept is presented, and it is argued that it is more (...) encompassing and closer to actual machine learning practices than the classic ones. In order to process the huge datasets which are commonplace nowadays, the computational complexity of the learning algorithm is the decisive factor to assess the viability of a machine learning strategy, while the classic accounts of simplicity play a surrogate role. Some of the desirable features of computational simplicity derive from its reliance on the learning system concept, which integrates key aspects of machine learning that are ignored by the classic concepts. Moreover, computational simplicity is directly associated with energy efficiency. In particular, the question of whether the maximum possibly achievable predictive accuracy should be attained, no matter the economic cost of the associated energy consumption pattern, is considered. (shrink)

What's wrong with targeted advertising in political campaigns? Are echo chambers a matter of genuine concern? How does data collection impact on trust in society? As decision-making becomes increasingly automated, how can decision-makers be held to account? This collection consider potential solutions to these challenges.

This contribution offers reflections about Chilean Cybersyn, 50 years ago. In recent years, Cybersyn, has received significant attention. It was the brainchild of Stafford Beer, who conceived it to support the transformation of the Chilean economy from its bureaucratic history to hopefully create a vibrant and modern society, driven by cybernetic tools. These aspects have received much attention in recent times; however, in this contribution, I want to discuss how working in Cybersyn influenced my work after the coup of 1973. (...) Perhaps, for me, its major influence was in the management of complexity, through what I refer here as variety engineering and through the Viable System Model VSM as a paradigm to the management of relationships with implications to enterprises, society and the economy. After the 1973 coup major interest was in technological aspects of Cybersyn such as real-time management and its contribution to decision support and executive information systems. In the late 70s I was personally influenced by information management, but by the early 1980s my work moved towards methodological aspects of how to use the VSM. By 1989 I had created the VIPLAN method. Key questions I attempted to answer were, how to model the complexity of enterprises and their interactions with environmental agents. Later on, in the 1990s and 2000s, the main direction of my work was epistemological, ontological and methodological towards second-order cybernetics and relationships. Only in recent decades the political transformations proposed by Cybersyn have captured the imagination of many commentators. The confluence of social and cultural changes with information technology, data models, artificial intelligence, algorithms and several additional technological developments have challenged the excesses of capitalism, particularly after the banking crisis of 2008–2009. The purpose in this paper is discussing this evolution in the light of those early days in Chile. (shrink)

The technological possibilities for new data sources in media psychology, such as online live recordings, called Live Streaming, are growing continuously. These sources do not only offer plentiful quantitative material but also a fairly new access to ecologically valid and unobtrusive observation of problem-solving and decision-making processes. However, to exploit these potentials, epistemological and methodological reflection should guide research. The availability of Big Data and naturally occurring data sets allows to revise the historical controversies on the eligibility of self-description. (...) Drawing on such reflections, media psychology can contribute to renovate well established research methods, such as think aloud protocols, in order to enhance their empirical claims. Apart from other confident attempts to improve these methods, phenomenology and ethnomethodology offer a fruitful account to develop innovative data sources for self-description. Yet, this approach does not support a recurrence of self-description’s previous application but proposes an epistemological shift towards more subtle observations. In order to convey the potentials of media psychology, the risk of repeating classical mistakes, such as introspectionism, have to be regarded. Beyond these fallacies, however, modern digital technology holds encouraging potentials which have already partly been sighted by video gaming research. Due to the similarity of digital environments to laboratory setups, there remains to be a continuity from offline to online research, from traditional data to Big Data. Nevertheless, a true advance into new possibilities requires understanding the qualitative meaning of such data. (shrink)

Intelligence on mass media audiences was founded on representative statistical samples, analysed by statisticians at the market departments of media corporations. The techniques for aggregating user data in the age of pervasive and ubiquitous personal media build on large aggregates of information analysed by algorithms that transform data into commodities. While the former technologies were built on socio-economic variables such as age, gender, ethnicity, education, media preferences, Big Data technologies register consumer choice, geographical position, web movement, and behavioural information in (...) technologically complex ways that for most lay people are too abstract to appreciate the full consequences of. The data mined for pattern recognition privileges relational rather than demographic qualities. We argue that the agency of interpretation at the bottom of market decisions within media companies nevertheless introduces a ‘heuristics of the algorithm’, where the data inevitably becomes translated into social categories. In the paper we argue that although the promise of algorithmically generated data is often implemented in automated systems where human agency gets increasingly distanced from the data collected, one can observe a felt need among media users and among industry actors to ‘translate back’ the algorithmically produced relational statistics into ‘traditional’ social parameters. The tenacious social structures within the advertising industries work against the techno-economically driven tendencies within the Big Data economy. (shrink)

We content-analyzed sixteen business ethics textbooks to assess the extent to which small business and entrepreneurship concepts appear in these texts. We found that scenarios related to large corporations and executive level decision-making dominate discussions and applications. These texts have very little to no coverage of small business and entrepreneurship and relevant ethical issues. We discuss this missing link and implications for integrating small business,entrepreneurship, and ethics into business ethics education.

We content-analyzed sixteen business ethics textbooks to assess the extent to which small business and entrepreneurship concepts appear in these texts. We found that scenarios related to large corporations and executive level decision-making dominate discussions and applications. These texts have very little to no coverage of small business and entrepreneurship and relevant ethical issues. We discuss this missing link and implications for integrating small business,entrepreneurship, and ethics into business ethics education.

We propose a descriptive version of the classical multi-attribute utility model; to that end, we add a new parameter, momentary salience, to the customary formulation. The addition of this parameter allows the theory to accommodate changes in the decision maker’s mood and circumstances, as the saliencies of anticipated consequences are driven by concerns of the moment. By allowing for the number of consequences given attention at the moment of decision to vary, the new model mutes the criticism that (...) SEU models call for an omniscient decision maker. Use of the model is illustrated with a large-scale longitudinal study showing that adolescent smokers have higher utility for smoking than nonsmokers. We also propose to use the model hierarchically to describe everyday decisions that people deal with repeatedly. Big decisions, which set policy, guide a host of nested little decisions, which in turn lead to action. For a little decision, one of the options will be consistent with the policy, and will inherit its high utility. Accordingly, most little decisions will be made quickly and will follow the policy. However, people do sometimes decide to violate their own policies, and we describe how these lapses can lead to collapse of the policy. (shrink)

Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process, which is indented to determine interesting associations between items and to establish a set of association rules whose support is greater than a specific threshold. The classical association rules can only be extracted from binary data where an (...) item exists in a transaction, but it fails to deal effectively with quantitative attributes, through decreasing the quality of generated association rules due to sharp boundary problems. In order to overcome the drawbacks of classical association rule mining, we propose in this research a new neutrosophic association rule algorithm. The algorithm uses a new approach for generating association rules by dealing with membership, indeterminacy, and non-membership functions of items, conducting to an efficient decision-making system by considering all vague association rules. To prove the validity of the method, we compare the fuzzy mining and the neutrosophic mining. The results show that the proposed approach increases the number of generated association rules. (shrink)

The rapid adoption of digital technologies has revolutionized business operations and introduced emerging concepts such as Digital Twin (DT) technology, which has the potential to predict system responses before they occur, making it an attractive option for smart and sustainable tourism. However, implementing DT software systems poses significant challenges, including compliance with regulations and effective communication among stakeholders, and concerns surrounding security, privacy, and trust with the use of big data. To address these challenges, this paper proposes a documentation framework (...) for architectural decisions (DFAD) that applies the concept of big data governance to the digital system. The framework aims to ensure accountability, transparency, and trustworthiness while adhering to rules and regulations. To demonstrate its applicability, a case study and three case scenarios on the potential use of Mobile Positioning Data (MPD) in Indonesia for DT technology in smart and sustainable tourism were examined. The paper highlights the benefits of DFAD in shaping stakeholder communication and human–machine interactions while leveraging the potential of MPD to measure tourism statistics by Statistics Indonesia since 2016. Not only the documentation framework promotes compliance with regulations, but it also facilitates effective communication among stakeholders and enhances trust and transparency in the use of big data in DT technology for smart and sustainable tourism. This paper emphasizes the importance of effective big data governance and its potential to promote sustainable tourism practices. The multidisciplinarity approach on political science, software engineering, tourism, and official statistics provides an opportunity for academic contribution and decision-making processes. (shrink)

This article has two general aims. It first of all critically reconsiders the empirical turn’s dismissal of transcendentalism in the philosophy of technology, in particular through the work of Ihde and Verbeek, and defends the continuing relevance of the notion of the transcencental in thinking about technology today, illustrating this mainly through a reading of Stiegler’s understanding of the human condition as a technical condition and his view of human (noetic) evolution as proceeding from a process of technical exteriorization. The (...) crucial issue that is missed by postphenomenology and the empirical turn is that technology itself in its empiricity occupies the (periodically changing) place of the transcendental. It thus fails to consider the transcendental operativity of technical artifacts within its own empiricist stance. Secondly, it argues for the continuing importance and usefulness of the idea of Technology with a capital T, equally discarded by the representatives of the empirical turn, in particular against the emerging backdrop of the Anthropocene as the age of decisive anthropogenic forcing of the planet and the growing dominance of what has recently been called the technosphere in Earth system science. With Stiegler I show that a proper, inherent dynamic of technology must be acknowledged historically, anthropologically, techno-evolutionarily as well as (techno)phenomenologically. I conclude by demonstrating that our time of planetary crisis summons us to redirect our attention to technology from the empirical to the transcendental, and from the micro-level to the macro-level again. (shrink)

The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper, we aim to provide these details through a detailed investigation of what we (...) will call the “Simple Stakes Thesis”. The Simple Stakes Thesis, as it will turn out, is too simple. For even if the stakes associated with a specific one-off decision are low—and hence does not engender a right to an explanation—such decisions may nevertheless form part of a high stakes pattern or aggregate of decisions. In such cases, we argue, even a low stakes decision may engender a right to explanation. Not only does this show that the right to explanation is more demanding than so far recognized. It also shows that the stakes thesis is significantly harder to apply in practice. (shrink)

BackgroundSystems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology ; “big data” statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems (...) medicine knowledge and clinicians working to apply it.DiscussionThis article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through “big data” approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the “death computer,” to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their “quantified self.”SummaryThis paper examines possible ethical challenges that are likely to be raised as systems medicine to be translated into clinical medicine. These include the epistemological challenges for clinical decision-making, the use of scoring systems optimized by big data techniques and the risk that incidental and secondary findings will significantly increase. While some ethical implications remain still hypothetical we should use the opportunity to prospectively identify challenges to avoid making foreseeable mistakes when systems medicine inevitably arrives in routine care. (shrink)