There is a popular conception among many Zeitgeist watchers, especially in places like the US, Western Europe and Australia, of the urbanized East as existing somehow further into the future. As William Gibson once stated: `The future is here; it just isn't equally distributed yet.' This kind of cultural fetishism extends to not only technolust, but the practices that new gadgets and electronics encourage. The specific phenomenon explored in this article is that of virtual girlfriends and boyfriends: whether in the (...) form of avatars or automated SMS text messages. This particularly Japanese `craze', if we can call it that, fascinates and appals people who still hold P2P romance IRL in high-esteem. It seems like an insult to the intrinsically human and humanist discourse of courtship; and indeed it is. How does this perspective change, however, if we consider `love' as a technology? That is, as both a code with its own algorithmic parameters, and a discourse that also challenges the hyper-rational assumptions of the `merely machinic'. Extending the argument articulated in my book, Love and Other Technologies, this article asks how the emergence of virtual dating and other techno-inflected treatments of romance are working to undo our jealously held notions of intimacy and identity. It concludes that all sex can be considered cybersex, given the communication flows that occur both before, during and after the act. For, as we continue to enframe the discourse of intimacy via new and mobile media, we find it increasingly difficult to deny that intensified inter-subjectivity is always already a matter of technics. Indeed, what Heidegger says of modern technology can effectively be applied to modern love: that it embodies an `unreasonable demand' of nature (and thus has the capacity to reveal something essential about the posthuman condition). (shrink)

This article describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behaviour of more traditional deduction engines such as theorem provers.The article explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of (...) Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this article include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values.The algorithms and techniques described in this article are all publicly released and freely available in the Semantic Vectors open-source software package.1. (shrink)

When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested that even if such (...) a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient’s (former) autonomy since it draws on the ‘wrong’ kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently ‘fine-tuned’ on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient’s preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient’s own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies. (shrink)

Given the profound influence of social media and emerging evidence of its effects on human behavior and health, bioethicists have an important role to play in the development of professional standards of conduct for health professionals using social media and in the design of online systems themselves. In short, social media is a bioethics issue that has serious implications for medical practice, research, and public health. Here, we inventory several ethical issues across four areas at the intersection of social media (...) and health: the impact of social networking sites on the doctor‐patient relationship, the development of e‐health platforms to deliver care, the use of online data and algorithms to inform health research, and the broader public health consequences of widespread social media use. In doing so, we review discussions of these topics and emphasize the need for bioethics to focus more deeply on the ways online technology platforms are designed and implemented. We argue that bioethicists should turn their attention to the ways in which consumer engagement, bias, and profit maximization shape online content and, consequently, human behavior and health. We also offer a set of recommendations and suggest future directions for addressing ethical challenges in these domains. (shrink)

Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...) accessible hardware and encourages the development of complete, self-contained applications, from data collection to deployment. To this end, a collaboration between academia and industry produced a four part MOOC that provides application-oriented instruction on how to develop solutions using TinyML. The series is openly available on the edX MOOC platform, has no prerequisites beyond basic programming, and is designed for global learners from a variety of backgrounds. It introduces real-world applications, ML algorithms, data-set engineering, and the ethi- cal considerations of these technologies through hands-on programming and deployment of TinyML applications in both the cloud and on their own microcontrollers. To facili- tate continued learning, community building, and collaboration beyond the courses, we launched a standalone website, a forum, a chat, and an optional course-project com- petition. We also open-sourced the course materials, hoping they will inspire the next generation of ML practitioners and educators and further broaden access to cutting-edge ML technologies. (shrink)

The major transcript variants of human protein‐coding genes are annotated to a certain degree of accuracy combining manual curation, transcript data, and proteomics evidence. However, there is considerable disagreement on the annotation of about 2000 genes—they can be protein‐coding, noncoding, or pseudogenes—and on the annotation of most of the predicted alternative transcripts. Pure transcriptome mapping approaches seem to be limited in discriminating functional expression from noise. These limitations have partially been overcome by dedicated algorithms to detect alternative spliced micro‐exons and (...) wobble splice variants. Recently, knowledge about splice mechanism and protein structure are incorporated into an algorithm to predict neighboring homologous exons, often spliced in a mutually exclusive manner. Predicted exons are evaluated by transcript data, structural compatibility, and evolutionary conservation, revealing hundreds of novel coding exons and splice mechanism re‐assignments. The emerging human pan‐genome is necessitating distinctive annotations incorporating differences between individuals and between populations. (shrink)

Digital platforms and application software have changed how people work in a range of industries. Empirical studies of the gig economy have raised concerns about new systems of algorithmic management exercised over workers and how these alter the structural conditions of their work. Drawing on the republican literature, we offer a theoretical account of algorithmic domination and a framework for understanding how it can be applied to ride hail and food delivery services in the on-demand economy. We (...) argue that certain algorithms can facilitate new relationships of domination by sustaining a socio-technical system in which the owners and managers of a company dominate workers. This analysis has implications for the growing use of algorithms throughout the gig economy and broader labor market. (shrink)

We analyze the pointwise convergence of a sequence of computable elements of L1 in terms of algorithmic randomness. We consider two ways of expressing the dominated convergence theorem and show that, over the base theory RCA0, each is equivalent to the assertion that every Gδ subset of Cantor space with positive measure has an element. This last statement is, in turn, equivalent to weak weak Königʼs lemma relativized to the Turing jump of any set. It is also equivalent to (...) the conjunction of the statement asserting the existence of a 2-random relative to any given set and the principle of Σ2 collection. (shrink)

With increasing use of automated algorithmic decision-making, issues of algorithmic fairness have attracted much attention lately. In this growing literature, existing concepts from ethics and political philosophy are often applied to new contexts. The reverse—that novel insights from the algorithmic fairness literature are fed back into ethics and political philosophy—is far less established. However, this short commentary on Baumann and Loi (Philosophy & Technology, 36(3), 45 2023) aims to do precisely this. Baumann and Loi argue that among (...) algorithmic group fairness measures proposed, one—sufficiency (well-calibration) is morally defensible for insurers to use, whereas independence (statistical parity or demographic parity) and separation (equalized odds) are not normatively appropriate in the insurance context. Such a result may seem to be of relatively narrow interest to insurers and insurance scholars only. We argue, however, that arguments such as that offered by Baumann and Loi have an important but so far overlooked connection to the derivation of the minimal state offered by Nozick (1974) and thus to political philosophy at large. (shrink)

The accurate annotation of an unknown protein sequence depends on extant data of template sequences. This could be empirical or sets of reference sequences, and provides an exhaustive pool of probable functions. Individual methods of predicting dominant function possess shortcomings such as varying degrees of inter-sequence redundancy, arbitrary domain inclusion thresholds, heterogeneous parameterization protocols, and ill-conditioned input channels. Here, I present a rigorous theoretical derivation of various steps of a generic algorithm that integrates and utilizes several statistical methods to predict (...) the dominant function in unknown protein sequences. The accompanying mathematical proofs, interval definitions, analysis, and numerical computations presented are meant to offer insights not only into the specificity and accuracy of predictions, but also provide details of the operatic mechanisms involved in the integration and its ensuing rigor. The algorithm uses numerically modified raw hidden markov model scores of well defined sets of training sequences and clusters them on the basis of known function. The results are then fed into an artificial neural network, the predictions of which can be refined using the available data. This pipeline is trained recursively and can be used to discern the dominant principal function, and thereby, annotate an unknown protein sequence. Whilst, the approach is complex, the specificity of the final predictions can benefit laboratory workers design their experiments with greater confidence. -/- . (shrink)

This paper argues that social media companies’ power to regulate communication in the public sphere illustrates a novel type of domination. The idea is that, since social media companies can partially dictate the terms of citizens’ political participation in the public sphere, they can arbitrarily interfere with the choices individuals make qua citizens. I contend that social media companies dominate citizens in two different ways. First, I focus on the cases in which social media companies exercise direct control over (...) political speech. They exercise quasi-public power over citizens because their regulation of speech on social media platforms implies the capacity to arbitrarily interfere with citizens’ democratic contestation in the political system. Second, companies’ algorithmic governance entails the capacity to interfere with citizens’ choices about what mode of discursive engagement they endorse in their relationships with fellow citizens. By raising the cost of deliberative engagement, companies narrow citizens’ choice menu. (shrink)

The paper examines some of the processes of the closely knit relationship between Google’s ideologies of neutrality and objectivity and global market dominance. Neutrality construction comprises an important element sustaining the company’s economic position and is reflected in constant updates, estimates and changes to utility and relevance of search results. Providing a purely technical solution to these issues proves to be increasingly difficult without a human hand in steering algorithmic solutions. Search relevance fluctuates and shifts through continuous tinkering and (...) tweaking of the search algorithm. The company also uses third parties to hire human raters for performing quality assessments of algorithmic updates and adaptations in linguistically and culturally diverse global markets. The adaptation process contradicts the technical foundations of the company and calculations based on the initial Page Rank algorithm. Annual market reports, Google’s Search Quality Rating Guidelines, and reports from media specialising in search engine optimisation business are analysed. The Search Quality Rating Guidelines document provides a rare glimpse into the internal architecture of search algorithms and the notions of utility and relevance which are presented and structured as neutral and objective. Intertwined layers of ideology, hidden labour of human raters, advertising revenues, market dominance and control are discussed throughout the paper. (shrink)

Big Data evangelists often argue that algorithms make decision-making more informed and objective—a promise hotly contested by critics of these technologies. Yet, to date, most of the debate has focused on the instruments themselves, rather than on how they are used. This article addresses this lack by examining the actual practices surrounding algorithmic technologies. Specifically, drawing on multi-sited ethnographic data, I compare how algorithms are used and interpreted in two institutional contexts with markedly different characteristics: web journalism and criminal (...) justice. I find that there are surprising similarities in how web journalists and legal professionals use algorithms in their work. In both cases, I document a gap between the intended and actual effects of algorithms—a process I analyze as “decoupling.” Second, I identify a gamut of buffering strategies used by both web journalists and legal professionals to minimize the impact of algorithms in their daily work. Those include foot-dragging, gaming, and open critique. Of course, these similarities do not exhaust the differences between the two cases, which are explored in the discussion section. I conclude with a call for further ethnographic work on algorithms in practice as an important empirical check against the dominant rhetoric of algorithmic power. (shrink)

Effective content moderation by social platforms is both important and difficult; numerous issues arise from the volume of information, the culturally sensitive and contextual nature of that information, and the nuances of human communication. Attempting to scale moderation, social platforms are increasingly adopting automated approaches to suppressing communications that they deem undesirable. However, this brings its own concerns. This paper examines the structural effects of algorithmic censorship by social platforms to assist in developing a fuller understanding of the risks (...) of such approaches to content moderation. This analysis shows that algorithmic censorship is distinctive for two reasons: in potentially bringing all communications carried out on social platforms within reach and in potentially allowing those platforms to take a more active, interventionist approach to moderating those communications. Consequently, algorithmic censorship could allow social platforms to exercise an unprecedented degree of control over both public and private communications. Moreover, commercial priorities would be inserted further into the everyday communications of billions of people. Due to the dominance of the web by a few social platforms, this may be difficult or impractical to escape for many people, although opportunities for resistance do exist. (shrink)

An amendment to this paper has been published and can be accessed via the original article.

Although overarching if not foundational conceptualizations of digital governance in the field of critical data studies aptly account for and explain subjection, calculated resistance is left conceptually unattended despite case studies that document instances of resistance. I ask at the outset why conceptualizations of digital governance are so bleak, and I argue that all are underscored implicitly by a Deleuzian theory of desire that overlooks agency, defined here in Foucauldian terms. I subsequently conceptualize digital governance as encompassing subjection as well (...) as resistance, and I cast the two in relational perspective by making use of the concepts “affordance” and “assemblage” in conjunction with multiple subjectivities and Foucault's view of power as productive as well as his view of resistance as an “antagonism of strategies” in his late scholarship on resistance, ethics, and subjectivity. I offer examples of salient modes of what I call “productive” resistance, and from a Foucauldian perspective I explain how each mode targets and subverts technologies of repressive power to produce new elements of the digital environment and construct new truths. I conclude by recognizing the agency embodied in resistance as an end in itself, but I also consider that modes of productive resistance can have extrinsic value as they affect the fluid interaction among elements of the digital environment, potentially disrupting the presumed structure of dominance and dependence, and opening our conceptualization of algorithmic life to hopeful possibilities for change. (shrink)

This article examines the interplay between contemporary algorithmic security technology and the political theory of the state of exception. I argue that the exception, as both a political and a technological concept, provides a crucial way to understand the power operating through machine learning technologies used in the security apparatuses of the modern state. I highlight how algorithmic security technology, through its inherent technical properties, carries exceptions throughout its political and technological architecture. This leads me to engage with (...) Theodor Adorno’s negative dialectics to interrogate the question of ‘ground truth’ in machine learning. I conclude that most machine learning technology asserts identity between itself and bourgeois reality – and thus inherently reinforces and reproduces the relations of domination entailed in that image of the world. However, space still exists for machine learning to operate within spaces of political non-identity, or exceptions to the bourgeois totality, and aid in liberatory politics. (shrink)

In recent years, artificial intelligence has been deployed by online platforms to prevent the upload of allegedly illegal content or to remove unwarranted expressions. These systems are trained to spot objectionable content and to remove it, block it, or filter it out before it is even uploaded. Artificial intelligence filters offer a robust approach to content moderation which is shaping the public sphere. This dramatic shift in norm setting and law enforcement is potentially game-changing for democracy. Artificial intelligence filters carry (...) censorial power, which could bypass traditional checks and balances secured by law. Their opaque and dynamic nature creates barriers to oversight, and conceals critical value choices and tradeoffs. Currently, we lack adequate tools to hold them accountable. This paper seeks to address this gap by introducing an adversarial procedure— – Contesting Algorithms. It proposes to deliberately introduce friction into the dominant removal systems governed by artificial intelligence. Algorithmic content moderation often seeks to optimize a single goal, such as removing copyright-infringing materials or blocking hate speech, while other values in the public interest, such as fair use or free speech, are often neglected. Contesting algorithms introduce an adversarial design which reflects conflicting values, and thereby may offer a check on dominant removal systems. Facilitating an adversarial intervention may promote democratic principles by keeping society in the loop. An adversarial public artificial intelligence system could enhance dynamic transparency, facilitate an alternative public articulation of social values using machine learning systems, and restore societal power to deliberate and determine social tradeoffs. (shrink)

This paper explores the intersection of René Girard's mimetic theory and the algorithmic society, particularly in the context of the potential advent of Artificial General Intelligence (AGI). Girard's theory, which elucidates the dynamics of desire, rivalry, scapegoating, and the sacrificial crisis, provides a unique lens through which to examine the complexities of our relationship with AI and its role in the creation of the sacred. As individuals increasingly rely on AI recommendations, the distinction between personal choice and algorithmic (...) manipulation becomes less clear, raising concerns about the authenticity of cultural expressions and the role of algorithms in shaping cultural narratives. The triangular structure of desire, with AI as the model and individuals as the imitators, underscores the power of algorithms in this process. The sacrificial crisis, a key concept in Girard's theory, becomes a critical point of reflection in the algorithmic society. The exposure of the scapegoating mechanism reveals the destructive potential of algorithmic manipulation and calls for new forms of understanding, empathy, and non-violent solutions. This paper argues that recognizing the sacrificial crisis can prompt individuals and society to critically examine the impact of AI's influence, challenge the narratives it perpetuates, and reclaim agency in the face of algorithmic dominance. This paper further discusses the potential implications of the emergence of AGI, which could intensify the influence of algorithms on the creation of the sacred due to its advanced cognitive capabilities and deep understanding of human desires and behaviors. This could fuel a rapid evolution of the mimetic ecosystem, with profound implications for personal freedom, independent decision-making, and the formation and preservation of individual identity. This paper concludes by emphasizing the need for responsible algorithmic practices and ethical considerations to ensure that the creation of the sacred serves the common good in the algorithmic society. (shrink)

The problem of algorithms is, I think, also the question of the framework by which we determine the validity of our knowledge. The frames built with the help of algorithms are strong, unambiguous and legible. This causes that algorithmic sciences are called, in colloquial language, ‘exact’ and the knowledge constructed in this way is referred to as ‘specific’. Not everyone is thinking about the fact that algorithms provide certain knowledge, but only if we meet certain restrictive conditions, we will (...) build new, additional kind of framework. According to Odo Marquard, this will be the case if we decide to dominate exclusive reason. This reason, i.e. the rejecting, bypassing and reducing reason, will bypass and disregard all the limitations that algorithmic knowledge carries, sometimes emphasizing the extremely arrogant basic advantage of algorithmic knowledge, i.e. its certainty. (shrink)

While the challenges workers face in the gig economy are now well-known, reflections on emancipatory solutions in political philosophy are still underdeveloped. Some have pleaded for enhancing workers' bargaining power through unionisation; others for enhancing exit options in the labour market. Both strategies, however, come with unin-tended side-effects and do not exhaust the full potential for worker self-government present in the digital gig economy. Using the republican theory of freedom as non-domination , I argue that G.D.H. Cole's 20th-century defence (...) of guild socialism offers a promising avenue for enhancing worker autonomy in the gig economy. Platform companies rely on relational and structural domination to undermine worker autonomy, but Cole's guild socialism was specifically designed to enhance autonomy in the workplace. Following Cole's advice today would amount to a defence of worker-owned cooperative platforms. By putting workers in control of platform design and governance, cooperative platforms create new opportunities for worker autonomy. However, platform coopera-tivism faces serious challenges if it plans on becoming a realistic alternative to the traditional gig economy. (shrink)

Purpose Algorithms are in the mainstream media news on an almost daily basis. Their context is invariably artificial intelligence and machine learning decision-making. In media articles, algorithms are described as powerful, autonomous actors that have a capability of producing actions that have consequences. Despite a tendency for deification, the prevailing critique of algorithms focuses on ethical concerns raised by decisions resulting from algorithmic processing. However, the purpose of this paper is to propose that the ethical concerns discussed are limited (...) in scope and suggest that it is not clear what concerns dominate the debate. Design/methodology/approach The paper uses a systematic mapping study approach to review articles appearing in leading UK national papers from the perspective of the ethical concerns over a period of one year. The articles are categorised using a widely cited framework detailing a taxonomy of ethical concerns. The UK context is important because of UK public policy initiatives around AI. Findings The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of widely accepted ethical concerns such as inscrutable evidence, misguided evidence, unfair outcomes and transformative effects. Originality/value The research presented in this paper contributes the first systematic mapping study of articles appearing in leading UK national papers from the perspective of the ethical concerns. The UK context is important because of UK public policy initiatives around AI. To review the media content from the perspective of ethical concerns, this paper uses the synthesised conceptual map of ethical concerns developed by Mittelstad et al. Given the dominance of that framework, this paper’s contribution is also an important instantiation and experimental validation of using that conceptual map. (shrink)

The heuristic search processes like simple genetic algorithms help in achieving optimization but do not guarantee robustness so there is an immediate need of a machine learning technique that also promises robustness. Diploid genetic algorithms ensure consistent results and can therefore replace Simple genetic algorithms in applications such as test data generation and regression testing, where robustness is more important. However, there is a need to review the work that has been done so far in the field. It is also (...) important to analyse the applicability of the premise of the dominance techniques applied so far in order to implement the technique. The work presents a systematic review of diploid genetic algorithms, examines the premise of the dominance relation used in different works and discusses the future scope. The work also discusses the biological basis of evaluating dominance. The work is important as the future of machine learning relies on techniques that are robust as well as efficient. (shrink)

Subgraph matching on a large graph has become a popular research topic in the field of graph analysis, which has a wide range of applications including question answering and community detection. However, traditional edge-cutting strategy destroys the structure of indivisible knowledge in a large RDF graph. On the premise of load-balancing on subgraph division, a dominance-partitioned strategy is proposed to divide a large RDF graph without compromising the knowledge structure. Firstly, a dominance-connected pattern graph is extracted from a pattern graph (...) to construct a dominance-partitioned pattern hypergraph, which divides a pattern graph as multiple fish-shaped pattern subgraphs. Secondly, a dominance-driven spectrum clustering strategy is used to gather the pattern subgraphs into multiple clusters. Thirdly, the dominance-partitioned subgraph matching algorithm is designed to conduct all isomorphic subgraphs on a cluster-partitioned RDF graph. Finally, experimental evaluation verifies that our strategy has higher time-efficiency of complex queries, and it has a better scalability on multiple machines and different data scales. (shrink)

Background There is a growing concern about artificial intelligence (AI) applications in healthcare that can disadvantage already under-represented and marginalised groups (eg, based on gender or race). Objectives Our objectives are to canvas the range of strategies stakeholders endorse in attempting to mitigate algorithmic bias, and to consider the ethical question of responsibility for algorithmic bias. Methodology The study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers. Results Findings (...) reveal considerable divergent views on three key issues. First, views on whether bias is a problem in healthcare AI varied, with most participants agreeing bias is a problem (which we call the bias-critical view), a small number believing the opposite (the bias-denial view), and some arguing that the benefits of AI outweigh any harms or wrongs arising from the bias problem (the bias-apologist view). Second, there was a disagreement on the strategies to mitigate bias, and who is responsible for such strategies. Finally, there were divergent views on whether to include or exclude sociocultural identifiers (eg, race, ethnicity or gender-diverse identities) in the development of AI as a way to mitigate bias. Conclusion/significance Based on the views of participants, we set out responses that stakeholders might pursue, including greater interdisciplinary collaboration, tailored stakeholder engagement activities, empirical studies to understand algorithmic bias and strategies to modify dominant approaches in AI development such as the use of participatory methods, and increased diversity and inclusion in research teams and research participant recruitment and selection. (shrink)

This research implements a recent evolutionary-based algorithm of equilibrium optimizer to resolve the constrained combined economic emission dispatch problem. This problem has two objective functions that represent the minimizing of generation costs and minimizing the emission of environmental pollution caused by generators. The proposed algorithm integrates the dominant criteria for multiobjective functions that allow the decision-maker to detect all the Pareto boundaries of constrained combined economic emission dispatch problem. In order to save the effort for the decision-maker to select the (...) best compromise alternative, a cluster study was carried out to minimize the size of the Pareto boundary to an acceptable size, representing all the characteristics of the main Pareto frontier. On the other hand, in order to deal with the infringement of constraints, a repair algorithm was used to preserve the viability of the particles. The proposed algorithm is applied to solve the standard 30-bus IEEE system with 6 generators to validate its robustness and efficiency to produce a well-distributed Pareto frontier for constrained combined economic emission dispatch problem. Compared with other studies, good results in solving constrained combined economic emission dispatch problem are obtained and a reasonable reduced Pareto set is found. (shrink)

A growing number of studies on fairness in artificial intelligence (AI) use the notion of intersectionality to measure AI fairness. Most of these studies take intersectional fairness to be a matter of statistical parity among intersectional subgroups: an AI algorithm is “intersectionally fair” if the probability of the outcome is roughly the same across all subgroups defined by different combinations of the protected attributes. This paper identifies and examines three fundamental problems with this dominant interpretation of intersectional fairness in AI. (...) First, the dominant approach is so preoccupied with the intersection of attributes/categories (e.g., race, gender) that it fails to address the intersection of oppression (e.g., racism, sexism), which is more central to intersectionality as a critical framework. Second, the dominant approach faces a dilemma between infinite regress and fairness gerrymandering: it either keeps splitting groups into smaller subgroups or arbitrarily selects protected groups. Lastly, the dominant view fails to capture what it really means for AI algorithms to be fair, in terms of both distributive and non-distributive fairness. I distinguish a strong sense of AI fairness from a weak sense that is prevalent in the literature, and conclude by envisioning paths towards strong intersectional fairness in AI. (shrink)

This study investigates the performance of 21 monolingual and 56 bilingual children aged 5;6-9;0 on German-LITMUS-sentence-repetition (SRT; Hamann et al., 2013) and nonword-repetition-tasks (NWRT; Grimm et al., 2014), which were constructed according to the LITMUS-principles (Language Impairment Testing in Multilingual Settings; Armon-Lotem et al., 2015). Both tasks incorporate complex structures shown to be cross-linguistically challenging for children with Specific Language Impairment (SLI) and aim at minimizing bias against bilingual children while still being indicative of the presence of language impairment across (...) language combinations. Given the great variability in bilingual language exposure and the potential effect of language experience on language performance in bilingual children, we examined whether background variables related to bilingualism, particularly, the degree language dominance as measured by relative amount of use and exposure, could compromise the diagnostic accuracy of the German-LITMUS-SRT and NWRT. We further investigated whether a combination of the two tasks provides better diagnostic accurracy. To address this, we used an unsupervised machine learning algorithm, the Partitioning-Around-Medoids (PAM), for deriving a clinical category for the children as ±language-impaired based on performance scores on SRT and/or NWRT while withholding information about their clinical status based on standardized assessment in L1/L2. Subsequently, we calculated diagnostic accuracy and investigated which background variables (age of onset, length of exposure, degree of language-dominance, socio-economic-status, and risk factors for SLI) best explained clinical-group-membership yielded from the PAM-analysis based on NWRT and/or SRT scores. Results show that although language-dominance influences the performance of bilingual typically-developing children, especially in the SRT, the diagnostic accuracy of the tools is not compromised by language dominance: while risk factors for SLI were significant predictors for clinical group membership in all models, language dominance did not contribute at all to explaining clinical cluster membership as typically-developing or SLI based on any of the combinations of the SRT and NWRT variables. Additionally, results confirm that a combination of SRT scored by correct target structure and the structurally more complex language-dependent part of the NWRT yields better diagnostic accuracy than single measures and is only sensitive for risk factors for SLI and not to dominance levels or SES. (shrink)

In this article, a new adaptive data-driven strategy for voice activity detection using empirical mode decomposition is proposed. Speech data are decomposed using an a posteriori, adaptive, data-driven EMD in the time domain to yield a set of physically meaningful intrinsic mode functions. Each IMF preserves the nonlinear and nonstationary property of the speech utterance. Among a set of IMFs, the IMF that contains source information dominantly called characteristic IMF can be identified and extracted by designing a zero-frequency filter-assisted peaking (...) resonator. The detected CIMF is used to compute energy using short-term processing. Choosing proper threshold, voiced regions in speech utterances are detected using frame energy. The proposed framework has been studied on both clean speech utterance and noisy speech utterance. The proposed method is used for voice activity detection in the presence of white noise and shows encouraging result in the presence of white noise up to 0 dB. (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)

Artificial intelligence has dramatically changed the way organizations communicate, understand, and interact with their potential consumers. In the context of this trend, the ethical considerations of advertising when applying AI should be the core question for marketers. This paper discusses six dominant algorithmic purchase decision pathways that align with ethical philosophies for online customers when buying a product/goods. The six ethical positions include: ethical egoism, deontology, relativist, utilitarianism, virtue ethics, and ethics of care. Furthermore, this paper launches an “intelligent (...) advertising” AI theme by examining its present and future as well as identifying the key phases of intelligent advertising. Several research questions are offered to guide future research on intelligent advertising to benefit ethical AI decision-making. Finally, several areas that can be widely applied to ethical intelligent advertising are suggested for future research. (shrink)

There is not one but many ways to picture the world--Australian "x-ray" pictures, cubish collages, Amerindian split-style figures, and pictures in two-point perspective each draw attention to different features of what they represent. Understanding Pictures argues that this diversity is the central fact with which a theory of figurative pictures must reckon. Lopes advances the theory that identifying pictures' subjects is akin to recognizing objects whose appearances have changed over time. He develops a schema for categorizing the different ways pictures (...) represent--the different kinds of meaning they have--and argues that that depiction's epistemic value lies in its representational diversity. He also offers a novel account of the phenomenology of pictorial experience, comparing pictures to visual prostheses like mirrors and binoculars. (shrink)

Limiting dangerous climate change is now widely believed to require negative emissions, a prospect some believe to be unjust and unacceptably risky. While NETs are not risk-free, I argue tha...

A growing body of empirical evidence suggests the existence of a Paradox of Choice, whereby a larger choice set leads to a lower expected payoff to the decisionmaker. These empirical findings contradict traditional choice-theoretic results in microeconomics and even social psychology, suggesting profound yet unexplained aspects of choice settings/behavior. The Paradox remains largely as a theoretically-rootless empirical phenomenon. We neither understand the mechanisms and conditions that generate it, nor whether the Paradox stems from choice behavior, choice setting, or both. We (...) present a general search model of consumer choice under incomplete information to examine the theoretical existence and conditions for the Paradox. The model departs from traditional microeconomic choice theory in assuming no “cognitive free lunches.” Search and evaluative efforts require time, focus, and opportunity cost in the model, as in real life. The model shows that conditions for Paradox readily exist, diminishing returns to potential value of the choice in choice set size is a necessary condition for a Paradox outcome, that a Paradox outcome can occur with or without a “choice overload” response by the decisionmaker, and that avoidance of a Paradox outcome is an impossibility in some choice settings (primitive to setting regardless of choice behavior). Lastly, we develop a pareto-improving choice set reduction algorithm that eliminates weakly dominated choice set elements and presents the restricted choice set to the decisionmaker. As such, it is shown that the algorithm acts to treat or mitigate the Paradox of Choice, as well as to pareto-improve choice-supporting evaluation more generally. Like established AI recommender systems, the novel algorithm filters choices. In the present case, the filtering is based upon identification of weakly dominated choice set elements. (shrink)

Empirical research on aesthetic response poses two challenges to philosophy. The more familiar challenge is that scientific explanations of aesthetic responses debunk what we take to be our reasons for those responses. One reaction to this challenge is an accommodation strategy that seeks to reconcile the scientific findings with an improved understanding of our normative reasons. This paper presents a more fundamental challenge: a well-established body of research in social psychology indicates that we routinely confabulate the reasons we give for (...) our aesthetic response. This challenges the accommodation strategy and suggests that philosophy should adopt a more radical naturalism about aesthetic response. (shrink)

Proponents of deliberative democracy believe deliberation provides the best chance of finding effective and legitimate climate policies. However, in many societies there is substantial evidence of biased cognition and polarisation about climate change. Further, many appear unable to distinguish reliable scientific information from false claims or misinformation. While deliberation significantly reduces polarisation about climate change, and can even increase the provision of reliable beliefs, these benefits are difficult to scale up, and are slow to affect whole societies. In response, I (...) propose a combined strategy of ‘thinking and nudging’. While deliberative theorists tend to view nudging askance, combining deliberation with nudges promises to be a timelier and more effective response to climate change than deliberation alone. I outline several proposals to improve societal deliberative capacity while reducing climate risks, including media reform, strategic communication and framing of debates, incentivising pro-climate behaviour change, and better education about science. (shrink)

We often ascribe possibility to the scenes that are displayed by mental or nonmental sensory images. The paper presents a novel argument for thinking that we are prima facie justified in ascribing metaphysical possibility to what is displayed by suitable visual images, and it argues that many of our imagery‐based ascriptions of metaphysical possibility are therefore prima facie justified. Some potential objections to the arguments are discussed, and some potential extensions of them, to cover nonvisual forms of imagery and nonmetaphysical (...) forms of possibility, are endorsed. (shrink)

The urgency of climate change has never been greater, nor the moral case for responding to it more compelling. This review essay critically compares Darrel Moellendorf's Mobilizing Hope and Catriona McKinnon's Climate Change and Political Theory. Moellendorf's book defends the moral importance of poverty alleviation through sustainable economic growth and argues for a mass climate movement based on the promise of a more prosperous future. By contrast, McKinnon provides a political vocabulary to articulate the many faces of climate injustice, and (...) to critically examine proposed policy solutions—notably including the indefinite pursuit of economic growth. While both find reasons to be hopeful, their wide-ranging accounts reflect different visions of what a just and sustainable future might look like. They reflect different understandings of sustainable development and the significance of environmental values; the scope of permissible climate activism; and the ethics of geoengineering. Building upon them, I argue in favor of a more pluralistic vision of a just climate future, one that is capable of speaking to the range of moral interests bearing upon the climate and biodiversity crises, and that supports sustainable development that is inclusive of diverse human-nature relationships. (shrink)

Visualizings, the simplest imaginings which employ visual imagery, have certain characteristic features; they are perspectival, for instance. Also, it seems that some but not all of our visualizings are imaginings of seeings. But it has been forcefully argued, for example by M.G.F. Martin and Christopher Peacocke, that all visualizings are imaginings of visual sensations. I block these arguments by providing an account of visualizings which allows for their perspectival nature and other features they typically have, but which also explains how (...) we can visualize things without thereby imagining visual sensations. (shrink)

Why do we tend to ascribe possibility to what we can imagine? One strategy for answering that question involves the thought that, just as sensory episodes often involve its seeming to us as though the world is certain ways, so imaginings involve its seeming to us that what we have imagined is possible. This chapter argues that while some imaginings do feature appearances of possibility, very many others do not; and it explores the broader relevance of its conclusions for modal (...) epistemology. (shrink)

We investigated the influence of social status on behavior in a modified dictator game. Since the DG contains an inherent dominance gradient, we examined the relationship between dictator decisions and recipient status, which was operationalized by three social identities and an artificial intelligence. Additionally, we examined the predictive value of social dominance orientation on the behavior of dictators toward the different social and non-social hierarchical recipients. A multilevel model analysis showed that recipients with the same status as the dictator benefited (...) the most and the artificial intelligence the least. Furthermore, SDO, regardless of social status, predicted behavior toward recipients in such a way that higher dominance was associated with lower dictator offers. In summary, participants treated other persons of higher and lower status equally, those of equal status better and, above all, an algorithm worst. The large proportion of female participants and the limited variance of SDO should be taken into account with regard to the results of individual differences in SDO. (shrink)

Can identity be vague? More exactly, can there be objects x and y such that it is vague whether x = y, and the vagueness is due to the objects themselves as opposed to vagueness in language used to denote the objects? The question has been extensively discussed since Evans (1978) where it was claimed that an affirmative answer was a necessary condition for the thesis that there could be vague objects. A recent, ingenious argument in Pinillos (2003) seeks to (...) establish the negative and show that it cannot be de re vague whether x = y. The argument depends crucially on count claims concerning objects whose identity conditions are de re vague, and so we must learn how to count such objects — clouds, persons and much else besides. When that has been accomplished we can see a way out of Pinillos’s argument, and claim that de re vague identity remains coherent. (shrink)

This chapter begins with a historical overview of aesthetics and the philosophy of art before turning to a discussion of how the philosophy of art bears upon human culture. It then considers the methods used in attacking problems in aesthetics and the philosophy of art by highlighting the distinctions between pure and applied philosophy, between internal and external perspectives on aesthetic and artistic phenomena, and between first-order and second-order methods. It also examines how aesthetics and the philosophy of art are (...) affected as the arts evolve and as empirical studies of aesthetic and artistic phenomena become well established in the social and behavioural sciences as well as the humanities. (shrink)

This chapter sketches an account of psychiatric explanation with roots in contemporary philosophy of science and suggests that it is a natural fit with what it will call the strong interpretation of the medical model in psychiatry. The chapter starts by distinguishing between strong and minimal ways to understand the medical model before it moves on to talk about explanation. The basic idea of the chapter is that the logic of the medical model, together with recent developments in the sciences (...) of the brain, suggests that psychiatry should be seen as a kind of cognitive neuroscience. The second part of the chapter discusses some issues in applying mechanistic explanatory models to mental disorders. Recent philosophical work on explanation in the cognitive neurosciences has seen it as mechanistic explanation. A mechanistic explanation shows how components of a system interact to give rise to the phenomenon to be explained. (shrink)