Autonomous mechanisms have been proposed to regulate certain aspects of society and are already being used to regulate business organisations. We take seriously recent proposals for algorithmic regulation of society, and we identify the existing technologies that can be used to implement them, most of them originally introduced in business contexts. We build on the notion of 'social machine' and we connect it to various ongoing trends and ideas, including crowdsourced task-work, social compiler, mechanism design, reputation management systems, (...) and social scoring. After showing how all the building blocks of algorithmic regulation are already well in place, we discuss possible implications for human autonomy and social order. The main contribution of this paper is to identify convergent social and technical trends that are leading towards social regulation by algorithms, and to discuss the possible social, political, and ethical consequences of taking this path. (shrink)

The world we inhabit is surrounded by ‘coded objects’ from credit cards to airplanes to telephones. Sadly the governance mechanisms of many of these technologies are only poorly understood, leading to the common premise that such technologies are ‘neutral’, thereby obscuring normative and power-related consequences of their design. In order to unpack supposedly neutral technologies, the following paper will try and foreground two of key questions around the technologies used on the global Internet: 1) how are content regulatory regimes governed (...) and 2) how are the algorithms embedded in software governed? The following paper will explore these two aspects in turn, before drawing conclusions on understanding the normative frameworks embedded in technological systems.Article first published online: 22 MARCH 2016. (shrink)

Autonomous mechanisms have been proposed to regulate certain aspects of society and are already being used to regulate business organisations. We take seriously recent proposals for algorithmic regulation of society, and we identify the existing technologies that can be used to implement them, most of them originally introduced in business contexts. We build on the notion of ‘social machine’ and we connect it to various ongoing trends and ideas, including crowdsourced task-work, social compiler, mechanism design, reputation management systems, (...) and social scoring. After showing how all the building blocks of algorithmic regulation are already well in place, we discuss the possible implications for human autonomy and social order. The main contribution of this paper is to identify convergent social and technical trends that are leading towards social regulation by algorithms, and to discuss the possible social, political, and ethical consequences of taking this path. (shrink)

This article puts into perspective the practice of financial regulation in contemporary financial markets, while a new normative order has emerged. This order, heralded by algorithmic technologies, changes the conditions for the exercise of regulation: to date, it has not yet been fully acknowledged nor understood by regulatory bodies. Computer code, replacing speech and writing, induces a changeover from one normative order to another in contemporary markets: the norm, previously explicated with recourse to interpretation, is now replaced (...) by an order characterized by calculation. Such paradigm change is identified based on a discussion of works by Gilles Deleuze. In so doing, it contributes to the developing research programme in the cultures of high-frequency trading (Lange et al. 2016) and also points at broader issues for conceptualising financial regulation. (shrink)

A wave of recent scholarship has warned about the potential for discriminatory harms of algorithmic systems, spurring an interest in algorithmic accountability and regulation. Meanwhile, parallel concerns about surveillance practices have already led to multiple successful regulatory efforts of surveillance technologies—many of which have algorithmic components. Here, we examine municipal surveillance regulation as offering lessons for algorithmic oversight. Taking the 2017 Seattle Surveillance Ordinance as our primary case study and surveying efforts across five other (...) cities, we describe the features of existing surveillance regulation; including procedures for describing surveillance technologies in detail, requirements for public engagement, and processes for establishing acceptable uses. Although the Seattle Surveillance Ordinance was not intended to address algorithmic accountability, we find these considerations to be relevant to the law’s aim of surfacing disparate impacts of systems in use. We also find that in notable cases government employees did not identify regulated algorithmic surveillance technologies as reliant on algorithmic or machine learning systems, highlighting definitional gaps that could hinder future efforts toward algorithmic regulation. We argue that finer-grained distinctions between types of information systems in the language of law and policy, and risk assessment tools integrated into their implementation would strengthen future regulatory efforts by rendering underlying algorithmic components more legible and accountable to political and community stakeholders. (shrink)

In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not (...) consider multiple stakeholders or the broader social context. In this article, we present an auditing framework to guide the ethical assessment of an algorithm. The audit instrument itself is comprised of three elements: a list of possible interests of stakeholders affected by the algorithm, an assessment of metrics that describe key ethically salient features of the algorithm, and a relevancy matrix that connects the assessed metrics to stakeholder interests. The proposed audit instrument yields an ethical evaluation of an algorithm that could be used by regulators and others interested in doing due diligence, while paying careful attention to the complex societal context within which the algorithm is deployed. (shrink)

While the academic separation of policing and regulation is still largely operative, points of convergence are more significant than ever in the digital age, starting with concomitant debates about algorithms as a new figure of power. From the policing of illegal activities to the regulation of legal ones, the algorithmization of such critical social ordering practices has been the subject of growing attention. These burgeoning discussions are focused on one common element: big data surveillance. In accordance with such (...) similarities and paralleled developments in policing and regulation, the article aims to further bridge the gap between literatures to respond to the calls for studying big data surveillance across institutional domains and social fields. To do so, it is focused on one case study that articulates algorithmic policing and regulation domains, in-between security and economic fields. This is the fight against illicit finance, i.e. ‘the global action against the financial flows that fuel crime and terrorism’. To what extent does big data surveillance make a difference in the main global policy of crime-fighting and financial regulation? Drawing on a fieldwork in a large North American bank, the present article takes stock of the algorithmic overlap between policing and regulation. It argues that the final result is policing and regulation of neither too much nor too little, which gives rise to automated and everyday mass surveillance while remaining as far removed from regulatory and crime-fighting ambitions as it is from dystopian visions of big data and algorithmic drama. (shrink)

The potential for biases being built into algorithms has been known for some time, yet literature has only recently demonstrated the ways algorithmic profiling can result in social sorting and harm marginalised groups. We contend that with increased algorithmic complexity, biases will become more sophisticated and difficult to identify, control for, or contest. Our argument has four steps: first, we show how harnessing algorithms means that data gathered at a particular place and time relating to specific persons, can (...) be used to build group models applied in different contexts to different persons. Thus, privacy and data protection rights, with their focus on individuals, do not protect from the discriminatory potential of algorithmic profiling. Second, we explore the idea that anti-discrimination regulation may be more promising, but acknowledge limitations. Third, we argue that in order to harness anti-discrimination regulation, it needs to confront emergent forms of discrimination or risk creating new invisibilities, including invisibility from existing safeguards. Finally, we outline suggestions to address emergent forms of discrimination and exclusionary invisibilities via intersectional and post-colonial analysis. (shrink)

The article discusses the use of algorithmic models in finance. Algo trading is widespread but also somewhat controversial in modern financial markets. It is a form of automated trading technology, which critics claim can, among other things, lead to market manipulation. Drawing on three cases, this article shows that manipulation also can happen in the reverse way, meaning that human traders attempt to make algorithms ‘make mistakes’ by ‘misleading’ them. These attempts to manipulate are very simple and immediately transparent (...) to humans. Nevertheless, financial regulators increasingly penalize such attempts to manipulate algos. The article explains this as an institutionalization of algo trading, a trading practice which is vulnerable enough to need regulatory protection. (shrink)

During the past decade, a small but rapidly growing number of Law&Tech scholars have been applying algorithmic methods in their legal research. This Article does it too, for the sake of saving disclosure regulation failure: a normative strategy that has long been considered dead by legal scholars, but conspicuously abused by rule-makers. Existing proposals to revive disclosure duties, however, either focus on the industry policies (e.g. seeking to reduce consumers’ costs of reading) or on rulemaking (e.g. by simplifying (...) linguistic intricacies). But failure may well depend on both. Therefore, this Article develops a `comprehensive approach', suggesting to use computational tools to cope with linguistic and behavioral failures at both the enactment and implementation phases of disclosure duties, thus filling a void in the Law & Tech scholarship. Specifically, it outlines how algorithmic tools can be used in a holistic manner to address the many failures of disclosures from the rulemaking in parliament to consumer screens. It suggests a multi-layered design where lawmakers deploy three tools in order to produce optimal disclosure rules: machine learning, natural language processing, and behavioral experimentation through regulatory sandboxes. To clarify how and why these tasks should be performed, disclosures in the contexts of online contract terms and privacy online are taken as examples. Because algorithmic rulemaking is frequently met with well-justified skepticism, problems of its compatibility with legitimacy, efficacy and proportionality are also discussed. (shrink)

An increasing number of regulations propose the notion of ‘AI audits’ as an enforcement mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the purpose of compliance and assurance currently have little to no agreed upon practices, procedures, taxonomies, and standards. We propose the ‘criterion audit’ as an operationalizable compliance and assurance external audit framework. We model elements of this approach after financial auditing practices, and argue (...) that AI audits should similarly provide assurance to their stakeholders about AI organizations’ ability to govern their algorithms in ways that mitigate harms and uphold human values. We discuss the necessary conditions for the criterion audit, and provide a procedural blueprint for performing an audit engagement in practice. We illustrate how this framework can be adapted to current regulations by deriving the criteria on which ‘bias audits’ for hiring algorithms can be performed, as required by the recently effective New York City Local Law 144 of 2021. We conclude by offering critical discussion on the benefits, inherent limitations, and implementation challenges of applying practices of the more mature financial auditing industry to AI auditing where robust guardrails against quality assurance issues are only starting to emerge. Our discussion as informed by experiences in performing these audits in practice highlights the critical role that an audit ecosystem plays in ensuring the effectiveness of such methodology. (shrink)

Philippe Baumard et Nadim Kobeissi explorent la relation entre liberté, transparence et sécurité. Dans le contexte de l’invalidation du 6 octobre 2015 de l’accord « Safe Harbour » par la Cour de justice de l’Union européenne, et revenant sur les implications de l’affaire Volkswagen, les auteurs dénouent les liens réputés inextricables entre les notions de souveraineté numérique, libertés individuelles et publiques, et de sécurité. Les deux auteurs considèrent ainsi la perspective qu’une meilleure transparence, gérée avec rigueur, peut battre aussi bien (...) l’efficience de marché, sans pour autant la délaisser, qu’une régulation excessive, ou l’opacité d’une économie numérique fondée sur le secret industriel et le secret des algorithmes ». (shrink)

In philosophy of mind, zombies are imaginary creatures that are exact physical duplicates of conscious subjects but for whom there is no first-personal experience. Zombies are meant to show that physicalism—the theory that the universe is made up entirely out of physical components—is false. In this paper, I apply the zombie thought experiment to the realm of morality to assess whether moral agency is something independent from sentience. Algorithms, I argue, are a kind of functional moral zombie, such that thinking (...) about the latter can help us better understand and regulate the former. I contend that the main reason why algorithms can be neither autonomous nor accountable is that they lack sentience. Moral zombies and algorithms are incoherent as moral agents because they lack the necessary moral understanding to be morally responsible. To understand what it means to inflict pain on someone, it is necessary to have experiential knowledge of pain. At most, for an algorithm that feels nothing, ‘values’ will be items on a list, possibly prioritised in a certain way according to a number that represents weightiness. But entities that do not feel cannot value, and beings that do not value cannot act for moral reasons. (shrink)

This paper argues that instituting Citizen Boards of Governance (CBGs) is the optimal strategy to democratically contain Big Tech’s algorithmic powers in the digital public sphere. CBGs are bodies of randomly selected citizens that are authorized to govern the algorithmic infrastructure of Big Tech platforms. The main advantage of CBGs is to tackle the concentrated powers of private tech corporations without giving too much power to governments. I show why this is a better approach than ordinary state (...) class='Hi'>regulation or relying on market mechanisms. My proposal follows from the critique of Big Tech’s concentrated powers, and explains how this justifies democratizing algorithms in the digital public sphere. My approach thus speaks to a core commitment in democratic theory: enhancing the autonomy of the public sphere from the centers of powers in modern societies, be it corporations or governments. (shrink)

Many artificial intelligence (AI) systems currently used for decision-making are opaque, i.e., the internal factors that determine their decisions are not fully known to people due to the systems’ computational complexity. In response to this problem, several researchers have argued that human decision-making is equally opaque and since simplifying, reason-giving explanations (rather than exhaustive causal accounts) of a decision are typically viewed as sufficient in the human case, the same should hold for algorithmic decision-making. Here, I contend that this (...) argument overlooks that human decision-making is sometimes significantly more transparent and trustworthy than algorithmic decision-making. This is because when people explain their decisions by giving reasons for them, this frequently prompts those giving the reasons to govern or regulate themselves so as to think and act in ways that confirm their reason reports. AI explanation systems lack this self-regulative feature. Overlooking it when comparing algorithmic and human decision-making can result in underestimations of the transparency of human decision-making and in the development of explainable AI that may mislead people by activating generally warranted beliefs about the regulative dimension of reason-giving. (shrink)

Marketing and web analytic companies have implemented sophisticated algorithms to observe, analyze, and identify users through large surveillance networks online. These computer algorithms have the capacity to infer categories of identity upon users based largely on their web-surfing habits. In this article I will first discuss the conceptual and theoretical work around code, outlining its use in an analysis of online categorization practices. The article will then approach the function of code at the level of the category, arguing that an (...) analysis of coded computer algorithms enables a supplement to Foucauldian thinking around biopolitics and biopower, of what I call soft biopower and soft biopolitics. These new conceptual devices allow us to better understand the workings of biopower at the level of the category, of using computer code, statistics and surveillance to construct categories within populations according to users’ surveilled internet history. Finally, the article will think through the nuanced ways that algorithmic inference works as a mode of control, of processes of identification that structure and regulate our lives online within the context of online marketing and algorithmic categorization. (shrink)

Critical algorithm scholarship has demonstrated the difficulties of attributing accountability for the actions and effects of algorithmic systems. In this commentary, we argue that we cannot stop at denouncing the lack of accountability for algorithms and their effects but must engage the broader systems and distributed agencies that algorithmic systems exist within; including standards, regulations, technologies, and social relations. To this end, we explore accountability in “the Generated Detective,” an algorithmically generated comic. Taking up the mantle of detectives (...) ourselves, we investigate accountability in relation to this piece of experimental fiction. We problematize efforts to effect accountability through transparency by undertaking a simple operation: asking for permission to re-publish a set of the algorithmically selected and modified words and images which make the frames of the comic. Recounting this process, we demonstrate slippage between the “complication” of the algorithm and the obscurity of the legal and institutional structures in which it exists. (shrink)

The paper deals with the difference between who and what we are in order to take an ethical perspective on algorithms and their regulation. The present casting of ourselves as homo digitalis implies the possibility of projecting who we are as social beings sharing a world, into the digital medium, thereby engendering what can be called digital whoness, or a digital reification of ourselves. A main ethical challenge for the evolving digital age consists in unveiling this ethical difference, particularly (...) when dealing with algorithms and their regulation in the context of human relationships. The paper addresses by way of example some issues raised by autonomous cars. (shrink)

We live in a world in which ‘smart’ algorithmic tools are regularly used to structure and control our choice environments. They do so by affecting the options with which we are presented and the choices that we are encouraged or able to make. Many of us make use of these tools in our daily lives, using them to solve personal problems and fulfill goals and ambitions. What consequences does this have for individual autonomy and how should our legal and (...) regulatory systems respond? This chapter defends three claims by way of response. First, it argues that autonomy is indeed under threat in some new and interesting ways. Second, it evaluates and disputes the claim that we shouldn’t overestimate these new threats because the technology is just an old wolf in a new sheep’s clothing. Third, and finally, it looks at responses to these threats at both the individual and societal level and argues that although we shouldn’t encourage an attitude of ‘helplessness’ among the users of algorithmic tools there is an important role for legal and regulatory responses to these threats that go beyond what are currently on offer. (shrink)

To analyze which ethically relevant biases have been identified by academic literature in artificial intelligence algorithms developed either for patient risk prediction and triage, or for contact tracing to deal with the COVID-19 pandemic. Additionally, to specifically investigate whether the role of social determinants of health have been considered in these AI developments or not. We conducted a scoping review of the literature, which covered publications from March 2020 to April 2021. ​Studies mentioning biases on AI algorithms developed for contact (...) tracing and medical triage or risk prediction regarding COVID-19 were included. From 1054 identified articles, 20 studies were finally included. We propose a typology of biases identified in the literature based on bias, limitations and other ethical issues in both areas of analysis. Results on health disparities and SDOH were classified into five categories: racial disparities, biased data, socio-economic disparities, unequal accessibility and workforce, and information communication. SDOH needs to be considered in the clinical context, where they still seem underestimated. Epidemiological conditions depend on geographic location, so the use of local data in studies to develop international solutions may increase some biases. Gender bias was not specifically addressed in the articles included. The main biases are related to data collection and management. Ethical problems related to privacy, consent, and lack of regulation have been identified in contact tracing while some bias-related health inequalities have been highlighted. There is a need for further research focusing on SDOH and these specific AI apps. (shrink)

A growing literature is taking an institutionalist and governance perspective on how algorithms shape society based on unprecedented capacities for managing social complexity. Algorithmic governance altogether emerges as a novel and distinctive kind of societal steering. It appears to transcend established categories and modes of governance—and thus seems to call for new ways of thinking about how social relations can be regulated and ordered. However, as this paper argues, despite its novel way of realizing outcomes of collective steering and (...) coordination, it can nevertheless be grasped with an old and fundamental figure in political philosophy: that of Thomas Hobbes’ Leviathan. Comparing algorithmic governance with this figure serves to highlight their similarities as socio-political arrangements, and specifically to clarify how algorithmic governance parallels the apolitical traits of the Leviathan—it eliminates the political as it requires compliance and forgoing contestation to best fulfill its role and to produce satisfying outcomes. (shrink)

Algorithmic systems are increasingly used by state agencies to inform decisions about humans. They produce scores on risks of recidivism in criminal justice, indicate the probability for a job seeker to find a job in the labor market, or calculate whether an applicant should get access to a certain university program. In this contribution, we take an interdisciplinary perspective, provide a bird’s eye view of the different key decisions that are to be taken when state actors decide to use (...) an algorithmic system, and illustrate these decisions with empirical examples from case studies. Building on these insights, we discuss the main pitfalls and promises of the use of algorithmic system by the state and focus on four levels: The most basic question whether an algorithmic system should be used at all, the regulation and governance of the system, issues of algorithm design, and, finally, questions related to the implementation of the system on the ground and the human–machine-interaction that comes with it. Based on our assessment of the advantages and challenges that arise at each of these levels, we propose a set of crucial questions to be asked when such intricate matters are addressed. (shrink)

Recent rapid advances in Artificial Intelligence and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by (...) machines. To achieve this, we can adapt the concept of human-in-the-loop from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop, which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

This paper studies the information of big data in the digital publishing industry chain and adopts advanced algorithms for its fusion calculation. The basic theory of digital publishing ecological chain is dissected, the construction requirements, construction methods, and construction paths of digital publishing ecological chain are analysed, and feasible construction measures are proposed. It also defines the connotation of the fusion of knowledge services between publishing institutions and libraries in the digital era; then analyses the characteristics and principles of the (...) fusion of knowledge services between publishing institutions and libraries in the digital era; and finally sorts out the theoretical foundations such as synergy theory, information integration service theory, and game theory. Meanwhile, this paper also studies the flow of digital publishing resources and empirically analyses the eco-efficiency of digital publishing eco-chain by using metabolic network analysis, population analysis, and life cycle analysis, and it finds the eco-efficiency problems of the existing e-book eco-chain from its analysis. Finally, the imbalance in the digital publishing ecological chain and its hazards are analysed, and specific regulation and optimization measures are proposed. The research in this paper makes up for the deficiencies of related studies and can well solve the problems that exist in the previous and provide theoretical support for the healthy development of digital publishing enterprises. (shrink)

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast (...) to the right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

This article discusses the role that algorithmic thinking and management play in health care and the kind of exclusions this might create. We argue that evidence‐based medicine relies on research and data to create pathways for patient journeys. Coupled with data‐based algorithmic prediction tools in health care, they establish what could be called health care algorithmics—a mode of management of healthcare that produces forms of algorithmic governmentality. Relying on a critical posthumanist perspective, we show how healthcare algorithmics (...) is contingent on the way authority over bodies is produced and how predictive health care algorithms can reproduce inequalities of the worlds from which they are made, centreing possible futures on existing normativities regulated through algorithmic biopower. In contrast to that, we explore posthuman speculative ethics as a way to challenge understanding of ‘ethics’ and ‘care’ in healthcare algorithmics. We suggest some possible avenues towards working speculative ethics into health care while still being critically attentive to algorithmic modes of management and prediction in health care. (shrink)

There is increasing criticism on the use of big data and algorithms in public governance. Studies revealed that algorithms may reinforce existing biases and defy scrutiny by public officials using them and citizens subject to algorithmic decisions and services. In response, scholars have called for more algorithmic transparency and regulation. These are useful, but ex post solutions in which the development of algorithms remains a rather autonomous process. This paper argues that co-design of algorithms with relevant stakeholders (...) from government and society is another means to achieve responsible and accountable algorithms that is largely overlooked in the literature. We present a case study of the development of an algorithmic tool to estimate the populations of refugee camps to manage the delivery of emergency supplies. This case study demonstrates how in different stages of development of the tool—data selection and pre-processing, training of the algorithm and post-processing and adoption—inclusion of knowledge from the field led to changes to the algorithm. Co-design supported responsibility of the algorithm in the selection of big data sources and in preventing reinforcement of biases. It contributed to accountability of the algorithm by making the estimations transparent and explicable to its users. They were able to use the tool for fitting purposes and used their discretion in the interpretation of the results. It is yet unclear whether this eventually led to better servicing of refugee camps. (shrink)

To date, research examining the socio-spatial effects of smart city technologies have charted how they are reconfiguring the production of space, spatiality and mobility, and how urban space is governed, but have paid little attention to how the temporality of cities is being reshaped by systems and infrastructure that capture, process and act on real-time data. In this article, we map out the ways in which city-scale Internet of Things infrastructures, and their associated networks of sensors, meters, transponders, actuators and (...) algorithms, are used to measure, monitor and regulate the polymorphic temporal rhythms of urban life. Drawing on Lefebvre, and subsequent research, we employ rhythmanalysis in conjunction with Miyazaki’s notion of ‘algorhythm’ and nascent work on algorithmic governance, to develop a concept of ‘algorhythmic governance’. We then use this framing to make sense of two empirical case studies: a traffic management system and sound monitoring and modelling. Our analysis reveals: how smart city technologies computationally perform rhythmanalysis and undertake rhythm-making that intervenes in space-time processes; distinct forms of algorhythmic governance, varying on the basis of adaptiveness, immediacy of action, and whether humans are in-, on-, or, off-the-loop; and a number of factors that shape how algorhythmic governance works in practice. (shrink)

This article examines algorithmic content moderation, using the moderation of violent extremist content as a specific case. In recent years, algorithms have increasingly been mobilized to perform essential moderation functions for online social media platforms such as Facebook, YouTube, and Twitter, including limiting the proliferation of extremist speech. Drawing on Katherine Hayles’ concept of “cognitive assemblages” and the Critical Security Studies literature, we show how algorithmic regulation operates within larger assemblages of humans and non-humans to influence the (...) surveillance and regulation of information flows. We argue that the dynamics of algorithmic regulation are more liquid, cobbled together and distributed than it appears. It is characterized by a set of shifting human and machine entities, which mix traditional surveillance methods with more sophisticated tools, and whose linkages and interactions are transient. The processes that enable the consolidation of knowledge about risky profiles and contents are, therefore, collective and distributed among humans and machines. This allows us to argue that the cognitive assemblages involved in content moderation become a cobbled space of preemptive calculation. (shrink)

Businesses increasingly rely on algorithms that are data-trained sets of decision rules (i.e., the output of the processes often called “machine learning”) and implement decisions with little or no human intermediation. In this article, we provide a philosophical foundation for the claim that algorithmic decision-making gives rise to a “right to explanation.” It is often said that, in the digital era, informed consent is dead. This negative view originates from a rigid understanding that presumes informed consent is a static (...) and complete transaction. Such a view is insufficient, especially when data are used in a secondary, noncontextual, and unpredictable manner—which is the inescapable nature of advanced artificial intelligence systems. We submit that an alternative view of informed consent—as an assurance of trust for incomplete transactions—allows for an understanding of why the rationale of informed consent already entails a right to ex post explanation. (shrink)

Bimanual robots have been studied for decades and regulation on internal force of the being held object by two manipulators becomes a research interest in recent years. In this paper, based on impedance model, a method to obtain the optimal target position for bimanual robots to hold an object is proposed. We introduce a cost function combining the errors of the force and the position and manage to minimize its value to gain the optimal coordinates for the robot end (...) effectors. To implement this method, two necessary algorithms are presented, which are the closed-loop inverse kinematics method to work out joint positions from desired EE pose and the generalized-momentum-based external force observer to measure the subjected force acting on the EE so as to properly compensate for the joint torques. To verify the effectiveness, practicality, and adaptivity of the proposed scheme, in the simulation, a bimanual robot system with three degrees of freedom in every manipulator was constructed and employed to hold an object, where the results are satisfactory. (shrink)

In this paper, a normalized robust FOPID controller regulation algorithm is proposed. Only one parameter k is necessary to be tuned in the controller regulation process, so the proposed control algorithm is convenient to be applied on both fractional-order systems and integer-order systems. A robustness evaluation function is constructed based on the small gain theorem. Larger robustness evaluation function value will help the system achieve better robustness performance. Another parameter, β, is also available to serve as a tuning (...) knob when larger robust evaluation function value is needed. Therefore, the controlled systems can be stabilized and can achieve quite satisfactory robust control performance using the proposed algorithm. The corresponding robust analysis results are obtained according to different conditions in the discussion. For a special case of widely used fractional-order systems, the FOPI and FOID controllers are presented based on the same tuning scheme together with their robustness discussion. Some examples are shown to verify the robustness of systems controlled by the proposed algorithm. (shrink)

If whatever counts as merit for some purpose is unevenly distributed, a decision procedure that accurately sorts people on that basis will “pick up” and reproduce the pre-existing pattern in ways that more random, less merit-tracking procedures would not. This dynamic is an important cause for concern about the use of predictive models to allocate goods and opportunities. In this article, I distinguish two different objections that give voice to that concern in different ways. First, decision procedures may contribute to (...) future social injustice and other social ills by sustaining or aggravating patterns that undermine equality of status and opportunity. Second, the same decision procedures may wrong particular individuals by compounding prior injustices that explain those persons’ predicted or actual characteristics. I argue for the importance of the first idea and raise doubts about the second. In normative assessments and legal regulation of algorithmic decisionmaking, as in our thinking about anti-discrimination norms more broadly, a central concern ought to be the prospect of entrenching harmful and unjust patterns—quite apart from any personal wrong done to the individuals about whom predictions are made. (shrink)

Here, we provide an ethical analysis of discrimination in private insurance to guide the application of non-discriminatory algorithms for risk prediction in the insurance context. This addresses the need for ethical guidance of data-science experts, business managers, and regulators, proposing a framework of moral reasoning behind the choice of fairness goals for prediction-based decisions in the insurance domain. The reference to private insurance as a business practice is essential in our approach, because the consequences of discrimination and predictive inaccuracy in (...) underwriting are different from those of using predictive algorithms in other sectors. Here we focus on the trade-off in the extent to which one can pursue indirect non-discrimination versus predictive accuracy. The moral assessment of this trade-off is related to the context of application—to the consequences of inaccurate risk predictions in the insurance domain. (shrink)

With Artificial Intelligence entering our lives in novel ways—both known and unknown to us—there is both the enhancement of existing ethical issues associated with AI as well as the rise of new ethical issues. There is much focus on opening up the ‘black box’ of modern machine-learning algorithms to understand the reasoning behind their decisions—especially morally salient decisions. However, some applications of AI which are no doubt beneficial to society rely upon these black boxes. Rather than requiring algorithms to be (...) transparent we should focus on constraining AI and those machines powered by AI within microenvironments—both physical and virtual—which allow these machines to realize their function whilst preventing harm to humans. In the field of robotics this is called ‘envelopment’. However, to put an ‘envelope’ around AI-powered machines we need to know some basic things about them which we are often in the dark about. The properties we need to know are the: training data, inputs, functions, outputs, and boundaries. This knowledge is a necessary first step towards the envelopment of AI-powered machines. It is only with this knowledge that we can responsibly regulate, use, and live in a world populated by these machines. (shrink)

Why hasn’t democracy been promoted by nor ICT been controlled by democratic governance? To answer this question, this research begins its investigation by comparing knowledge acquisition systems throughout history: orality, literacy, hyperlink, and hyperlead. “Hyperlead” is a newly coined concept to emphasize the passivity of people when achieving knowledge and information via algorithmic recommendation technologies. Subsequently, the four systems are compared in terms of their epistemological characteristics and political implications. It is argued that, while literacy and hyperlink contributed to (...) the furthering of democracy, hyperlead poses a fundamental challenge to it, undermining human autonomy to make decisions and aggravating vertical and lateral polarizations. In addition, the similarity between orality and hyperlead is addressed. Finally, suggestions to improve or to advert the current trend are provided. What happened during the transition period from orality to literacy and subsequently to hyperlink could be a reference for an alternative to hyperlead. Some technical adjustments and appropriate regulations requiring more transparency in algorithmic recommendation systems would help us to overcome hyperlead and preserve human autonomy. (shrink)

BackgroundThere 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).ObjectivesOur 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.MethodologyThe study involves in-depth, semistructured interviews with healthcare workers, screening programme managers, consumer health representatives, regulators, data scientists and developers.ResultsFindings 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/significanceBased 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)

In this study a combination of computer tools for coupling and virtual screening is detailed, in 108 active molecules and 3620 decoys to find stabilizers for G quadruplex. To have more precise results, combinations of coupling programs with fifteen energy scoring functions were applied. The validation and evaluation of the metrics was done with the CompScore genetic algorithm. The results showed an increase in BEDROC and EF of 50% compared to other strategies, as well as reflecting early recognition of active (...) molecules. From these results it is possible to work with the molecules that showed a good early recognition and evaluate their effect as G4 stabilizers. This ensures more efficient and accurate results in the preclinical stage for the development of anticancer drugs. Keywords: Enrichment metrics; telomere; G quadruplex ; CompScore. References [1]M. Porru, P. Zizza, M. Franceschin, C. Leonetti and A. Biroccio. «EMICORON: A multi-targeting G4 ligand with a promising preclinical profile» 2017. Biochimica et Biophysica Acta - General Subjects, 1861, 1362–1370. [Online]. Available: https://doi.org/10.1007/s00294-018-0836-6. [2]K. Tomita. «How long does telomerase extend telomeres? Regulation of telomerase release and telomere length homeostasis». Current Genetics, 64, 1177–1181. 2018. [Online]. Available: https://doi.org/10.1016/j.bbagen. 2016.11.010. [3]M. Jafri, S. Ansari, M. Alqahtani and J. Shay. «Roles of telomeres and telomerase in cancer, and advances in telomerase-targeted therapies. Genome Medicine., 2016. [Online]. Available: https://doi.org/10.3390/ijms19020482. [4]J. Huppert and S. Balasubramanian. «G-quadruplexes in promoters throughout the human genome». 35, 406–413. 2007. [Online]. Available: https://doi.org/10.1016/j.bbapap.2017.06.012. [5]S. Joy, Vijayakumar, S. Choi and H. Sunhye. «Role of computer-aided drug design in modern drug discovery». Archives of Pharmacal Research. 2015. [Online]. Available: https://doi.org/10.1007/s12272-015-0640-5. [6]S. Asamitsu, S. Obata, Z. Yu, T. Bando and H. Sugiyama. «Recent Progress of Targeted G-Quadruplex-Preferred Ligands Toward Cancer Therapy». Molecules, 24, 429. 2019. [En línea]. Available: https://doi.org/10.3390/molecules24030429. [7]R. Monsen and J. Trent. «Biochimie G-quadruplex virtual drug screening : A review». Biochimie, 152, 134–148. 2018. [Online]. Available: https://doi.org/10.1039/c9cc06748e. [8]J. Beauvarlet, P. Bensadoun, E. Darbo, G. Labrunie, E. Richard, I. Draskovic and M. Djavaheri-mergny. «Modulation of the ATM / autophagy pathway by a G-quadruplex ligand tips the balance between senescence and apoptosis in cancer cells». 1–18. 2019. [Online]. Available: https://doi.org/10.1093/nar/gkz095. [9].Z. Crees, J. Girard, Z. Rios, G. Botting, K. Harrington and C. Shearrow. « Oligonucleotides and G-quadruplex stabilizers: targeting telomeres and telomerase in cancer therapy».2014. [Online]. Available: https://doi.org/10.2174/1381612820666140630100702. [10].M. Meier, A. Moya-torres, N. Krahn, M. Mcdougall, L. Orriss, E. Mcrae and T. Patel. «Structure and hydrodynamics of a DNA Gquadruplex with a cytosine bulge»., 1–13. 2018. [Online]. Available: https://doi.org/10.1093/nar/gky307. (shrink)

The complexity of chromium chemistry makes it an ideal example of how the Principle of Expediency, first articulated by sanitary pioneer Earle Phelps, can be used in a standard setting. Expediency, defined by Phelps as “the attempt to reduce the numerical measure of probable harm, or the logical measure of existing hazard, to the lowest level that is practicable and feasible within the limitations of financial resources and engineering skill”, can take on negative connotations unless subject to ethical guidance. In (...) this paper we argue that without ethical principles as a rubric for negotiating environmental regulations, communities run the risk of slipping from the Principle of Expediency as defined by Phelps to the alternative usage of expediency meaning that which does not reflect ethical consideration or concern beyond self-serving interest. Three ethical ideals—justice, mercy and humility—are suggested as values to be considered while resolving regulatory issues related to environmental protection. The Principle of Expediency serves as a working principle, but not as a rigid algorithm, for setting regulatory limits for environmental concentrations of waste products like chromium. (shrink)

Recent algorithmic technologies have challenged law’s anthropocentric assumptions. In this article, we develop a set of theoretical tools drawn from new materialisms and the philosophy of information to unravel the complex intra-actions between law and computer code. Accordingly, we first propose a framework for understanding the enmeshing of law and code based on a diffractive reading of Barad’s agential realism and Simondon’s theory of information. We argue that once law and code are understood as material entities that intra-act through (...) in-formation, the concept of transduction allows us to trace how they push each other towards change. After developing the theoretical tools, we deploy them to make sense of how law and code have changed in response to increasing automation of decision-making and the appearance of unexplainable artificial intelligence (AI) code. Thus, we employ a case study to trace transformations of the right to explanation under the European data protection regulations. This provides the backdrop for our account of how law transduces into code (and vice versa) and a proving ground for our framework. (shrink)

L’ouverture au public des décisions de justice prévue par les articles 20 et 21 de la loi du 7 octobre 2016 pour une République numérique va favoriser le traitement des données figurant au sein des décisions par des outils automatisés. Cette exploitation ouvre des perspectives nouvelles pour les justiciables et les acteurs du droit, notamment de meilleure compréhension de la justice, de prévisibilité accrue des décisions rendues par les juridictions ou de création de valeur économique 2. Elle implique toutefois l’élaboration (...) de mécanismes de régulation adaptés, dont la construction constitue un défi à relever pour les pouvoirs publics dans un contexte d’évolution extrêmement rapide des technologies et d’internationalisation des acteurs et des flux. (shrink)

Product configuration is a key enabling technology for mass customization production. Previous studies mainly focus on the solving technologies for obtaining a feasible configuration or optimal configuration but ignore environmental factors like CO2 emissions, especially the environmental regulations from international organizations. In this article, we address product configuration optimization problems considering both carbon cap and carbon tax regulations. A two-stage approach that combines both Particle Swarm Optimization and a greedy algorithm is presented to solve the product configuration problems with carbon (...) emission concerns. A case study of a configurable ranger-drilling machine is illustrated to demonstrate the effectiveness of the presented approach. The impacts of carbon cap and carbon tax regulations on configuration results are compared. Further, the models are extended to analyze the effects of single-sourcing and multisourcing on product configuration. The analysis shows that multisourcing in combination with carbon tax regulation can facilitate a manufacturer to provide more green and low-carbon customized products for customers. Numerical experiments are conducted to validate the effectiveness of the model and the efficiency of the proposed solution method. (shrink)

Face recognition is one of the core and challenging issues in computer vision field. Compared to computer vision, human visual system can identify a target from complex backgrounds quickly and accurately. This paper proposes a new network model deriving from Where-What Networks (WWNs), which can approximately simulate the information processing pathways (i.e., dorsal pathway and ventral pathway) of human visual cortex and recognize different types of faces with different locations and sizes in complex background. To enhance the recognition performance, synapse (...) maintenance mechanism and neuron regenesis mechanism are both introduced. Synapse maintenance is used to reduce the background interference while neuron regenesis mechanism is introduced to regulate the neuron resource dynamically to improve the network usage efficiency. Experiments have been conducted on human face images of 5 types, 11 sizes, and 225 locations in complex backgrounds. Experiment results demonstrate that the proposed WWN model can basically learn three concepts (type, location and size) simultaneously. The experiment results also show the advantages of the enhanced WWN-7 model for face recognition in comparison with several existing methods. (shrink)

India has produced several drafts of data policies. In this work, they are referred to [1] JBNSCR 2018, [2] DPDPR 2018, [3] NSAI 2018, [4] RAITF 2018, [5] PDPB 2019, [6] PRAI 2021, [7] JPCR 2021, [8] IDAUP 2022, [9] IDABNUP 2022. All of them consider Artificial Intelligence (AI) a social problem solver at the societal level, let alone an incentive for economic growth. However, these policy drafts warn of the social disruptions caused by algorithms and encourage the careful use (...) of computational technologies in various social contexts. Hence, the emerging data society and its implications in India's social contexts demand immense social science attention, which needs to be improved in the policy drafts, primarily because they are creations of industry stakeholders, technocrats, bureaucrats, and experts from tech schools. In the larger social milieu of digital infrastructure emerging, the fundamental question is whether India's national philosophy envisioned in the Indian constitution is reflected in the policy papers. The paper enquires whether the national data policy upholds the core values dispersed through the philosophy of the Indian constitution, which, among other things, is not confined only to inclusion, diversity, rights, liberty, justice and equality. By focusing on constitutional values, the paper seeks to offer a broader and more critical understanding of India's approach to AI policy by bringing together analyses of a wide array of policy documents available in the public realm. (shrink)

Contemporary financial markets have recently witnessed a sea change with the ‘algorithmic revolution’, as trading automats are used to ease the execution sequences and reduce market impact. Being constantly monitored, they take an active part in the shaping of markets, and sometimes generate crises when ‘they mess up’ or when they entail situations where traders cannot go backwards. Algorithms are software codes coding practices in an IT significant ‘textual’ device, designed to replicate trading patterns. To be accepted, however, they (...) need to comply with regulatory texts, which are nothing else but codes of conduct coding accepted practices in the markets. In this article, I draw on ethnographic fieldwork in order to open these black boxes, while trying to describe their existence as devices encapsulating several points of views. I address the question of a possible misalignment between those visions, and more specifically try to draw the consequences raised by such discrepancies as regards the future of financial regulation. (shrink)