The paper offers a semantic and pragmatic analysis of statements of the form ‘x is beautiful’ as involving a double speech act: first, a report that x is beautiful relative to the speaker’s aesthetic standard, along the lines of naive contextualism; second, the speaker’s recommendation that her audience comes to share her appraisal of x as beautiful. We suggest that attributions of beauty tend to convey such a recommendation due to the role that aesthetic practices play in fostering (...) and enhancing interpersonal coordination. Aesthetic practices are driven by a disposition towards the attunement of attitudes and aesthetic recommendations contribute to forwarding such attunement. Our view is motivated by an attempt to satisfy the following set of desiderata: to account for the experiential nature of aesthetic judgments, disagreements in aesthetic debates, and the normative aspirations of aesthetic discourse, as well as to avoid appealing to error theory and realist ontological commitments. (shrink)

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.

Social media (SM) influence young adults’ communication practices. Artificial Intelligence (AI) is increasingly used for making recommendations on SM. Yet, its effects on different generations of SM users are unknown. SM can use AI recommendations to sort texts and prioritize them, shaping users’ online and offline experiences. Current literature primarily addresses technological or human-user perspectives, overlooking cognitive perspectives. This research aims to propose methods for mapping users’ interactions with AI recommendations (AiRS) and analyzes how embodied interactions mediated by a digital (...) agent can lead to changes in social and cultural practices. For this, this work proposes a comparative analysis of central practices evoked by AI recommendations-mediated communication on SM among users in Italy, Estonia, and the Netherlands in the age category 18–26 years old. The data used in the comparative analysis was collected via semi-structured interviews and elaborated based on cognitive psychology and semiotics. This research highlights the contextual significance of AI recommendations as a mediator in creating new communication practices. Findings confirm that young adults often choose practices that would enhance their digital representations according to AiRS’ dominant patterns and categories. AiRS impacts individual interpretations and practices and can further affect social and cultural levels. (shrink)

Recommender systems assist users in receiving preferred or relevant services and information. Using such technology could be instrumental in addressing the lack of relevance digital mental health apps have to the user, a leading cause of low engagement. However, the use of recommender systems for digital mental health apps, particularly those driven by personal data and artificial intelligence, presents a range of ethical considerations. This paper focuses on considerations particular to the juncture of recommender systems and digital mental health technologies. (...) While separate bodies of work have focused on these two areas, to our knowledge, the intersection presented in this paper has not yet been examined. This paper identifies and discusses a set of advantages and ethical concerns related to incorporating recommender systems into the digital mental health ecosystem. Advantages of incorporating recommender systems into DMH apps are identified as a reduction in choice overload, improvement to the digital therapeutic alliance, and increased access to personal data & self-management. Ethical challenges identified are lack of explainability, complexities pertaining to the privacy/personalization trade-off and recommendation quality, and the control of app usage history data. These novel considerations will provide a greater understanding of how DMH apps can effectively and ethically implement recommender systems. (shrink)

Advancements in novel neurotechnologies, such as brain computer interfaces and neuromodulatory devices such as deep brain stimulators, will have profound implications for society and human rights. While these technologies are improving the diagnosis and treatment of mental and neurological diseases, they can also alter individual agency and estrange those using neurotechnologies from their sense of self, challenging basic notions of what it means to be human. As an international coalition of interdisciplinary scholars and practitioners, we examine these challenges and make (...) recommendations to mitigate negative consequences that could arise from the unregulated development or application of novel neurotechnologies. We explore potential ethical challenges in four key areas: identity and agency, privacy, bias, and enhancement. To address them, we propose democratic and inclusive summits to establish globally-coordinated ethical and societal guidelines for neurotechnology development and application, new measures, including “Neurorights,” for data privacy, security, and consent to empower neurotechnology users’ control over their data, new methods of identifying and preventing bias, and the adoption of public guidelines for safe and equitable distribution of neurotechnological devices. (shrink)

The article brings to light the use of recommender systems as technologies of the self, complementing the observations in current literature regarding their employment as technologies of ‘soft’ power. User practices on the music recommendation website last.fm reveal that many users do not only utilize the website to receive guidance about music products but also to examine and transform an aspect of their self, i.e. their ‘music taste’. The capacity of assisting users in self-cultivation practices, however, is not unique (...) to last.fm but stem from certain properties shared by all recommendation systems. Furthermore, unlike other oft-studied digital/web technologies of the self which facilitate ‘self-publishing’ vis-à-vis virtual companions in social media, recommender algorithms themselves can act as ‘intimate experts’, accompanying users in their self-care practices. Thus, recommendation systems can facilitate both algorithmic control and creative self-transformation, which calls for a theorization of this new cultural medium as a space of tension. (shrink)

Recommender Systems (RS) on digital platforms increasingly influence user behavior, raising ethical concerns, privacy risks, harmful content promotion, and diminished user autonomy. This article examines RS within the framework of regulations and lawsuits in the United States and advocates for legislation that can withstand constitutional scrutiny under First Amendment protections. We propose (re)framing RS-curated content as commercial speech, which is subject to lessened free speech protections. This approach provides a practical path for future legislation that would allow for effective oversight (...) of RS, particularly in areas of substantial public interest like child safety, national security, and misinformation. (shrink)

This paper recommends how authors of statistical studies can communicate to general audiences fully, clearly, and comfortably. The studies may use statistical methods to explore issues in science, engineering, and society or they may address issues in statistics specifically. In either case, readers without explicit statistical training should have no problem understanding the issues, the methods, or the results at a non-technical level. The arguments for those results should be clear, logical, and persuasive. This paper also provides advice for editors (...) of general journals on selecting high quality statistical articles without the need for exceptional work or expense. Finally, readers are also advised to watch out for some common errors or misuses of statistics that can be detected without a technical statistical background. (shrink)

Research on children raises major ethical issues, the most important being the inability of the subjects to provide freely given informed consent. Committees in Canada and the United States charged with formulating recommendations for the protection of human subjects in research came to some fundamentally different conclusions. Two of these are discussed as they apply to children: first the distinction between therapeutic and non-therapeutic research, recognized implicitly by the National Commission and deliberately avoided by the Medical Research Council Working Group (...) ; and second, the looser relation between local committees and Council as defined by guidelines in Canada and the tighter relation between the institutional review committees and the Department of Health, Education and Welfare defined by regulations in the United States. (shrink)

Maintaining academic integrity is a growing concern for higher education, increasingly so due to the pivot to remote learning in 2020 caused by the COVID-19 pandemic. We canvassed students, faculty, and tutors at an online Canadian university about their perspectives on academic integrity and misconduct. The survey asked how the university could improve policies concerning issues of academic integrity, how faculty and tutors handled cases of misconduct, about satisfaction with how academic violations were treated, and about the role of students, (...) faculty, and tutors in encouraging academic integrity. As well, we collected suggestions from respondents for reducing cheating, addressing academic misconduct, and general ideas about academic integrity. The distinction between misconduct and integrity was not always clear in their comments. We received responses from 228 students and 73 faculty and tutors, generating hundreds of comments. In this paper we focus only on the answers to open-ended questions. Using content analysis, we categorized the replies into similar threads. After multiple iterations of analysis, we extracted three general recommendation groupings: Policy and Procedures, Compliance and Commitment, and Resources. Based on respondents’ views, we propose a balanced approach to supporting academic integrity. Although we conducted the study pre-COVID-19, the recommendations apply to current and future academic integrity practices in our context and beyond. (shrink)

Philosophers have talked to each other about moral issues concerning technology, but few of them have talked about issues of technology and the good life, and even fewer have talked about technology and the good life with the public in the form of recommendation. In effect, recommendations for various technologies are often left to technologists and gurus. Given the potential benefits of informing the public on their impacts on the good life, however, this is a curious state of affairs. (...) In the present paper, I will examine why philosophers are seemingly reluctant to offer recommendations to the public. While there are many reasons for philosophers to refrain from offering recommendations, I shall focus on a specific normative reason. More specifically, it appears that, according to a particular definition, offering recommendations can be viewed as paternalistic, and therefore is prima facie wrong to do so. I will provide an argument to show that the worry about paternalism is unfounded, because a form of paternalism engendered by technology is inevitable. Given the inevitability of paternalism, I note that philosophers should accept the duty to offer recommendations to the public. I will then briefly turn to design ethics, which has reconceptualised the role of philosophers and, in my mind, fitted well with the inevitability of paternalism. Finally, I shall argue that design ethics has to be supplemented by the practice of recommendation if it is to sustain its objective. (shrink)

Recommender Systems (RecSys) have been around since the early days of the Internet, helping users navigate the vast ocean of information and the increasingly available options that have been available for us ever since. The range of tasks for which one could use a RecSys is expanding as the technical capabilities grow, with the disruption of Machine Learning representing a tipping point in this domain, as in many others. However, the increase of the technical capabilities of AI-powered RecSys did not (...) come with a thorough consideration of their ethical implications and, despite being a well-established technical domain, the potential impacts of RecSys on their users are still under-assessed. This paper aims at filling this gap in regards to one of the main impacts of RecSys: personal autonomy. We first describe how technology can affect human values and a suitable methodology to identify these effects and mitigate potential harms: Value Sensitive Design (VSD). We use VSD to carry out a conceptual investigation of personal autonomy in the context of a generic RecSys and draw on a nuanced account of procedural autonomy to focus on two components: competence and authenticity. We provide the results of our inquiry as a value hierarchy and apply it to the design of a speculative RecSys as an example. (shrink)

Current methods to capture, analyse and present the audience participation of broadcast events are increasingly carried out using social media. Uptake of such technology tools has so far been poor amongst older adults, and it has the worrying effect of excluding the demographic from participation. Our work explores whether a common desire to interact with debates can be tapped with technology with a very low barrier to entry, to both support better engagement with broadcast debates and encourage greater use of (...) social media. This paper describes experiments where older adults interact with a BBC radio debate programme: The Moral Maze. As a result, we obtained common interaction patterns which then are used to define recommendations for software-supported interaction with debates based on theories of argumentation. Our goal is to combine research on computational models of argument and user-driven research on human-centred computing in a project with the potential for high-profile impact in addressing older adults inclusion in the digital economy. (shrink)

In recent years, social networks have made significant progress and the number of people who use them to communicate is increasing day by day. The vast amount of information available on social networks has led to the importance of using friend recommender systems to discover knowledge about future communications. It is challenging to choose the best machine learning approach to address the recommender system issue since there are several strategies with various benefits and drawbacks. In light of this, a solution (...) based on the stacking approach was put out in this study to provide a buddy recommendation system in social networks. Additionally, a decrease in system performance was caused by the large amount of information that was accessible and the inefficiency of some functions. To solve this problem, a particle swarm optimization algorithm to select the most efficient features was used in our proposed method. To learn the model in the objective function of the particle swarm algorithm, a hybrid system based on stacking is proposed. In this method, two random forests and Extreme Gradient Boosting had been used as the base classifiers. The results obtained from these base classifiers were used in the logistic regression algorithm, which has been applied sequentially. The suggested approach was able to effectively address this issue by combining the advantages of the applied strategies. The results of implementation and evaluation of the proposed system show the appropriate efficiency of this method compared with other studied techniques. (shrink)

With the rapid development of the Internet, recommendation systems have received widespread attention as an effective way to solve information overload. Social tagging technology can both reflect users’ interests and describe the characteristics of the items themselves, making group recommendation thus becoming a recommendation technology in urgent demand nowadays. In traditional tag-based recommendation systems, the general processing method is to calculate the similarity and then rank the recommended items according to the similarity. Without considering the influence (...) of continuous user behavior, in this article, we propose a personalized recommendation algorithm based on social tags by combining the ideas of Markov chain and collaborative filtering. This algorithm splits the three-dimensional relationship of into two two-dimensional relationships of and. The user’s interest degree to the tags is calculated by the Markov chain model, and then the items corresponding to them are matched by the recommended tag set. The influence between tags is used to model the satisfaction of items based on the correlation between the tags contained in the matched items, and collaborative filtering is used to complete the sparse values when calculating the interest and satisfaction between user–tags and user–items to improve the accuracy of recommendations. The experiments show that in the publicly available dataset, the personalized recommendation algorithm proposed in this article has significantly improved in accuracy and recall rate compared with the existing algorithms. (shrink)

It is not unusual for patients and their families, when confronted with difficult medical choices, to ask their physicians for advice. This paper outlines the shades of meaning of two questions frequently put to physicians: “What should I do?” and “What would you do?” It is argued that these are not questions about objective matters of fact. Hence, any response to such questions requires an understanding, appreciation, and disclosure of the personal context and values that inform the recommendation. A (...) framework for considering and articulating a response to these questions is suggested, using as a heuristic the phrasing “If I were you…/If it were me…” Journal of Medical Ethics. (shrink)

On March 11, 2020 the World Health Organization classified COVID‐19, caused by Sars‐CoV‐2, as a pandemic. Although not much was known about the new virus, the first outbreaks in China and Italy showed that potentially a large number of people worldwide could fall critically ill in a short period of time. A shortage of ventilators and intensive care resources was expected in many countries, leading to concerns about restrictions of medical care and preventable deaths. In order to be prepared for (...) this challenging situation, national triage guidance has been developed or adapted from former influenza pandemic guidelines in an increasing number of countries over the past few months. In this article, we provide a comparative analysis of triage recommendations from selected national and international professional societies, including Australia/New Zealand, Belgium, Canada, Germany, Great Britain, Italy, Pakistan, South Africa, Switzerland, the United States, and the International Society of Critical Care Medicine. We describe areas of consensus, including the importance of prognosis, patient will, transparency of the decision‐making process, and psychosocial support for staff, as well as the role of justice and benefit maximization as core principles. We then probe areas of disagreement, such as the role of survival versus outcome, long‐term versus short‐term prognosis, the use of age and comorbidities as triage criteria, priority groups and potential tiebreakers such as ‘lottery’ or ‘first come, first served’. Having explored a number of tensions in current guidance, we conclude with a suggestion for framework conditions that are clear, consistent and implementable. This analysis is intended to advance the ongoing debate regarding the fair allocation of limited resources and may be relevant for future policy‐making. (shrink)

In the July 2001 issue of the JournalofBiosocialScience Tina Moffat presents an interesting study from Nepal (Moffat, 2001). She refers to several studies, among them our study from Nepal’s neighbouring country Bhutan (Bøhler & Ingstad, 1996), to show that weaning practices are determined by different aspects of the environment, and thus cannot be made universal. However, she goes on to conclude that the recommendation of exclusive breast-feeding for 6 months may not be appropriate for the population she studied. This (...) part of her conclusion is, in my view, far from sufficiently supported by her data. (shrink)

With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation (...) system, the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered. (shrink)

Nanomedicine is yielding new and improved treatments and diagnostics for a range of diseases and disorders. Nanomedicine applications incorporate materials and components with nanoscale dimensions where novel physiochemical properties emerge as a result of size-dependent phenomena and high surface-to-mass ratio. Nanotherapeutics and in vivo nanodiagnostics are a subset of nanomedicine products that enter the human body. These include drugs, biological products, implantable medical devices, and combination products that are designed to function in the body in ways unachievable at larger scales. (...) Nanotherapeutics andin vivonanodiagnostics incorporate materials that are engineered at the nanoscale to express novel properties that are medicinally useful. These nanomedicine applications can also contain nanomaterials that are biologically active, producing interactions that depend on biological triggers. Examples include nanoscale formulations of insoluble drugs to improve bioavailability and pharmacokinetics, drugs encapsulated in hollow nanoparticles with the ability to target and cross cellular and tissue membranes and to release their payload at a specific time or location, imaging agents that demonstrate novel optical properties to aid in locating micrometastases, and antimicrobial and drug-eluting components or coatings of implantable medical devices such as stents. (shrink)

Gamification is increasingly being proposed as a strategy to increase engagement for mental health and wellbeing technologies. However, its implementation has been criticized as atheoretical, particularly in relation to behavior change theory and game studies theories. Definitions of the term “gamification” vary, sometimes widely, between and within academic fields and the effectiveness of gamification is yet to be empirically established. Despite this, enthusiasm for developing gamified mental health technologies, such as interventions, continues to grow. There is a need to examine (...) how best to implement gamification in mental health and wellbeing technologies in a way that takes quick production cycles into account while still emphasizing empirical investigation and building a rigorous evidence base. With reference to game studies and the medical literature, this article interrogates gamification for mental health and wellbeing by examining core properties of the game form. It then explores how gamification can best be conceptualized and implemented for mental health and wellbeing goals from conceptualization through to iterative co-development and evaluation that accommodates software development schedules. Finally, it summarizes its conceptual analysis into recommendations for researchers and designers looking to do so. These recommendations are: assess suitability, implement to support, assess acceptability, evaluate impact, and document comprehensively. These recommendations aim to encourage clear language, unified terminology, the application and evaluation of theory, comprehensive and constant documentation, and transparent evaluation of outcomes. (shrink)

Although I am neither a Nazi nor an anti-Semite (quite the contrary, in fact), I like the music of Richard Wagner. Why do I like his music? Mainly because I find it intoxicating. Intoxicate: To cause stupefaction, stimulation, or excitement by or as if by use of a chemical substance.) I admit that this is not a very deep reason. But I’m not very deep. (My years as an analytic philosopher would have drained any depths I may once have had.) (...) Although Mark Twain once described Wagner’s music as ‘better than it sounds’, it actually sounds better than it is, since intoxicating substances deceive our senses. (Think of the love potion in Tristan.) There are, I grant, other more serious reasons to like and to value Wagner’s music. Rather than rehearse any of them, I’m going to turn to an annotated list of some of my favorite recordings. (shrink)

As a result of simultaneous developments, including the proliferation of opportunities for online feedback, the application of discourse ethics to journalism, and a greater emphasis on journalistic accountability, the time is ripe for revisiting opportunities that online mechanisms provide for holding journalists accountable to audiences. This paper proposes recommendations to guide hosting online comments in light of the Habermasian framework of discourse ethics developed by Glasser and Ettema (2008). It also explores the limits of such approaches in nations with different (...) press models, such as the development model as practiced in China. (shrink)

Algorithmic decision making is used in an increasing number of fields. Letting automated processes take decisions raises the question of their accountability. In the field of computational journalism, the algorithmic accountability framework proposed by Diakopoulos formalizes this challenge by considering algorithms as objects of human creation, with the goal of revealing the intent embedded into their implementation. A consequence of this definition is that ensuring accountability essentially boils down to a transparency question: given the appropriate reverse-engineering tools, it should be (...) feasible to extract design criteria and to identify intentional biases. General limitations of this transparency ideal have been discussed by Ananny and Crawford :973–989, 2018). We further focus on its technical limitations. We show that even if reverse-engineering concludes that the criteria embedded into an algorithm correspond to its publicized intent, it may be that adversarial behaviors make the algorithm deviate from its expected operation. We illustrate this issue with an automated news recommendation system, and show how the classification algorithms used in such systems can be fooled with hard-to-notice modifications of the articles to classify. We therefore suggest that robustness against adversarial behaviors should be taken into account in the definition of algorithmic accountability, to better capture the risks inherent to algorithmic decision making. We finally discuss the various challenges that this new technical limitation raises for journalism practice. (shrink)

Recommending the identity of bidders in public procurement auctions has a significant impact in many areas of public procurement, but it has not yet been studied in depth. A bidders recommender would be a very beneficial tool because a supplier can search appropriate tenders and, vice versa, a public procurement agency can discover automatically unknown companies which are suitable for its tender. This paper develops a pioneering algorithm to recommend potential bidders using a machine learning method, particularly a random forest (...) classifier. The bidders recommender is described theoretically, so it can be implemented or adapted to any particular situation. It has been successfully validated with a case study: an actual Spanish tender dataset which has 102,087 tenders from 2014 to 2020 and a company dataset which has 1,353,213 Spanish companies. Quantitative, graphical, and statistical descriptions of both datasets are presented. The results of the case study were satisfactory: the winning bidding company is within the recommended companies group, from 24% to 38% of the tenders, according to different test conditions and scenarios. (shrink)

In his recent article ‘Nudging, Informed Consent and Bullshit’, William Simkulet1 convincingly argues that certain types of nudging satisfy Frankfurt’s criteria of bullshit. As a prelude to this argument, Simkulet considers whether recommendations and framing are types of nudging and whether they satisfy the requirement of adequate disclosure essential for a valid informed consent. He defines nudging as the systematic attempt at altering behaviour by non-rational means, and describes adequate disclosure as providing the patient with true information that enables an (...) understanding of treatment options and their risks and benefits. Simkulet argues that recommendations and framing are types of rational persuasion in that they potentially enhance patients’ understanding of treatment options and their risks and benefits. Therefore, not only do they not qualify as nudging, but they may be required in order to secure adequate disclosure. In this brief comment, I focus on Simkulet’s considerations of framing and show that framing may be nudging and that it may violate the requirements of informed consent. The framing of medical information may influence patients’ preferences for treatment. It has been shown that framing information about a risky medical intervention in chance of survival rather than risk of death increases patients’ preferences for the intervention.2 3 In his exploration of framing, Simkulet contends that the fact that people respond differently to …. (shrink)

Periodic tables (PTs) are the ‘ultimate paper tools’ of general and inorganic chemistry. There are three fields of open questions concerning the relation between PTs and physics: (i) the relation between the chemical facts and the concept of a periodic system (PS) of chemical elements (CEs) as represented by PTs; (ii) the internal structure of the PS; (iii)␣The relation between the PS and atomistic quantum chemistry. The main open questions refer to (i). The fuzziness of the concepts of chemical properties (...) and of chemical similarities of the CE and their compounds guarantees the autonomy of chemistry. We distinguish between CEs, Elemental Stuffs and Elemental Atoms. We comment on the basic properties of the basic elements. Concerning (ii), two sharp physical numbers (nuclear charge and number of valence electrons) and two coarse fuzzy ranges (ranges of energies and of spatial extensions of the atomic orbitals, AOs) characterize the atoms of the CEs and determine the two-dimensional structure of the PS. Concerning (iii), some relevant ‘facts’ about and from quantum chemistry are reviewed and compared with common ‘textbook facts’. What counts in chemistry is the whole set of nondiffuse orbitals in low-energy average configurations of chemically bonded atoms. Decisive for the periodicity are the energy gaps between the core and valence shells. Diffuse Rydberg orbitals and minute spin–orbit splittings are important in spectroscopy and for philosophers, but less so in chemical science and for the PS. (shrink)

This paper proposes a personalized music recommendation method based on multidimensional time-series analysis, which can improve the effect of music recommendation by using user’s midterm behavior reasonably. This method uses the theme model to express each song as the probability of belonging to several hidden themes, then models the user’s behavior as multidimensional time series, and analyzes the series so as to better predict the use of music users’ behavior preference and give reasonable recommendations. Then, a music (...) class='Hi'>recommendation method is proposed, which integrates the long-term, medium-term, and real-time behaviors of users and considers the dynamic adjustment of the influence weight of the three behaviors so as to further improve the effect of music recommendation by adopting the advanced long short time memory technology. Through the implementation of the prototype system, the feasibility of the proposed method is preliminarily verified. (shrink)

For graduate students and junior researchers alike, organising a science café may seem a simple and relatively harmless academic activity. However, organising such an event, especially when it aims to share complex and sophisticated thinking with the general public, can raise challenges from conception to completion. In this text, we share our reflections on the challenges and other lessons learned by the members of the organising team of a bioethics café funded by the Canadian Institutes of Health Research, in the (...) hope that our experience can be of use to others in organising similar events. (shrink)

This paper explores and rehabilitates the value of decisional privacy as a conceptual tool, complementary to informational privacy, for critiquing personalized choice architectures employed by self-tracking technologies. Self-tracking technologies are promoted and used as a means to self-improvement. Based on large aggregates of personal data and the data of other users, self-tracking technologies offer personalized feedback that nudges the user into behavioral change. The real-time personalization of choice architectures requires continuous surveillance and is a very powerful technology, recently coined as (...) “hypernudging.” While users celebrate the increased personalization of their coaching devices, “hypernudging” technologies raise concerns about manipulation. This paper addresses that intuition by claiming that decisional privacy is at stake. It thus counters the trend to solely focus on informational privacy when evaluating information and communication technologies. It proposes that decisional privacy and informational privacy are often part of a mutually reinforcing dynamic. Hypernudging is used as a key example to illustrate that the two dimensions should not be treated separately. Hypernudging self-tracking technologies compromise autonomy because they violate informational and decisional privacy. In order to effectively judge whether technologies that use hypernudges empower users, we need both privacy dimensions as conceptual tools. (shrink)

These range from merely good reads to really outstanding books; but rather than trying to rate each one, or (what would be more to the point) explain my ratings, I've merely listed them without any particular indication of rank. Horror novels are included here for want of anyplace better to put them. Titles are added as they occur to me.

Despite their ethical challenges, recommender systems (RS) are widely endorsed as a necessary solution to the problem of information overload. After clarifying how the harmful effects of information overload can be characterized in distinct ways, I explore the often overlooked potential benefits of abundant online spaces. I argue that these spaces afford valuable opportunities to experience spontaneous freedom. I then put forth a more comprehensive evaluation of the role RS should assume in algorithmically structuring the online space. This evaluation aims (...) to reconcile the dual objectives of mitigating the harms of information overload and preserving opportunities to experience spontaneous freedom. (shrink)

Sequential recommendation algorithm can predict the next action of a user by modeling the user’s interaction sequence with an item. However, most sequential recommendation models only consider the absolute positions of items in the sequence, ignoring the time interval information between items, and cannot effectively mine user preference changes. In addition, existing models perform poorly on sparse data sets, which make a poor prediction effect for short sequences. To address the above problems, an improved sequential recommendation algorithm (...) based on short-sequence enhancement and temporal self-attention mechanism is proposed in this paper. In the proposed algorithm, a backward prediction model is trained first, to predict the prior items in the user sequence. Then, the reverse prediction model is used to generate a batch of pseudo-historical items before the initial items of the short sequence, to achieve the goal of enhancing the short sequence. Finally, the absolute position information and time interval information of the user sequence are modeled, and a time-aware self-attention model is adopted to predict the user’s next action and generate a recommendation list. Various experiments are conducted on two public data sets. The experimental results show that the method proposed in this paper has excellent performance on both dense and sparse data sets, and its effect is better than that of the state of the art. (shrink)

Collaborative filtering technology is currently the most successful and widely used technology in the recommendation system. It has achieved rapid development in theoretical research and practice. It selects information and similarity relationships based on the user’s history and collects others that are the same as the user’s hobbies. User’s evaluation information is to generate recommendations. The main research is the inadequate combination of context information and the mining of new points of interest in the context-aware recommendation process. On (...) the basis of traditional recommendation technology, in view of the characteristics of the context information in music recommendation, a personalized and personalized music based on popularity prediction is proposed. Recommended algorithm is MRAPP. The algorithm first analyzes the user’s contextual information under music recommendation and classifies and models the contextual information. The traditional content-based recommendation technology CB calculates the recommendation results and then, for the problem that content-based recommendation technology cannot recommend new points of interest for users, introduces the concept of popularity. First, we use the memory and forget function to reduce the score and then consider user attributes and product attributes to calculate similarity; secondly, we use logistic regression to train feature weights; finally, appropriate weights are used to combine user-based and item-based collaborative filtering recommendation results. Based on the above improvements, the improved collaborative filtering recommendation algorithm in this paper has greatly improved the prediction accuracy. Through theoretical proof and simulation experiments, the effectiveness of the MRAPP algorithm is demonstrated. (shrink)

People are increasingly subject to algorithmic decisions, and it is generally agreed that end-users should be provided an explanation or rationale for these decisions. There are different purposes that explanations can have, such as increasing user trust in the system or allowing users to contest the decision. One specific purpose that is gaining more traction is algorithmic recourse. We first pro- pose that recourse should be viewed as a recommendation problem, not an explanation problem. Then, we argue that the (...) capability approach provides plausible and fruitful ethical standards for re- course. We illustrate by considering the case of diversity constraints on algorithmic recourse. Finally, we discuss the significance and implications of adopting the capability approach for algorithmic recourse research. (shrink)

Heterogeneous information networks can naturally simulate complex objects, and they can enrich recommendation systems according to the connections between different types of objects. At present, a large number of recommendation algorithms based on heterogeneous information networks have been proposed. However, the existing algorithms cannot extract and combine the structural features in heterogeneous information networks. Therefore, this paper proposes an efficient recommendation algorithm based on heterogeneous information network, which uses the characteristics of graph convolution neural network to automatically (...) learn node information to extract heterogeneous information and avoid errors caused by the manual search for metapaths. Furthermore, by fully considering the scoring relationship between nodes, a calculation strategy combining heterogeneous information and a scoring information fusion strategy is proposed to solve the scoring between nodes, which makes the prediction scoring more accurate. Finally, by updating the nodes, the training scale is reduced, and the calculation efficiency is improved. The study conducted a large number of experiments on three real data sets with millions of edges. The results of the experiments show that compared with PMF, SemRec, and other algorithms, the proposed algorithm improves the recommendation accuracy MAE by approximately 3% and the RMSE by approximately 8% and reduces the time consumption significantly. (shrink)

More and more tourists are sharing their travel feelings and posting their real experiences on the Internet, generating tourism big data. Online travel reviews can fully reflect tourists’ emotions, and mining and analyzing them can provide insight into the value of them. In order to analyze the potential value of online travel reviews by using big data technology and machine learning technology, this paper proposes an improved support vector machine algorithm based on travel consumer sentiment analysis and builds an Hadoop (...) Distributed File System system based on Map-Reduce model. Firstly, Internet travel reviews are pre-processed for sentiment analysis of the review text. Secondly, an improved SVM algorithm is proposed based on the main features of linear classification and kernel functions, so as to improve the accuracy of sentiment word classification. Then, HDFS data nodes are deployed on the basis of Hadoop platform with the actual tourism application context. And based on the Map-Reduce programming model, the map function and reduce function are designed and implemented, which greatly improves the possibility of parallel processing and reduces the time consumption at the same time. Finally, an improved SVM algorithm is implemented under the built Hadoop platform. The test results show that online travel reviews can be an important data source for travel big data recommendation, and the proposed method can quickly and accurately achieve travel sentiment classification. (shrink)

The prelims comprise: Half Title Page Blackwell Philosopher Dictionaries Title Page Copyright Page For everyone at 12 Willow Lane Dedication Table of Contents Preface and acknowledgments.

In this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education platform using a cross-platform compatible HTML5 and high-performance framework hybrid programming approach. The server-side development adopts a mature B/S architecture and the popular development model, while the mobile terminal uses HTML5 and framework to implement the function of recommending personalized courses for users using collaborative filtering and recommendation algorithms. (...) By improving the traditional recommendation algorithm based on collaborative filtering, the course recommendation results are more in line with users' interests, which greatly improves the accuracy and efficiency of the recommendation. On this basis, online teaching on this platform is divided into two modes: one mode is the original teacher uploads recorded teaching videos and students can learn by purchasing online or offline download; the other mode is interactive online live teaching. Each course is a separate online classroom; the teacher will publish online class information in advance, and students can purchase to get classroom number and password information online. (shrink)

Nigeria is developing country where the practice of euthanasia is not legalized. But a look at the socio-economic conditions of Nigeria calls for the need to legalize the practice in this country. This paper examines the features of this country such as poverty, endemic diseases and a low level of investment in healthcare systems . It argues for the need to legalize euthanasia by justifying it as a policy and practice and identifying factors which are to be taken into account. (...) They include poor standard of living which reduces the life span of many and limited health care resources which prevents access to health care. The paper justifies legalizing euthanasia in Nigeria by responding to some arguments against euthanasia raised by critics emphasizing at the same time ethical issues such as autonomy, dignity and quality of life for euthanasia debate. It concludes by stressing that in Nigeria, a competent person who is terminally ill and undergoing severe pain should be able to determine how and when to end his life; the possibility of this will only depend on the legalization of euthanasia in this country. (shrink)