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.

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)

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)

The Movie Recommendation System using Machine Learning Techniques is a data-driven approach designed to provide personalized movie suggestions based on user preferences and historical data. This system leverages advanced machine learning algorithms, including collaborative filtering, content-based filtering, and hybrid methods, to predict the most relevant movies for individual users. The system's primary goal is to enhance user experience by recommending movies that align with their tastes, thereby promoting user engagement and satisfaction. The recommendation process starts by collecting user data, such (...) as viewing history, ratings, and genre preferences, which are then processed to generate personalized suggestions. Collaborative filtering analyzes the behavior of similar users to recommend movies based on common interests, while content-based filtering focuses on movie features such as genre, director, actors, and plot summary. By combining both methods, the hybrid approach further refines the recommendation, ensuring diverse and accurate results. The model's effectiveness is evaluated using standard metrics like precision, recall, and F1-score, demonstrating its ability to accurately predict user preferences. The system can be integrated into various platforms, offering real-time recommendations and improving user satisfaction. This project can be expanded by incorporating more sophisticated algorithms, such as deep learning, to further enhance recommendation accuracy and scalability. Overall, this movie recommendation system aims to optimize content discovery and cater to diverse audience needs. (shrink)

Agriculture plays a crucial role in the economic stability of many nations, and optimizing crop selection is essential for enhancing agricultural productivity and sustainability. The "Crop Recommender System Using Machine Learning Approach" aims to leverage machine learning techniques to provide precise crop recommendations based on various environmental and soil conditions. By incorporating factors such as soil composition, pH level, temperature, humidity, rainfall, and geographic location, this system suggests the most suitable crops for a given area. The system utilizes machine (...) learning models, particularly Random Forest and Decision Trees, to analyze historical agricultural data, predict optimal crops, and improve the decision-making process for farmers. By training the model on large datasets, it ensures accurate predictions that align with real-world agricultural practices. The application of this system can lead to higher crop yields, sustainable farming practices, and reduced risks associated with poor crop choices. Through rigorous evaluation using standard classification metrics, the model's performance demonstrates its potential to revolutionize farming practices by aiding farmers in making informed decisions. The system has the potential to be an invaluable tool for agricultural consultants, farmers, and policymakers, ensuring long-term sustainability and improved productivity. (shrink)

As the multiple issues of the digital public sphere threaten our democracies and the cohesion of our societies, most attempts for a betterment of the digital networks and platforms revolve around a risk-response approach. This paper takes the opposite approach and develops a positive definition of the ideal ethical public sphere, combining normative features with original taxonomies. In view of defining common standards for a healthy digital public sphere, this paper offers an interdisciplinary literature review, and original recommendations, before (...) discussing potential leverages for implementing these changes. The suggested ethical normative features derive from a positive approach to the digital public sphere, as ideal common standards. Sustained by the underlying assumption that the composite landscape of the media ecosystem and its different layers (networks, platforms, users) cannot be steered by government regulations alone, the normative (deontological) approach serves to understand and justify the need for a normative approach, to help envision new pathways for an ethical transformation. (shrink)

In critical medical emergencies, timely and accurate drug recommendation is essential for saving lives and reducing complications. This project proposes a Drug Recommendation System utilizing Machine Learning (ML) techniques to assist healthcare professionals in making quick and accurate drug selections based on patient symptoms, medical history, and emergency condition. The system integrates data from diverse medical databases, including symptoms, diseases, patient demographics, and prior medical records, to recommend the most appropriate drugs or treatments in real-time. The ML model is trained (...) on historical medical data, utilizing algorithms such as Decision Trees, Random Forests, and Neural Networks to predict optimal drug choices for different emergency situations. The system not only considers the immediate medical needs but also factors in contraindications, potential drug interactions, and patient-specific conditions, ensuring safer drug administration. This approach aims to reduce human errors in emergency drug prescriptions, enhance the speed of medical response, and improve the overall quality of care during emergencies. By leveraging data-driven insights, the system supports healthcare professionals in making well-informed decisions, even in high-pressure situations. Ultimately, the Drug Recommendation System serves as a valuable tool in healthcare, enhancing emergency medical care and optimizing treatment outcomes. (shrink)

Personalized medicine recommendation systems are increasing in popularity to predict diseases and provide customized health advice on diet, workout plans and medication. The medical suggestion system can be valuable when pandemics, floods, or cyclones hit. In the age of Machine Learning (ML), recommender systems give more accurate, precise, and reliable clinical predictions while using less resources. Through the use of machine learning algorithms like Decision Tree, Random Forest, K-Means Clustering, and Hierarchical Clustering, these systems analyze patient inputs such as lifestyle (...) data, symptoms, and health metrics for accurate predictions of diseases and holistic recommendations on health. This inclusive process ensures each person receives tailored support to enhance the entire management of their health. The system's ability to suggest accurate diets, proper workouts, and appropriate drugs depending on the condition of the user significantly enhances its contribution toward more healthy lifestyles. The variety of algorithms increases accuracy and reliability as well because each model contributes uniquely in analyzing various aspects of patient data. This study presents a framework that demonstrates the system's efficacy in providing personalized disease predictions and health recommendations, which can benefit the development of preventive care and improve treatment outcomes. (shrink)

Recommender systems are artificial intelligence technologies, deployed by online platforms, that model our individual preferences and direct our attention to content we’re likely to engage with. As the digital world has become increasingly saturated with information, we’ve become ever more reliant on these tools to efficiently allocate our attention. And our reliance on algorithmic recommendation may, in turn, reshape us as moral agents. While recommender systems could in principle enhance our moral agency by enabling us to cut through the information (...) saturation of the internet and focus on things that matter, as they’re currently designed and implemented they’re apt to interfere with our ability to attend appropriately to morally relevant factors. In order to analyze the distinctive moral problems algorithmic recommendation poses, we develop a framework for the ethics of attention and an account of judicious attention allocation as a moral skill. We then discuss empirical evidence suggesting that attentional moral skill can be thwarted and undermined in various ways by algorithmic recommendation and related affordances of online platforms, as well as economic and technical considerations that support this concern. Finally, we consider how emerging technologies might overcome the problems we identify. (shrink)

Digital media has become an integral part of people’s lives, and its ubiquity and pervasiveness in our everyday lives raise new ethical, social, cultural, political, economic and legal issues. Many of these issues have primarily been dealt with in terms of what is ‘right’ or ‘just’ with digital media and digitally-mediated practices, and questions about the relations between digital media and the good life are often left in the background. In short, what is often missing is an explicit discussion of (...) the relations between digital media and the good life. Under the label of ‘Net recommendation’, the present study aims to offer a balanced and constructive normative analysis of digital media, focusing on the relations between digital media and the good life. The project of Net recommendation aims to (re)assert the importance of actual discourses in our normative analysis of the relations between digital media and the good life. I pursue this project with a Walzerian approach to digital media and the good life that takes seriously (and, ideally, also interacts with) actual discourses. This approach allows us to have a better understanding of our normative judgements on the impacts of digital media has (or will have) on the good life and, at the same time, allows us to answer the question of ‘how should we live with digital media?’ more adequately. Moreover, the Walzerian approach is useful in both an intra-cultural and an inter¬cultural context. Using China’s Internet as a case study, I show that the relations between digital media and the good life in each culture should be examined in its own right. Together, I hope, this study provides an adequate illustration and defence of the project of Net recommendation that does not start with the assumption of digital media being a source of moral problem and strives to recommending specific ways to reform and/or transform digital media and digitally-mediated practices that allow us to have better relations with digital media and enable us to live better lives with them. (shrink)

Recommender systems have become essential in modern entertainment platforms, aiding users in discovering movies and TV shows tailored to their preferences. Traditional movie recommendation systems often rely on collaborative filtering or content-based methods. However, supervised learning offers an alternative approach by learning from labeled data, leveraging classification or regression models to predict user preferences. In this paper, we explore the implementation of a movie recommender system using supervised learning techniques, such as decision trees, random forests, and support vector machines. We (...) discuss the dataset used, feature extraction techniques, model training, and evaluation metrics. The proposed system predicts user ratings and recommends movies based on historical data, user features, and movie characteristics. We demonstrate how supervised learning models can outperform traditional methods by integrating both user and item data in a structured manner. (shrink)

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by (...) other stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (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)

In today's agricultural landscape, farmers face numerous challenges in selecting the right crops to plant, primarily due to varying soil conditions and unpredictable weather patterns. This often leads to suboptimal yields and inefficient use of resources. To tackle these issues, we propose a Crop Recommendation System powered by machine learning, specifically utilizing the Random Forest algorithm. This innovative system will analyze essential factors such as soil nutrients—nitrogen, phosphorus, and potassium—as well as climatic conditions like temperature, humidity, and rainfall, to provide (...) tailored crop recommendations. Our goal is to empower farmers by simplifying the decision-making process, ensuring they have access to reliable guidance for improving crop selection. By making informed decisions, farmers can boost their yields, enhance sustainability, and ultimately contribute to a more efficient agricultural sector. This project not only aims to improve individual crop management practices but also supports researchers and policymakers in developing better agricultural strategies. Through this initiative, we hope to pave the way for a future where technology and agriculture work hand in hand for a more sustainable and productive world. (shrink)

Longtermism is the view that the most urgent global priorities, and those to which we should devote the largest portion of our resources, are those that focus on (i) ensuring a long future for humanity, and perhaps sentient or intelligent life more generally, and (ii) improving the quality of the lives that inhabit that long future. While it is by no means the only one, the argument most commonly given for this conclusion is that these interventions have greater expected goodness (...) per unit of resource devoted to them than each of the other available interventions, including those that focus on the health and well-being of the current population. In this paper, I argue that, even if we grant the consequentialist ethics upon which this argument depends, and even if we grant one of the axiologies that are typically paired with that ethics to give the argument, we are not morally required to choose an option that maximises expected utility; indeed, we might not even be permitted to do so. Instead, I will argue, if the argument's consequentialism is correct, we should choose using a decision theory that is sensitive to risk, and allows us to give greater weight to worse-case outcomes than expected utility theory does. And, I will show, such decision theories do not always recommend longtermist interventions. Indeed, sometimes, they recommend exactly the opposite: sometimes, they recommend hastening human extinction. Many, though not all, will take this as a reductio of the consequentialism or the axiology of the argument. I remain agnostic on the conclusion we should draw. (shrink)

The current study is conducted to examine the following research questions: 1) What information sources on social media are associated with the general intention to try space tourism? 2) Does the automatically recommended information moderate the associations between multiple sources of information and the intention to try space tourism?

This paper examines about suggestions of the motion pictures. A film suggestion is significant in our public activity because of its solidarity in giving upgraded diversion. Such a framework can propose a bunch of motion pictures to clients dependent on their advantage, or the popularities of the films. A proposal framework is utilized to recommend things to buy or to see. They direct clients towards those things which can address their issues through chopping down huge data set of Information. A (...) recommender framework, or a suggestion framework (now and then supplanting 'framework' with an equivalent like stage or motor), is a subclass of data sifting framework that tries to anticipate the "rating" or "inclination" a client would provide for a thing. They are principally utilized in business applications, likewise assist clients with finding the motion pictures of their decisions dependent on the film insight of different clients in proficient and compelling way without burning through much time in pointless perusing. (shrink)

Control interventions (often called “sham,” “placebo,” or “attention controls”) are essential for studying the efficacy or mechanism of physical, psychological, and self-management interventions in clinical trials. This article presents core recommendations for designing, conducting, and reporting control interventions to establish a quality standard in nonpharmacological intervention research. A framework of additional considerations supports researchers’ decision making in this context. We also provide a reporting checklist for control interventions to enhance research transparency, usefulness, and rigour.

Wearable devices are increasingly present in the health context, as tools for biomedical research and clinical care. In this context, wearables are considered key tools for a more digital, personalised, preventive medicine. At the same time, wearables have also been associated with issues and risks, such as those connected to privacy and data sharing. Yet, discussions in the literature have mostly focused on either technical or ethical considerations, framing these as largely separate areas of discussion, and the contribution of wearables (...) to the collection, development, application of biomedical knowledge has only partially been discussed. To fill in these gaps, in this article we provide an epistemic (knowledgerelated) overview of the main functions of wearable technology for health: monitoring, screening, detection, and prediction. On this basis, we identify 4 areas of concern in the application of wearables for these functions: data quality, balanced estimations, health equity, and fairness. To move the field forward in an effective and beneficial direction, we present recommendations for the 4 areas: local standards of quality, interoperability, access, and representativity. (shrink)

It is widely agreed by philosophers that the so-called “Frege-Russell definition of natural number” is actually an assertion concerning the nature of the numbers and that it cannot be regarded as a definition in the ordinary mathematical sense. On the basis of the reasoning in this paper it is clear that the Frege-Russell definition contradicts the following three principles (taken together): (1) each number is the same entity in each possible world, (2) each number exists in each possible world, (3) (...) some entities existing in the actual world do not exist in every possible world. Since these principles seem to be true, the paper is a refutation of the Frege-Russell definition. The paper does more. It shows that the contradictory of the Frege-Russell definition follows even when principles 2 and 3 are replaced by one considerably weaker principle. The ideas contained in the paper are related to two earlier objections to the definition. The first, sometimes attributed to the mathematician, C. S. Keyser, is that existence of the numbers as defined implies the existence of infinitely many particulars in each possible world. The second is, in effect, an idea which is said to have led Whitehead to reject the definition of number to which he had subscribed in Principia Mathematica. Whitehead is supposed to have said that he could not believe that the number two changes every “time twins are born”. The mathematician H. Jeffreys expressed similar ideas [Philos. of Sci. 5 (1938), 434–451]. One of the merits of the author’s work is that it refutes the Frege-Russell definition without the need to take sides on controversial points presupposed by the Keyser and Whitehead objections. The objections made by the author are therefore not to be identified with the Keyser and Whitehead objections. Even if the author’s work is to be regarded as a refinement and integration of previous ideas, it is nevertheless a contribution—not only because the basic points are well worth repeating but also because the refinements are logically significant improvements and because the author has stated them clearly and concisely in the idiom of contemporary philosophy. (shrink)

The public discussion on artificial intelligence for public health often revolves around future applications like drug discovery or personalized medicine. But already deployed artificial intelligence for content recommendation, especially on social networks, arguably plays a far greater role. After all, such algorithms are used on a daily basis by billions of users worldwide. In this paper, we argue that, left unchecked, this enormous influence of recommendation algorithms poses serious risks for public health, e.g., in terms of misinformation and mental health. (...) But more importantly, we argue that this enormous influence also yields a fabulous opportunity to provide quality information and to encourage healthier habits at scale. We also discuss the philosophical, technical and socio-economical challenges to seize this immense opportunity, and sketch the outlines of potential solutions. In particular, we argue that it would be extremely helpful if public and private institutions could publicly take a stand, as this may then generate the necessary social, economical and political pressure to massively invest in the research, development and deployment of the potential solutions. (shrink)

Corruption Prevention Measures Recommended by Kautilya -/- Author / Authors : Dr. Priti Pohekar Page no. 107- 113 Discipline : Political Science/Polity/ Democratic studies Script/language : Roman/English Category : Research paper Keywords:Corruption, remedies of corruption, Kautilya Arthashastra.

This article analyses the ethical aspects of multistakeholder recommendation systems (RSs). Following the most common approach in the literature, we assume a consequentialist framework to introduce the main concepts of multistakeholder recommendation. We then consider three research questions: who are the stakeholders in a RS? How are their interests taken into account when formulating a recommendation? And, what is the scientific paradigm underlying RSs? Our main finding is that multistakeholder RSs (MRSs) are designed and theorised, methodologically, according to neoclassical welfare (...) economics. We consider and reply to some methodological objections to MRSs on this basis, concluding that the multistakeholder approach offers the resources to understand the normative social dimension of RSs. (shrink)

The goal of this article is to present a first list of ethical concerns that may arise from research and personal use of virtual reality (VR) and related technology, and to offer concrete recommendations for minimizing those risks. Many of the recommendations call for focused research initiatives. In the first part of the article, we discuss the relevant evidence from psychology that motivates our concerns. In Section “Plasticity in the Human Mind,” we cover some of the main results (...) suggesting that one’s environment can influence one’s psychological states, as well as recent work on inducing illusions of embodiment. Then, in Section “Illusions of Embodiment and Their Lasting Effect,” we go on to discuss recent evidence indicating that immersion in VR can have psychological effects that last after leaving the virtual environment. In the second part of the article, we turn to the risks and recommendations. We begin, in Section “The Research Ethics of VR,” with the research ethics of VR, covering six main topics: the limits of experimental environments, informed consent, clinical risks, dual-use, online research, and a general point about the limitations of a code of conduct for research. Then, in Section “Risks for Individuals and Society,” we turn to the risks of VR for the general public, covering four main topics: long-term immersion, neglect of the social and physical environment, risky content, and privacy. We offer concrete recommendations for each of these 10 topics, summarized in Table 1. (shrink)

In contemporary paternalism literature, persuasion is commonly not considered paternalistic. Moreover, paternalism is typically understood to be problematic either because it is seen as coercive, or because of the insult of the paternalist considering herself superior. In this paper, I argue that doctors who persuade patients act paternalistically. Specifically, I argue that trying to persuade a patient (here understood as aiming for the patient to consent to a certain treatment, although he prefers not to) should be differentiated from trying to (...) convince him (here understood as aiming for the patient to want the treatment) and recommending (the doctor merely providing her professional opinion). These three forms of influence are illustrated by summaries of video-recorded hospital encounters. While convincing and recommending are generally not paternalistic, I argue that persuasion is what I call communicative paternalism and that it is problematic for two reasons. First, the patient’s preferences are dismissed as unimportant. Second, the patient might wind up undergoing treatment against his preferences. This does not mean that persuasion always should be avoided, but it should not be undertaken lightly, and doctors should be aware of the fine line between non-paternalism and paternalism. The fact that my analysis of paternalism differs from traditional accounts does not imply that I deem these to be wrong, but rather that paternalism should be considered as a more multi-faceted concept than previous accounts allow for. (shrink)

One of the key responsibilities of public institutions in liberal democracies is to formulate recommendations for decision makers. However, public institutions realize that decision makers will often partly ignore their recommendations. This situation of “partial compliance” with recommendations raises a number of philosophical issues for institutions. Based on an analysis of 570 recommendations drawn from 40 Quebec public-sector documents and reports, we identify two issues surrounding the structure of public-policy recommendations.

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms of concept (...) combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

YouTube has been implicated in the transformation of users into extremists and conspiracy theorists. The alleged mechanism for this radicalizing process is YouTube’s recommender system, which is optimized to amplify and promote clips that users are likely to watch through to the end. YouTube optimizes for watch-through for economic reasons: people who watch a video through to the end are likely to then watch the next recommended video as well, which means that more advertisements can be served to them. This (...) is a seemingly innocuous design choice, but it has a troubling side-effect. Critics of YouTube have alleged that the recommender system tends to recommend extremist content and conspiracy theories, as such videos are especially likely to capture and keep users’ attention. To date, the problem of radicalization via the YouTube recommender system has been a matter of speculation. The current study represents the first systematic, pre-registered attempt to establish whether and to what extent the recommender system tends to promote such content. We begin by contextualizing our study in the framework of technological seduction. Next, we explain our methodology. After that, we present our results, which are consistent with the radicalization hypothesis. Finally, we discuss our findings, as well as directions for future research and recommendations for users, industry, and policy-makers. (shrink)

The evidence based medicine movement has championed the need for objective and transparent methods of clinical guideline development. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) framework was developed for that purpose. Central to this framework is criteria for assessing the quality of evidence from clinical studies and the impact that body of evidence should have on our confidence in the clinical effectiveness of a therapy under examination. Grades of Recommendation, Assessment, Development, and Evaluation has been adopted by a (...) number of professional medical societies and organizations as a means for orienting the development of clinical guidelines. As a result, the method of GRADE has implications on how health care is delivered and patient outcomes. In this paper, we reveal several issues with the underlying logic of GRADE that warrant further discussion. First, the definitions of the “grades of evidence” provided by GRADE, while explicit, are functionally vague. Second, the “criteria for assigning grade of evidence” is seemingly arbitrary and arguably logically incoherent. Finally, the GRADE method is unclear on how to integrate evidence grades with other important factors, such as patient preferences, and trade‐offs between costs, benefits, and harms when proposing a clinical practice recommendation. Much of the GRADE method requires judgement on the part of the user, making it unclear as to how the framework reduces bias in recommendations or makes them more transparent—both goals of the programme. It is our view that the issues presented in this paper undermine GRADE's justificatory scheme, thereby limiting the usefulness of GRADE as a tool for developing clinical recommendations. (shrink)

This article summarizes the recommendations concerning robotics as issued by the Commission for the Ethics of Research in Information Sciences and Technologies (CERNA), the French advisory commission for the ethics of information and communication technology (ICT) research. Robotics has numerous applications in which its role can be overwhelming and may lead to unexpected consequences. In this rapidly evolving technological environment, CERNA does not set novel ethical standards but seeks to make ethical deliberation inseparable from scientific activity. Additionally, it provides (...) tools and guidance for researchers and research institutions. (shrink)

This paper examines how science advice can provide policy recommendations in a trustworthy manner. Despite their major political importance, expert recommendations are understudied in the philosophy of science and social epistemology. Matthew Bennett has recently developed a notion of what he calls recommendation trust, according to which well-placed trust in experts’ policy recommendations requires that recommendations are aligned with the interests of the trust-giver. While interest alignment might be central to some cases of public trust, this (...) paper argues against the significance of interest-alignment to meritorious public trust. First, political bodies and citizens can have a basic kind of well-placed recommendation trust in science advice based on an all-things-considered judgement regarding the possession of relevant competencies, responsible conduct, and a proper institutional design. Moreover, scientists’ policy recommendations can be seen as open-ended and as dynamic proposals that enable inter-institutional reasoning and political deliberation. Finally, by providing conditional recommendations, scientists can expand the scope of feasible policy options from which political bodies can choose, thus making the condition of interest alignment even less significant to the trustworthy provision of recommendations. (shrink)

This is the third draft of a paper that aims to clarify the apparent contradictions in the views presented in certain standards and other specifications of health informatics systems, contradictions which come to light when the latter are evaluated from the perspective of realist philosophy. One of the origins of this document was Klein’s discussion paper of 2005-07-02 entitled “Conceptology vs Reality” and the responses from Smith, as well as the several hours of discussions during the 2005 MIE meeting in (...) Geneva. (shrink)

Background: Efforts to better understand and improve letters of recommendation (LORs) in the resident selection process have identified unwritten rules and hidden practices that may limit their effectiveness. The objective of our study is to explore these unwritten rules and hidden practices more fully in one Canadian academic medical community. -/- Methods: We conducted semi-structured, discourse-based interviews with 18 faculty members from the departments of Internal Medicine and Psychiatry at the University of Manitoba, Canada. Interviews were guided by sample LORs (...) and were focused on experiences with either writing or reading LORs. We analyzed interviews using key concepts from genre theory and Aristotle’s appeals to ethos, logos, and pathos. -/- Results: Participants described how the practices surrounding LORs are guided by unwritten rules. These practices contributed to writers’ use of visible strategies and textual silence to establish credibility, build a strong case, and appeal to readers. Readers rely on similar strategies, but not always as intended by the writers. -/- Conclusions: The unwritten rules of one academic community can impede a nationally-facilitated resident selection process. Our findings highlight how critiques and potential improvements to LORs could benefit from considering the use of visible and invisible rhetorical strategies in specific contexts. (shrink)

Emergency situations require individuals to make important changes in their behavior. In the case of the COVID-19 pandemic, official recommendations to avoid the spread of the virus include costly behaviors such as self-quarantining or drastically diminishing social contacts. Compliance (or lack thereof) with these recommendations is a controversial and divisive topic, and lay hypotheses abound regarding what underlies this divide. This paper investigates which cognitive, moral, and emotional traits separate people who comply with official recommendations from those (...) who don't. In four studies (three pre-registered) on both U.S. and French samples, we found that individuals' self-reported compliance with official recommendations during the COVID-19 pandemic was partly driven by individual differences in moral values, disgust sensitivity, and psychological reactance. We discuss the limitations of our studies and suggest possible applications in the context of health communication. (shrink)

The contribution of the data paper publishing paradigm to the knowledge generation and validation processes is becoming substantial and pivotal. In this paper, through the information-processing perspective of Mindsponge Theory, we discuss how the data article publishing system serves as a filtering mechanism for quality control of the increasingly chaotic datasphere. The overemphasis on machine-actionality and technical standards presents some shortcomings and limitations of the data article publishing system, such as the lack of consideration of humanistic values, radical race for (...) big data, and inadequate use of expertise in data evaluation. Without addressing the shortcomings and limitations, the reusability of data will be hindered, and scientific investment to facilitate data sharing will be wasted. Thus, we suggest that the current data paper publishing paradigm needs to be updated with a new philosophy of data. (shrink)

Building on past constructive criticism, the present study provides further methodological development focused on the elimination of bias that may occur during first-person observation. First, various sources of errors that may accompany introspection are distinguished based on previous critical literature. Four main errors are classified, namely attentional, attributional, conceptual, and expressional error. Furthermore, methodological recommendations for the possible elimination of these errors have been determined based on the analysis and focused excerpting of introspective scientific literature. The following groups of (...) methodological recommendations were determined: 1) a better focusing of the subject’s attention to their mental processes, 2) providing suitable stimuli, and 3) the sharing of introspective experience between subjects. Furthermore, the potential of adjustments in introspective research designs for eliminating attentional, attributional, conceptual, and expressional error is discussed. (shrink)

Recently, a group of researchers, led by Daniel J. Ingram (University of Stirling), has conducted a critical review of the literature and experts’ evaluations of the on-the-ground progress to gauge the progress toward 11 recommended research needs and actions in approximately the last two decades. According to the review, most areas of wild meat research and management showed limited progress toward sustainability. The most progressive aspect is understanding the drivers behind hunting and the demand for wild meat.

Although patterns of human activity show a large degree of freedom, they exhibit structural patterns subjected by geographic and social constraints. Aiming at various problems of personalized recommendation in mobile networks, a social network recommendation algorithm is proposed with a variety of context-aware information and combined with a series of social network analysis methods.Based on geographical location and temporal information, potential social relations among users are mined deeply to find the most similar set of users for the target user, then (...) recommendations are carried out incorporating with social relations of the mobile users to effectively solve the problem of recommendation precision. The above study can not only help LBSN designers and developers to better understand their users and grasp their want, but also help to refine the design of their system to provide users with more appropriate applications and services.The experimental results on the real-world dataset verify the feasibility and effectiveness of the proposed algorithm, and it has higher prediction accuracy compared with existing recommendation algorithms. (shrink)

Background Retraction is a mechanism for alerting readers to unreliable material and other problems in the published scientific and scholarly record. Retracted publications generally remain visible and searchable, but the intention of retraction is to mark them as “removed” from the citable record of scholarship. However, in practice, some retracted articles continue to be treated by researchers and the public as valid content as they are often unaware of the retraction. Research over the past decade has identified a number of (...) factors contributing to the unintentional spread of retracted research. The goal of the Reducing the Inadvertent Spread of Retracted Science: Shaping a Research and Implementation Agenda (RISRS) project was to develop an actionable agenda for reducing the inadvertent spread of retracted science. This included identifying how retraction status could be more thoroughly disseminated, and determining what actions are feasible and relevant for particular stakeholders who play a role in the distribution of knowledge. -/- Methods These recommendations were developed as part of a year-long process that included a scoping review of empirical literature and successive rounds of stakeholder consultation, culminating in a three-part online workshop that brought together a diverse body of 65 stakeholders in October–November 2020 to engage in collaborative problem solving and dialogue. Stakeholders held roles such as publishers, editors, researchers, librarians, standards developers, funding program officers, and technologists and worked for institutions such as universities, governmental agencies, funding organizations, publishing houses, libraries, standards organizations, and technology providers. Workshop discussions were seeded by materials derived from stakeholder interviews (N = 47) and short original discussion pieces contributed by stakeholders. The online workshop resulted in a set of recommendations to address the complexities of retracted research throughout the scholarly communications ecosystem. -/- Results The RISRS recommendations are: (1) Develop a systematic cross-industry approach to ensure the public availability of consistent, standardized, interoperable, and timely information about retractions; (2) Recommend a taxonomy of retraction categories/classifications and corresponding retraction metadata that can be adopted by all stakeholders; (3) Develop best practices for coordinating the retraction process to enable timely, fair, unbiased outcomes; and (4) Educate stakeholders about pre- and post-publication stewardship, including retraction and correction of the scholarly record. -/- Conclusions Our stakeholder engagement study led to 4 recommendations to address inadvertent citation of retracted research, and formation of a working group to develop the Communication of Retractions, Removals, and Expressions of Concern (CORREC) Recommended Practice. Further work will be needed to determine how well retractions are currently documented, how retraction of code and datasets impacts related publications, and to identify if retraction metadata (fails to) propagate. Outcomes of all this work should lead to ensuring retracted papers are never cited without awareness of the retraction, and that, in public fora outside of science, retracted papers are not treated as valid scientific outputs. (shrink)

The Adverse Outcome Pathway (AOP) concept is a knowledge assembly and communication tool to facilitate the transparent translation of mechanistic information into outcomes meaningful to the regulatory assessment of chemicals. The AOP framework and associated knowledgebases (KBs) have received significant attention and use in the regulatory toxicology community. However, it is increasingly apparent that the potential stakeholder community for the AOP concept and AOP KBs is broader than scientists and regulators directly involved in chemical safety assessment. In this paper we (...) identify and describe those stakeholders who currently—or in the future—could benefit from the application of the AOP framework and knowledge to specific problems. We also summarize the challenges faced in implementing pathway-based approaches such as the AOP framework in biological sciences, and provide a series of recommendations to meet critical needs to ensure further progression of the framework as a useful, sustainable and dependable tool supporting assessments of both human health and the environment. Although the AOP concept has the potential to significantly impact the organization and interpretation of biological information in a variety of disciplines/applications, this promise can only be fully realized through the active engagement of, and input from multiple stakeholders, requiring multi-pronged substantive long-term planning and strategies. (shrink)

Primarily, this article emphasises that while conducting research, especially one involving human subjects, researchers are expected to comply with applicable global and national ethical standards. Should a researcher fail to do so, he/she stands the risk of breaching research ethics, and this is capable of rendering his/her research unacceptable. Accordingly, this article, making reference to relevant ethical theories, critically examines and analyses the actions of a researcher who set out to investigate treatment recommendations for diarrhoea. Ultimately, a number of (...) ethical pitfalls in the stated research are x-rayed and some recommendations for subsequent studies are provided in this paper. (shrink)

ABSTRACT:This paper examines the compliance of universities in the European Union with the UNESCO Recommendation concerning the Status of Higher–Education Teaching Personnel, which deals primarily with protection for academic freedom. The paper briefly surveys the European genesis of the modern research university and academic freedom, before evaluating compliance with the UNESCO recommendation on institutional autonomy, academic freedom, university governance and tenure. Following from this, the paper examines the reasons for the generally low level of compliance with the UNESCO Recommendation within (...) the EU states, and considers how such compliance could be improved. (shrink)

This essay briefly summarizes the key characteristics and social philosophies in Japan’s vision of Society 5.0. Then it discusses why Vietnam, as a developing country, can learn from the experiences of Japan in establishing its vision for an AI-powered human-centric society. The paper finally provides five concrete recommendations for Vietnam toward a harmonic and human-centric coexistence with increasingly competent and prevalent AI systems, including: Human-centric AI vision; Multidimensional, pluralistic understanding of human-technology relation; AI as a driving force for socio-economic (...) development; Bottom-up, participatory approach for building the vision; and Sustainability and inclusion in the adoption of AI. (shrink)

Growing awareness of the ethical implications of neuroscience in the early years of the 21st century led to the emergence of the new academic field of “neuroethics,” which studies the ethical implications of developments in the neurosciences. However, despite the acceleration and evolution of neuroscience research on nonhuman animals, the unique ethical issues connected with neuroscience research involving nonhuman animals remain underdiscussed. This is a significant oversight given the central place of animal models in neuroscience. To respond to these concerns, (...) the Center for Neuroscience and Society and the Center for the Interaction of Animals and Society at the University of Pennsylvania hosted a workshop on the “Neuroethics of Animal Research” in Philadelphia, Pennsylvania. At the workshop, expert speakers and attendees discussed ethical issues arising from neuroscience research involving nonhuman animals, including the use of animal models in the study of pain and psychiatric conditions, animal brain-machine interfaces, animal–animal chimeras, cerebral organoids, and the relevance of neuroscience to debates about personhood. This paper highlights important emerging ethical issues based on the discussions at the workshop. This paper includes recommendations for research in the United States from the authors based on the discussions at the workshop, loosely following the format of the 2 Gray Matters reports on neuroethics published by the Presidential Commission for the Study of Bioethical Issues. (shrink)

Online education will be paired by developing intelligent systems that can provide personalization to the learner. To that extent ,this paper is proposing the design for an Online Personalized Learning Remediation/Tutoring Tool to help learners find the most suitable teachers for certain topics. The tool relies on a dataset of teacher profiles, comprising the subjects taught, video links, ratings, and experience, so that using machine learning techniques, it could recommend top educators. Applying feature extraction using CountVectorizer and recommendation based on (...) cosine similarity, it will ensure the robust and personalized search experience to the learners. The tool will augment the process of learning by not wasting time of the learner searching for an appropriate teacher and provides an uninterrupted user experience through an easy-to-understand web interface. This system increases the satisfaction of learners along with optimizing their ability to engage with the relevant teachers effectively. (shrink)

As a result of vocal autism activists pushing against traditional views of autism, there is a bilateral debate that reflects a deeper philosophical divide between medical and social definitions of disability. Both sides seek to determine the manner in which autistics and their communities view autism, and thus influence the manner in which cures or treatments are sought, dispensed and taken up. Through an investigation of this debate, this project will explore the practical benefits and ethical obligations of accommodating autistic (...) differences. One side of this debate, which we will call the cure theory approach, seeks treatments that will eradicate or at least minimize autistic symptoms. The philosophical assertion that lies behind this objective is that autistic differences, particularly disruptive autistic differences, ought to be removed. The other side of the debate, which we will call the neurodiverse perspective, seeks to define autism as neurological difference, that is relationally determined, rather than a disorder or a syndrome. The neurodiversity movement recommends educating autistics and their communities regarding how to fully accommodate autistic differences. The underlying philosophical commitment of the neurodiverse perspective is that it is in the best interests of autistics and their communities to accommodate differences, rather than seek treatments that encourage conformity. I will argue that these two sides are not mutually exclusive. Through a synthesis of the neurodiverse and cure theory points of view I will enable the development of a method, which facilitates justice for autistics and their communities. This synthesis garners the maximum capabilities that the expression of autistic differences can offer, and maintains the freedom for all community members to actualize their capabilities. (shrink)

The aim of this project is to develop a system that uses the Internet of Things (IoT) and machine learning (ML) to help farmers select the best crops for their fields. The geolocations are fetched using the GPS receiver by communicating with the satellite. The system consists of IoT sensors that collect data on soil and environmental conditions, such as pH, temperature, humidity, and rainfall. This data is sent to a cloud platform, where ML algorithms analyze it and provide crop (...) recommendations based on historical data, weather forecasts, and soil properties. The system offers a user-friendly interface that allows farmers to access the recommendations, monitor their crops, and provide feedback. The system aims to enhance agricultural productivity, resource efficiency, and sustainability by using data-driven insights. (shrink)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

The automatic integration of rapidly expanding information resources in the life sciences is one of the most challenging goals facing biomedical research today. Controlled vocabularies, terminologies, and coding systems play an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources – for example pertaining to genes and proteins, drugs and diseases – secure in the knowledge that the same terms will also represent the same entities on all occasions of use. In the (...) naming of genes, proteins, and other molecular structures, considerable efforts are under way to reduce the effects of the different naming conventions which have been spawned by different groups of researchers. Electronic patient records, too, increasingly involve the use of standardized terminologies, and tremendous efforts are currently being devoted to the creation of terminology resources that can meet the needs of a future era of personalized medicine, in which genomic and clinical data can be aligned in such a way that the corresponding information systems become interoperable. (shrink)

Collaborative filtering is being used within organizations and in community contexts for knowledge management and decision support as well as the facilitation of interactions among individuals. This article analyzes rhetorical and technical efforts to establish trust in the constructions of individual opinions, reputations, and tastes provided by these systems. These initiatives have some important parallels with early efforts to support quantitative opinion polling and construct the notion of “public opinion.” The article explores specific ways to increase trust in these systems, (...) albeit a “guarded trust” in which individuals actively seek information about system foibles and analyze the reputations of participants. (shrink)