Search (8 results, page 1 of 1)

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Abstract

This conceptual article argues for the value of an approach to privacy in the digital information environment informed by Luciano Floridi's philosophy of information and information ethics. This approach involves achieving informational privacy, through the features of anonymity and obscurity, through an optimal balance of ontological frictions. This approach may be used to modify models for information behavior and for information literacy, giving them a fuller and more effective coverage of privacy issues in the infosphere. For information behavior, the Information Seeking and Communication Model and the Information Grounds conception are most appropriate for this purpose. For information literacy, the metaliteracy model, using a modification a privacy literacy framework, is most suitable.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.9, S.1030-1043

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Abstract

This text proposes a multidisciplinary reflection on the subject of ethics, based on philosophical approaches, using Spinoza's work, Ethics, as a foundation. The power of Spinoza's geometric reasoning and deterministic logic, compatible with formal grammars and programming languages, provides a favorable framework for this purpose. In an information society characterized by an abundance of data and a diversity of perspectives, complex thinking is an essential tool for developing an ethical construct that can deal with the uncertainty and contradictions in the field. Acknowledging the natural complexity of ethics in interpersonal relationships, the use of AI techniques appears unavoidable. Artificial intelligence in KOS offers the potential for processing complex questions through the formal modeling of concepts in ethical discourse. By formalizing problems, we hope to unleash the potential of ethical analysis; by addressing complexity analysis, we propose a mechanism for understanding problems and empowering solutions.

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Abstract

The scale and complexity of the data and algorithms used in artificial intelligence (AI)-based systems present significant challenges for anticipating their ethical, legal, and policy implications. Given these challenges, who does the work of AI ethics, and how do they do it? This study reports findings from interviews with 26 stakeholders in AI research, law, and policy. The primary themes are that the work of AI ethics is structured by personal values and professional commitments, and that it involves situated meaning-making through data and algorithms. Given the stakes involved, it is not enough to simply satisfy that AI will not behave unethically; rather, the work of AI ethics needs to be incentivized.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.3, S.311-322

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Abstract

In this paper we discuss some ethical issues and challenges of the use of algorithms on the web from the perspective of knowledge organization. We review some of the problems that these algorithms and the filter bubbles pose for the users. We contextualize these issues within the user-based approaches to knowledge organization in a larger sense. We review some of the technologies that have been developed to counter these problems as well as initiatives from the knowledge organization field. We conclude with the necessity of adopting a critical and ethical stance towards the use of algorithms on the web and the need for an education in knowledge organization that addresses these issues.

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Abstract

In this paper, I critically examine ethical issues introduced by predictive analytics. I argue firms can have a market incentive to construct deceptively inflated true-positive outcomes: individuals are over-categorized as requiring a penalizing treatment and the treatment leads to mistakenly thinking this label was correct. I show that differences in power between firms developing and using predictive analytics compared to subjects can lead to firms reaping the benefits of predatory predictions while subjects can bear the brunt of the costs. While profitable, the use of predatory predictions can deceive stakeholders by inflating the measurement of accuracy, diminish the individuality of subjects, and exert arbitrary power. I then argue that firms have a responsibility to distinguish between the treatment effect and predictive power of the predictive analytics program, better internalize the costs of categorizing someone as needing a penalizing treatment, and justify the predictions of subjects and general use of predictive analytics. Subjecting individuals to predatory predictions only for a firms' efficiency and benefit is unethical and an arbitrary exertion of power. Firms developing and deploying a predictive analytics program can benefit from constructing predatory predictions while the cost is borne by the less powerful subjects of the program.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.5, S.531-545

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Abstract

The paper examines the integration of born-digital and digitized content into an outdated classification system within the Museum of European Cultures in Berlin. It underscores the predicament encountered by smaller to medium-sized cultural institutions as they navigate between adhering to established knowl­edge management systems and preserving an expanding array of contemporary cultural artifacts. The perspective of infrastructure studies is employed to scrutinize the representation of diverse viewpoints and voices within the museum's collections. The study delves into museum personnel's challenges in cataloging and classifying ethnographic objects utilizing a numerical-alphabetical categorization scheme from the 1930s. It presents an analysis of the limitations inherent in this method, along with its implications for the assimilation of emerging forms of born-digital and digitized objects. Through an exploration of the case of category 74, as observed at the Museum of European Cultures, the study illustrates the complexities of replacing pre-existing systems due to their intricate integration into the socio-technical components of the museum's information infrastructure. The paper reflects on how resource-constrained cultural institutions can take a proactive and ethical approach to knowl­edge management, re-evaluating their knowl­edge infrastructure to promote inclusion and ensure adaptability.

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Abstract

The Cataloguing Code of Ethics, released in January 2021, was the product of a multi-national, multi-year endeavor by the Cataloging Ethics Steering Committee to create a useful framework for the discussion of cataloging ethics. The six Cataloging Ethics Steering Committee members, based in the United States, United Kingdom, and Canada, recount the efforts of the group and the cataloging community leading up to the release of the Code, as well as provide their thoughts on the challenges of creating the document, lessons learned, and the future of the Code.

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Abstract

Ethics are principles which provide a framework for making decisions that best reflect a set of values. Cataloging carries power, so ethical decision-making is crucial. Because cataloging requires decision-making in areas that differ from other library work, cataloging ethics are a distinct subset of library ethics. Cataloging ethics draw on the primary values of serving the needs of users and providing access to materials. Cataloging ethics are not new, but they have received increased attention since the 1970s. Major current issues in cataloging ethics include the creation of a code of ethics; ongoing debate on the appropriate role of neutrality in cataloging misleading materials and in subject heading lists and classification schemes; how and to what degree considerations of privacy and self-determination should shape authority work; and whether or not our current cataloging codes are sufficiently user-focused.