Journal articles: 'Algorithmic knowledge'

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Surowik, Dariusz. "Logic of Algorithmic Knowledge." Studies in Logic, Grammar and Rhetoric 42, no. 1 (September 1, 2015): 163–72. http://dx.doi.org/10.1515/slgr-2015-0035.

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Abstract In this paper we consider the construction of a LAK system of temporal-epistemic logic which is used to formally describe algorithmic knowledge. We propose an axiom system of LAK and discuss the basic properties of this logic.

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Pucella, Riccardo. "Deductive Algorithmic Knowledge." Journal of Logic and Computation 16, no. 2 (April 1, 2006): 287–309. http://dx.doi.org/10.1093/logcom/exi078.

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Anderson, John R. "Methodologies for studying human knowledge." Behavioral and Brain Sciences 10, no. 3 (September 1987): 467–77. http://dx.doi.org/10.1017/s0140525x00023554.

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AbstractThe appropriate methodology for psychological research depends on whether one is studying mental algorithms or their implementation. Mental algorithms are abstract specifications of the steps taken by procedures that run in the mind. Implementational issues concern the speed and reliability of these procedures. The algorithmic level can be explored only by studying across-task variation. This contrasts with psychology's dominant methodology of looking for within-task generalities, which is appropriate only for studying implementational issues.The implementation-algorithm distinction is related to a number of other “levels” considered in cognitive science. Its realization in Anderson's ACT theory of cognition is discussed. Research at the algorithmic level is more promising because it is hard to make further fundamental scientific progress at the implementational level with the methodologies available. Protocol data, which are appropriate only for algorithm-level theories, provide a richer source than data at the implementational level. Research at the algorithmic level will also yield more insight into fundamental properties of human knowledge because it is the level at which significant learning transitions are defined.The best way to study the algorithmic level is to look for differential learning outcomes in pedagogical experiments that manipulate instructional experience. This provides control and prediction in realistically complex learning situations. The intelligent tutoring paradigm provides a particularly fruitful way to implement such experiments.The implications of this analysis for the issue of modularity of mind, the status of language, research on human/computer interaction, and connectionist models are also examined.

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Carlson, Matt. "Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism." New Media & Society 20, no. 5 (May 22, 2017): 1755–72. http://dx.doi.org/10.1177/1461444817706684.

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Journalistic judgment is both a central and fraught function of journalism. The privileging of objectivity norms and the externalization of newsworthiness in discourses about journalism leave little room for the legitimation of journalists’ subjective judgment. This tension has become more apparent in the digital news era due to the growing use of algorithms in automated news distribution and production. This article argues that algorithmic judgment should be considered distinct from journalists’ professional judgment. Algorithmic judgment presents a fundamental challenge to news judgment based on the twin beliefs that human subjectivity is inherently suspect and in need of replacement, while algorithms are inherently objective and in need of implementation. The supplanting of human judgment with algorithmic judgment has significant consequences for both the shape of news and its legitimating discourses.

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Amoore, Louise, and Rita Raley. "Securing with algorithms: Knowledge, decision, sovereignty." Security Dialogue 48, no. 1 (December 12, 2016): 3–10. http://dx.doi.org/10.1177/0967010616680753.

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Amid the deployment of algorithmic techniques for security – from the gathering of intelligence data to the proliferation of smart borders and predictive policing – what are the political and ethical stakes involved in securing with algorithms? Taking seriously the generative and world-making capacities of contemporary algorithms, this special issue draws attention to the embodied actions of algorithms as they extend cognition, agency and responsibility beyond the conventional sites of the human, the state and sovereignty. Though focusing on different modes of algorithmic security, each of the contributions to the special issue shares a concern with what it means to claim security on the terrain of incalculable and uncertain futures. To secure with algorithms is to reorient the embodied relation to uncertainty, so that human and non-human cognitive beings experimentally generate and learn what to bring to the surface of attention for a security action.

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Monahan, Torin. "Algorithmic Fetishism." Surveillance & Society 16, no. 1 (April 1, 2018): 1–5. http://dx.doi.org/10.24908/ss.v16i1.10827.

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Surveillance-infused forms of algorithmic discrimination are beginning to capture public and scholarly attention. While this is an encouraging development, this editorial questions the parameters of this emerging discussion and cautions against algorithmic fetishism. I characterize algorithmic fetishism as the pleasurable pursuit of opening the black box, discovering the code hidden inside, exploring its beauty and flaws, and explicating its intricacies. It is a technophilic desire for arcane knowledge that can never be grasped completely, so it continually lures one forward into technical realms while deferring the point of intervention. The editorial concludes with a review of the articles in this open issue.

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LOMUSCIO, ALESSIO, and MARK RYAN. "An algorithmic approach to knowledge evolution." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 13, no. 2 (April 1999): 119–32. http://dx.doi.org/10.1017/s0890060499132062.

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Intelligent agents must update their knowledge base as they acquire new information about their environment. The modal logic S5n has been designed for representing knowledge bases in societies of agents. Halpern and Vardi have proposed the notion of refinement of S5n Kripke models in order to solve multi-agent problems in which knowledge evolves. We argue that there are some problems with their proposal and attempt to solve them by moving from Kripke models to their corresponding trees. We define refinement of a tree with a formula, show some properties of the notion, and illustrate with the muddy children puzzle. We show how some diagnosis problems in engineering can be modelled as knowledge-based multi-agent systems, and hence how our approach can address them.

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Yakubjanovna, Turaboeva Muqaddas. "Developing Linguistic Competence Through Algorithmic Exercises In 5th Grade Mother Tongue Lessons." American Journal of Social Science and Education Innovations 02, no. 12 (December 28, 2020): 235–39. http://dx.doi.org/10.37547/tajssei/volume02issue12-42.

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This article discusses algorithmic exercises as a means of increasing the effectiveness of 5th grade mother tongue teaching. In particular, it is scientifically based on the development of pupils' knowledge of linguistic competence through the performance of algorithmic exercises.

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Holen, A. T., A. Botnen, P. Stoa, and J. J. Keronen. "Coupling between knowledge-based and algorithmic methods." Proceedings of the IEEE 80, no. 5 (May 1992): 745–57. http://dx.doi.org/10.1109/5.137229.

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Bhattarai, Pratistha. "Algorithmic Value: Cultural Encoding, Textuality, and the Myth of “Source Code”." Catalyst: Feminism, Theory, Technoscience 3, no. 1 (October 19, 2017): 1–28. http://dx.doi.org/10.28968/cftt.v3i1.28786.

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In this article, I provide a Spivakian analysis of computational algorithms. Building upon Gayatri Spivak’s claim that the value coding of late capitalism extends beyond the economic realm to the cultural and affective, I show that it seeps into the algorithmic as well. The recent proliferation of algorithmic applications has been met by an increased scholarly interest in their underlying mechanisms. Several critics of predictive algorithms, for instance, proceed as though the racial and gender discrimination that a given algorithm enacts upon execution can be positively attributed to -- and mitigated through a re-coding of – either its training data or its “source code.” There is little denying that the logic of computation undergirds much of our sociality. But, as I argue in this article, to concentrate the source of an algorithm’s action in its semiotic representations is to hide and legitimize the value codings that lend these representations their efficacy. My aim in this article is two-fold. First, to show how seemingly benign investments in algorithms can reproduce, in a larger network, the exploitative value systems that manage the worth of knowledge, epistemologies, labor, and bodies. Second, to raise a question of methodology: What antitechnocratic, nonhegemonic engagements with algorithms might feminists produce that do not privilege the algorithmic as a site of intervention

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Mackinnon, Lee. "Toward an Algorithmic Realism: The Evolving Nature of Astronomical Knowledge in Representations of the Non-Visible." Leonardo 47, no. 3 (June 2014): 225–31. http://dx.doi.org/10.1162/leon_a_00764.

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This paper explores the gathering of radio, optical and electromagnetic wavelength data in assembling images of the Crab Nebula (1844–2000). The author considers the expanding fields of astronomical and astrophysical knowledge to which such data analysis has given rise. She suggests that the data that makes such imaging possible moves us further from conventions of the optical real toward an algorithmic realism, alluding to time-scales that delimit and circumvent human time. Thus Cartesian metaphysics is displaced—the human becomes one agent among many in a process of algorithmic inference.

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Draude, Claude, Goda Klumbyte, Phillip Lücking, and Pat Treusch. "Situated algorithms: a sociotechnical systemic approach to bias." Online Information Review 44, no. 2 (November 12, 2019): 325–42. http://dx.doi.org/10.1108/oir-10-2018-0332.

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Purpose The purpose of this paper is to propose that in order to tackle the question of bias in algorithms, a systemic, sociotechnical and holistic perspective is needed. With reference to the term “algorithmic culture,” the interconnectedness and mutual shaping of society and technology are postulated. A sociotechnical approach requires translational work between and across disciplines. This conceptual paper undertakes such translational work. It exemplifies how gender and diversity studies, by bringing in expertise on addressing bias and structural inequalities, provide a crucial source for analyzing and mitigating bias in algorithmic systems. Design/methodology/approach After introducing the sociotechnical context, an overview is provided regarding the contemporary discourse around bias in algorithms, debates around algorithmic culture, knowledge production and bias identification as well as common solutions. The key concepts of gender studies (situated knowledges and strong objectivity) and concrete examples of gender bias then serve as a backdrop for revisiting contemporary debates. Findings The key concepts reframe the discourse on bias and concepts such as algorithmic fairness and transparency by contextualizing and situating them. The paper includes specific suggestions for researchers and practitioners on how to account for social inequalities in the design of algorithmic systems. Originality/value A systemic, gender-informed approach for addressing the issue is provided, and a concrete, applicable methodology toward a situated understanding of algorithmic bias is laid out, providing an important contribution for an urgent multidisciplinary dialogue.

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Jarrahi, Mohammad Hossein, Gemma Newlands, Min Kyung Lee, Christine T. Wolf, Eliscia Kinder, and Will Sutherland. "Algorithmic management in a work context." Big Data & Society 8, no. 2 (July 2021): 205395172110203. http://dx.doi.org/10.1177/20539517211020332.

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The rapid development of machine-learning algorithms, which underpin contemporary artificial intelligence systems, has created new opportunities for the automation of work processes and management functions. While algorithmic management has been observed primarily within the platform-mediated gig economy, its transformative reach and consequences are also spreading to more standard work settings. Exploring algorithmic management as a sociotechnical concept, which reflects both technological infrastructures and organizational choices, we discuss how algorithmic management may influence existing power and social structures within organizations. We identify three key issues. First, we explore how algorithmic management shapes pre-existing power dynamics between workers and managers. Second, we discuss how algorithmic management demands new roles and competencies while also fostering oppositional attitudes toward algorithms. Third, we explain how algorithmic management impacts knowledge and information exchange within an organization, unpacking the concept of opacity on both a technical and organizational level. We conclude by situating this piece in broader discussions on the future of work, accountability, and identifying future research steps.

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O'Hara, Ian. "Feedback Loops: Algorithmic Authority, Emergent Biases, and Implications for Information Literacy." Pennsylvania Libraries: Research & Practice 9, no. 1 (June 29, 2021): 8–15. http://dx.doi.org/10.5195/palrap.2021.231.

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Algorithms have become increasingly ubiquitous in our modern, technologically driven society. Algorithmic tools that are embedded to “enhance” the user experience when information-seeking carry problematic epistemological concerns. These algorithms are developed and interjected into search tools by human beings who, consciously or not, tend to impart biases into the functionality of the information retrieval process. These search tools have become our primary arbiters of knowledge and have been granted relatively unmitigated sovereignty over our perceptions of reality and truth. This article provides broader awareness of how the bias embedded within these algorithmic systems structures users’ perception and knowledge of the world, preserving traditional power hierarchies and the marginalization of specific groups of people, and examines the implications of algorithmic search systems on information literacy instruction from a critical pedagogical perspective.

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Bishop, Sophie. "Managing visibility on YouTube through algorithmic gossip." New Media & Society 21, no. 11-12 (June 15, 2019): 2589–606. http://dx.doi.org/10.1177/1461444819854731.

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Beauty vloggers’ feminised outputs often position them outside of traditional spheres of technical expertise, however, their strategic management of algorithmic visibility makes them an illuminating source of algorithmic knowledge. I draw from an ethnography of beauty vloggers and industry stakeholders to study the collaborative and directive processes used to formulate and sustain algorithmic expertise – algorithmic gossip. Algorithmic gossip is defined as communally and socially informed theories and strategies pertaining to recommender algorithms, shared and implemented to engender financial consistency and visibility on algorithmically structured social media platforms. Gossip is productive: community communication and talk informs and supports practices such as uploading frequently and producing feminised beauty content to perform more effectively on YouTube. Taking gossip seriously can present a valuable resource for revealing information about how algorithms work and have worked, in addition to revealing how perceptions of algorithms inform content production.

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Kotras, Baptiste. "Mass personalization: Predictive marketing algorithms and the reshaping of consumer knowledge." Big Data & Society 7, no. 2 (July 2020): 205395172095158. http://dx.doi.org/10.1177/2053951720951581.

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This paper focuses on the conception and use of machine-learning algorithms for marketing. In the last years, specialized service providers as well as in-house data scientists have been increasingly using machine learning to predict consumer behavior for large companies. Predictive marketing thus revives the old dream of one-to-one, perfectly adjusted selling techniques, now at an unprecedented scale. How do predictive marketing devices change the way corporations know and model their customers? Drawing from STS and the sociology of quantification, I propose to study the original ambivalence that characterizes the promise of a mass personalization, i.e. algorithmic processes in which the precise adjustment of prediction to unique individuals involves the computation of massive datasets. By studying algorithms in practice, I show how the active embedding of local preexisting consumer knowledge and punctual de-personalization mechanisms are keys to the epistemic and organizational success of predictive marketing. This paper argues for the study of algorithms in their contexts and suggests new perspectives on algorithmic objectivity.

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Kadirov Jasur Abdumalikovich. "Methodology of developing algorithmic skills through mathematical images in preschool children." International Journal on Integrated Education 3, no. 9 (September 26, 2020): 240–41. http://dx.doi.org/10.31149/ijie.v3i9.637.

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This article focuses on the methods, problems and solutions for the development of methods for improving the mathematical knowledge and algorithmic skills of preschool children. It is aimed at paying attention to the changing characteristics of the properties of the algorithm, taking into account the age, and to ensure that children act on the basis of algorithmic skills in lifestyle and training.

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Orduna, E., F. Garces, and E. Handschin. "Algorithmic-knowledge-based adaptive coordination in transmission protection." IEEE Transactions on Power Delivery 18, no. 1 (January 2003): 61–65. http://dx.doi.org/10.1109/tpwrd.2002.806683.

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Bona, B., P. Brandimarte, and C. Greco. "Algorithmic and Knowledge-Based Techniques for Adaptive Control." IFAC Proceedings Volumes 22, no. 6 (July 1989): 219–23. http://dx.doi.org/10.1016/s1474-6670(17)54375-x.

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Orduna, E., F. Garces, and E. Handschin. "Algorithmic-Knowledge Based Adaptive Coordination in Transmission Protection." IEEE Power Engineering Review 22, no. 12 (December 2002): 63. http://dx.doi.org/10.1109/mper.2002.4311922.

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Richmond, Sheldon. "Post-Knowledge." Dialogue and Universalism 29, no. 2 (2019): 123–45. http://dx.doi.org/10.5840/du201929226.

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The monopolization of our techno-scientific culture by digital information technology, the Technopoly has unintentionally resulted in the extinction of knowledge or postknowledge, by reducing knowledge to systems of symbols—formalized algorithmic hierarchies of symbol-systems without external reference; a totalistic virtuality, or real virtuality. The extinction of knowledge or post-knowledge has resulted in two mutually reinforcing situations. One situation is the rise of a new elite of technology experts. The other situation is the dummification of people. These two mutually reinforcing situations further result in an illegitimate role reversal between people and their machines. The machines become treated as smart; people become treated as dummies. The role reversal of machines and people reinforces the monopoly of digital technology over everything. The monopoly of digital techno-scientific culture, the Technopoly, becomes accepted without question and without criticism. However, there is a way to retrieve knowledge, and that way is through restoring the (Ionian) tradition of critical discussion within all our institutions. Critical discussion can be restored by increasing democratic participation in our techno-scientific culture, which amounts to implementing a Socratic social architecture.

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Oliver, Ron. "Measuring Hierarchical Levels of Programming Knowledge." Journal of Educational Computing Research 9, no. 3 (August 1993): 299–312. http://dx.doi.org/10.2190/0lgx-m45x-2wbk-b7a6.

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This article describes the development and implementation of the Algorithmic Process Test (APT), an instrument that measures the achievement of semantic programming knowledge among novice programmers. The APT measures three distinct components of semantic programming knowledge, the attributes of which are discussed in detail in the article. An implementation among 101 sixteen-year-old novice programmers provided strong evidence of developmental levels among the three knowledge components of the APT. Among this sample of students, it was also found that there was strong achievement in the lower levels of semantic programming knowledge, but few students demonstrated achievement at the highest level despite its critical importance for programming success.

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Makuseva, T. G., and E. V. Yakovleva. "FORMATION OF LOGIC - ALGORITHMIC CULTURE OF STUDENTS IN THE PROCESS OF TEACHING NATURAL SCIENTIFIC DISCIPLINES." Bulletin of Kazakh National Women's Teacher Training University, no. 2 (July 16, 2021): 79–89. http://dx.doi.org/10.52512/2306-5079-2021-86-2-79-89.

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The paper substantiates the need for the formation of a logical and algorithmic culture of students, which contributes to the conscious perception of educational material, which is adequate to modern school and university education in order to instill information and computer literacy in the younger generation. Teaching students to generalize, systematize, apply logical knowledge in a new situation, transfer the acquired knowledge from one subject to another is one of the main tasks of a modern school. At the same time, the logical and algorithmic level of their assimilation provides such a quality of knowledge as completeness and effectiveness, i.e. the student can list all the leading elements of knowledge, define each of them, characterize their main features, and also perform tasks on the topic using the acquired knowledge and skills. The generalization of the practical experience of the organization of the educational process allowed us to offer methodological recommendations for the organization of the formation of the logical and algorithmic culture of students on the basis of interdisciplinary connections in the process of teaching natural science disciplines. In the article, this technique is implemented with the help of one of the new forms of organization of classroom work at the university – complex seminars. The plans of conducting complex seminars on the topics "Harmonic oscillations" and "Integral and its application in physics" are given.

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Zaurbekov, N. S., and G. A. Sherkhan. "ABOUT PROBLEMS AND METHOD OF TEACHING STUDENTS OF SENIOR CLASSES TO THE BASES OF ALGORITHMIZATION AND PROGRAMMING." BULLETIN Series of Physics & Mathematical Sciences 69, no. 1 (March 10, 2020): 339–45. http://dx.doi.org/10.51889/2020-1.1728-7901.60.

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Due to the high level of continuous development of science and technology, programming languages are constantly updated and changed. Programming has become an important tool for the development of creative abilities, intelligence and thinking of students, as well as the formation of knowledge, skills. The article discusses the problems of teaching the basics of programming, which allows them to organize, structure, systematize information and knowledge, understand the importance of information modeling, ways of presenting information and use it in the process of reviewing and making decisions, mastering modern information technologies . Algorithmic thinking grows throughout life under the influence of external conditions and additional factors. The need to search for new effective ways of forming algorithmic thinking in adolescents shows the connection of the importance of personality with the aim of further self-knowledge in the modern computerized world. The main purpose of this article is to identify some of the problems of teaching the basics of programming languages and ways to solve them. The study of the topic “Algorithmization and programming” revealed the importance of an effective method for the formation of algorithmic thinking in high school students in the development of algorithms and their application in solving problems.

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Al-shukri, Noor Ameer, and Basim Hasan Al-Majidi. "Algorithmic Synergy and Architectural Form Generation Mechanisms." Journal of Engineering 26, no. 9 (September 1, 2020): 114–36. http://dx.doi.org/10.31026/j.eng.2020.09.08.

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Today, the architecture field is witnessing a noticeable evolution regarding the used tools that the designer should invest in a peculiar way that is made available in architecture through the concept of synergy generally and algorithmic synergy specifically. The synergy is meant to study and analyze the cooperative behavior of complex systems and self-organizing systems that leads to different outputs referred to by the synergy as the (whole), which is bigger than the sum of parts and in architecture, it's translated as the architectural form. This point resulted in a need of a specific study regarding the concept of synergy that focuses on the cooperative, synergistic relations within the trilogy of (form, structure, and material) and clarifies the role of technological evolution of design tools through algorithmic synergy in formulating that relation, thus resulted in the research's problem which came in the following statement (The lack of clear knowledge of the algorithmic synergy and its mechanisms in generating and discovering the architectural form digitally) and to solve this problem and Achieving the research goal which is represented in (Clarifying the knowledge regarding the role of algorithmic synergy and its mechanisms in generating and discovering the architectural form digitally), the research clarifies the concept of "Synergy" in general and "Algorithmic Synergy" precisely in order to get the epitome of vocabulary on the theoretical part and moving on to the practical application on elected projects samples moving on to the conclusions and recommendations that shows having the architecture a self-organizing synergy system connects the designer and the developed digital tool that is provided by algorithmic synergy, plays a vital role in reaching the digitally synergized whole that represented by the architectural form.

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Swart, Joëlle. "Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media." Social Media + Society 7, no. 2 (April 2021): 205630512110088. http://dx.doi.org/10.1177/20563051211008828.

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The news that young people consume is increasingly subject to algorithmic curation. Yet, while numerous studies explore how algorithms exert power in citizens’ everyday life, little is known about how young people themselves perceive, learn about, and deal with news personalization. Considering the interactions between algorithms and users from an user-centric perspective, this article explores how young people make sense of, feel about, and engage with algorithmic news curation on social media and when such everyday experiences contribute to their algorithmic literacy. Employing in-depth interviews in combination with the walk-through method and think-aloud protocols with a diverse group of 22 young people aged 16–26 years, it addresses three current methodological challenges to studying algorithmic literacy: first, the lack of an established baseline about how algorithms operate; second, the opacity of algorithms within everyday media use; and third, limitations in technological vocabularies that hinder young people in articulating their algorithmic encounters. It finds that users’ sense-making strategies of algorithms are context-specific, triggered by expectancy violations and explicit personalization cues. However, young people’s intuitive and experience-based insights into news personalization do not automatically enable young people to verbalize these, nor does having knowledge about algorithms necessarily stimulate users to intervene in algorithmic decisions.

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Wexler, Mark N., and Judy Oberlander. "Robo-advisors (RAs): the programmed self-service market for professional advice." Journal of Service Theory and Practice 31, no. 3 (January 8, 2021): 351–65. http://dx.doi.org/10.1108/jstp-07-2020-0153.

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PurposeThis conceptual paper draws together an interdisciplinary approach to robo-advisors (RAs) as an example of an early and successful example of automated, programmed professional services.Design/methodology/approachLittle is known about the forces driving this change in the delivery of professional service. This work explores the drivers of RAs, the degree of disruption incurred by the introduction of RAs, and how, as RAs advance, trust in algorithmic authority aids in legitimating RAs as smart information.FindingsFrom the firms' perspective, the drivers include rebranding occasioned by the financial crisis (2008), the widening of the client base and the “on-trend” nature of algorithmic authority guided by artificial intelligence (AI) embedded in RAs. This examination of the drivers of RAs indicates that professional service automation is aligned with information society trends and is likely to expand.Practical implicationsExamining RAs as an indicator of the future introduction of programmed professional services suggests that success increases when the algorithmic authority in the programmed serves are minimally disruptive, trustworthy and expand the client base while keeping the knowledge domain of the profession under control of the industry.Originality/valueTreating RAs as an early instance of successfully embedding knowledge in AI and algorithmically based platforms adds to the early stages of theory and practice in the monetization and automation of professional knowledge-based services.

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Köchling, Alina, and Marius Claus Wehner. "Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development." Business Research 13, no. 3 (November 2020): 795–848. http://dx.doi.org/10.1007/s40685-020-00134-w.

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AbstractAlgorithmic decision-making is becoming increasingly common as a new source of advice in HR recruitment and HR development. While firms implement algorithmic decision-making to save costs as well as increase efficiency and objectivity, algorithmic decision-making might also lead to the unfair treatment of certain groups of people, implicit discrimination, and perceived unfairness. Current knowledge about the threats of unfairness and (implicit) discrimination by algorithmic decision-making is mostly unexplored in the human resource management context. Our goal is to clarify the current state of research related to HR recruitment and HR development, identify research gaps, and provide crucial future research directions. Based on a systematic review of 36 journal articles from 2014 to 2020, we present some applications of algorithmic decision-making and evaluate the possible pitfalls in these two essential HR functions. In doing this, we inform researchers and practitioners, offer important theoretical and practical implications, and suggest fruitful avenues for future research.

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Dudhwala, Farzana, and Lotta Björklund Larsen. "Recalibration in counting and accounting practices: Dealing with algorithmic output in public and private." Big Data & Society 6, no. 2 (July 2019): 205395171985875. http://dx.doi.org/10.1177/2053951719858751.

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Algorithms are increasingly affecting us in our daily lives. They seem to be everywhere, yet they are seldom seen by the humans dealing with the consequences that result from them. Yet, in recent theorisations, there is a risk that the algorithm is being given too much prominence. This article addresses the interaction between algorithmic outputs and the humans engaging with them by drawing on studies of two distinct empirical fields – self-quantification and audit controls of taxpayers. We explore recalibration as a way to understand the practices and processes involved when, on the one hand, decisions are made based on results from algorithmic calculations in counting and accounting software, and on the other hand, when decisions are made based on human experience/knowledge. In particular, we are concerned with moments when an algorithmic output differs from expectations of ‘normalcy’ and ‘normativity’ in any given situation. This could be a ‘normal’ relation between sales and VAT deductions for a business, or a ‘normal’ number of steps one takes in a day, or ‘normative’ as it is according to the book, following guidelines and recommendations from other sources. In these moments, we argue that a process of recalibration occurs – an effortful moment where, rather than treat the algorithmic output as given, individuals’ tacit knowledge, experiences and intuition are brought into play to address the deviation from the normal and normative.

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Allsopp, David, Louann Lovin, Gerald Green, and Emma Savage-Davis. "Why Students with Special Needs Have Difficulty Learning Mathematics and What Teachers Can Do to Help." Mathematics Teaching in the Middle School 8, no. 6 (February 2003): 308–14. http://dx.doi.org/10.5951/mtms.8.6.0308.

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The national council of teachers of Mathematics advocates a balanced approach of teaching both procedural and conceptual knowledge (NCTM 2000). In practice, however, students with special needs often receive a great deal of algorithmic instruction because mastering algorithms is what we “see” them struggle with the most. Even with a heavy dose of algorithmic instruction, many of these students still have difficulty performing algorithms efficiently. Furthermore, without developing conceptual understanding while learning algorithms, these students will never understand foundational mathematical concepts.

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Doroshenko, A. E., L. M. Zakhariya, and G. E. Tseitlin. "Formalization of algorithmic knowledge of object domains in terms of the algebra of algorithmics." Cybernetics and Systems Analysis 43, no. 6 (November 2007): 767–78. http://dx.doi.org/10.1007/s10559-007-0101-3.

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Fisher, Eran. "The ledger and the diary: algorithmic knowledge and subjectivity." Continuum 34, no. 3 (February 10, 2020): 378–97. http://dx.doi.org/10.1080/10304312.2020.1717445.

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Tseytlin, G. Ye, and L. M. Zakhariya. "Algebraic-algorithmic means for designing knowledge of object domains." Cybernetics and Systems Analysis 45, no. 6 (November 2009): 854–63. http://dx.doi.org/10.1007/s10559-009-9155-8.

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Dong, Zhaoan, Jiaheng Lu, Tok Wang Ling, Ju Fan, and Yueguo Chen. "Using hybrid algorithmic-crowdsourcing methods for academic knowledge acquisition." Cluster Computing 20, no. 4 (September 25, 2017): 3629–41. http://dx.doi.org/10.1007/s10586-017-1089-8.

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Harkens, Adam. "The ghost in the legal machine: algorithmic governmentality, economy, and the practice of law." Journal of Information, Communication and Ethics in Society 16, no. 1 (March 12, 2018): 16–31. http://dx.doi.org/10.1108/jices-09-2016-0038.

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Purpose This paper aims to investigate algorithmic governmentality – as proposed by Antoinette Rouvroy – specifically in relation to law. It seeks to show how algorithmic profiling can be particularly attractive for those in legal practice, given restraints on time and resources. It deviates from Rouvroy in two ways. First, it argues that algorithmic governmentality does not contrast with neoliberal modes of government in that it allows indirect rule through economic calculations. Second, it argues that critique of such systems is possible, especially if the creative nature of law can be harnessed effectively. Design/methodology/approach This is a conceptual paper, with a theory-based approach, that is intended to explore relevant issues related to algorithmic governmentality as a basis for future empirical research. It builds on governmentality and socio-legal studies, as well as research on algorithmic practices and some documentary analysis of reports and public-facing marketing of relevant technologies. Findings This paper provides insights on how algorithmic knowledge is collected, constructed and applied in different situations. It provides examples of how algorithms are currently used and how trends are developing. It demonstrates how such uses can be informed by socio-political and economic rationalities. Research limitations/implications Further empirical research is required to test the theoretical findings. Originality/value This paper takes up Rouvroy’s question of whether we are at the end(s) of critique and seeks to identify where such critique can be made possible. It also highlights the importance of acknowledging the role of political rationalities in informing the activity of algorithmic assemblages.

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Рындин, Н. А. "STRATEGY OF AUTOMATED CREATION OF MULTICOMPONENT SOFTWARE TOOLS BASED ON OPTIMIZATION OF KNOWLEDGE SOURCES." СИСТЕМЫ УПРАВЛЕНИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ, no. 3(85) (September 30, 2021): 46–53. http://dx.doi.org/10.36622/vstu.2021.85.3.009.

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В статье описывается алгоритмическая стратегия, способствующая созданию многокомпонентных программных средств. Представлено определение задачи идентификации набора компонентов, математическая формулировка, процедура решения и некоторые результаты вычислений. The article describes an algorithmic strategy that contributes to the creation of multicomponent software tools. The definition of the problem of identifying a set of components, a mathematical formulation, a solution procedure and some calculation results are presented.

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Saurwein, Florian, Natascha Just, and Michael Latzer. "Governance of algorithms: options and limitations." info 17, no. 6 (September 14, 2015): 35–49. http://dx.doi.org/10.1108/info-05-2015-0025.

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Purpose – The purpose of this paper is to contribute to a better understanding of governance choice in the area of algorithmic selection. Algorithms on the Internet shape our daily lives and realities. They select information, automatically assign relevance to them and keep people from drowning in an information flood. The benefits of algorithms are accompanied by risks and governance challenges. Design/methodology/approach – Based on empirical case analyses and a review of the literature, the paper chooses a risk-based governance approach. It identifies and categorizes applications of algorithmic selection and attendant risks. Then, it explores the range of institutional governance options and discusses applied and proposed governance measures for algorithmic selection and the limitations of governance options. Findings – Analyses reveal that there are no one-size-fits-all solutions for the governance of algorithms. Attention has to shift to multi-dimensional solutions and combinations of governance measures that mutually enable and complement each other. Limited knowledge about the developments of markets, risks and the effects of governance interventions hampers the choice of an adequate governance mix. Uncertainties call for risk and technology assessment to strengthen the foundations for evidence-based governance. Originality/value – The paper furthers the understanding of governance choice in the area of algorithmic selection with a structured synopsis on rationales, options and limitations for the governance of algorithms. It provides a functional typology of applications of algorithmic selection, a comprehensive overview of the risks of algorithmic selection and a systematic discussion of governance options and its limitations.

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ANDERLE, Michal. "PRASK – an Algorithmic Competitionfor Middle Schoolers in Slovakia." Olympiads in Informatics 12 (May 15, 2018): 147–57. http://dx.doi.org/10.15388/ioi.2018.12.

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Although informatics education is compulsory in Slovak middle schools, its curriculum is insufficient to prepare the pupils for competitions such as the national Olympiad in informatics. There is a huge gap in knowledge that needs to be addressed. To reduce this problem, PRASK, an algorithmic contest for middle schoolers (approx. ages 10–15), was created in 2015. In this paper we discuss the main concepts behind this competition, ways of dealing with insufficient computational knowledge, types of tasks used to engage and educate young competitors, and some results and lessons learned from the first four years of this competition.

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Hälterlein, Jens. "Epistemologies of predictive policing: Mathematical social science, social physics and machine learning." Big Data & Society 8, no. 1 (January 2021): 205395172110031. http://dx.doi.org/10.1177/20539517211003118.

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Predictive policing has become a new panacea for crime prevention. However, we still know too little about the performance of computational methods in the context of predictive policing. The paper provides a detailed analysis of existing approaches to algorithmic crime forecasting. First, it is explained how predictive policing makes use of predictive models to generate crime forecasts. Afterwards, three epistemologies of predictive policing are distinguished: mathematical social science, social physics and machine learning. Finally, it is shown that these epistemologies have significant implications for the constitution of predictive knowledge in terms of its genesis, scope, intelligibility and accessibility. It is the different ways future crimes are rendered knowledgeable in order to act upon them that reaffirm or reconfigure the status of criminological knowledge within the criminal justice system, direct the attention of law enforcement agencies to particular types of crimes and criminals and blank out others, satisfy the claim for the meaningfulness of predictions or break with it and allow professionals to understand the algorithmic systems they shall rely on or turn them into a black box. By distinguishing epistemologies and analysing their implications, this analysis provides insight into the techno-scientific foundations of predictive policing and enables us to critically engage with the socio-technical practices of algorithmic crime forecasting.

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Bless, Patrick N., Shiv G. Kapoor, Richard E. DeVor, and Diego Klabjan. "An Algorithmic Strategy for Automated Generation of Multicomponent Software Tools for Virtual Manufacturing." Journal of Manufacturing Science and Engineering 127, no. 4 (August 30, 2004): 866–74. http://dx.doi.org/10.1115/1.1954792.

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This paper describes an algorithmic strategy to facilitate the generation of multicomponent software tools for computer-aided manufacturing (CAM) and virtual manufacturing (VM). Components that are often used to build CAM and VM applications include a wide range of domain-specific knowledge sources and also more general utility components with often very heterogeneous characteristics. The identification of a suitable and compatible set of these components is the first and arguably most important step during the development process of any CAM or VM application. This paper presents an algorithmic strategy that automates this development step by solving a time-expanded network problem, referred to as the component set identification (CSI) problem. A definition of the CSI problem, a mathematical formulation, a solution procedure, and some computational results are presented. Finally, an application to predict hole quality in drilling is used to illustrate the functionality of the proposed algorithmic strategy.

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Ebby, Caroline Brayer. "The powers and pitfalls of algorithmic knowledge: a case study." Journal of Mathematical Behavior 24, no. 1 (January 2005): 73–87. http://dx.doi.org/10.1016/j.jmathb.2004.12.002.

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GRÉGOIRE, ÉRIC, and DU ZHANG. "A FRAMEWORK FOR HANDLING LOGICAL INCONSISTENCIES IN THE FUSION OF BOOLEAN KNOWLEDGE BASES." International Journal of Semantic Computing 05, no. 03 (September 2011): 323–34. http://dx.doi.org/10.1142/s1793351x11001262.

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In this paper, a framework for fusing several Boolean knowledge bases together is presented. The focus is on detecting inconsistencies and overcoming them so that a consistent global knowledge base is obtained. The framework is based on two cornerstones: detecting inconsistencies using algorithmic techniques to compute minimally unsatisfiable sub-formulas, and adopting a logic-based weakening approach to restore consistency for the fused knowledge. The dynamics in the framework in terms of both model-theoretic and the fixpoint semantics is then investigated.

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Griffiths, Catherine. "Computational Visualization for Critical Thinking." Journal of Science and Technology of the Arts 11, no. 2 (December 29, 2019): 9–17. http://dx.doi.org/10.7559/citarj.v11i2.666.

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This paper looks back at historical precedents for how computational systems and ideas have been visualized as a means of access to and engagement with a broader audience, and to develop a new more tangible language to address abstraction. These precedents share a subversive ground in using a visual language to provoke new ways of engaging with about complex ideas. Two new approaches to visualizing algorithmic systems are proposed for the emerging context of algorithmic ethics in society, looking at prototypical algorithms in computer vision and machine learning systems, to think through the meaning created by algorithmic structure and process. The aim is to use visual design to provoke new kinds of thinking and criticality that can offer opportunities to address algorithms in their increasingly more politicized role today. These new approaches are developed from an arts research perspective to support critical thinking and arts knowledge through creative coding and interactive design.

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Biazzo, Stefano, Alberto Fabris, and Roberto Panizzolo. "Virtual Visual Planning: A Methodology to Assess Digital Project Management Tools." International Journal of Applied Research in Management and Economics 3, no. 4 (December 30, 2020): 1–10. http://dx.doi.org/10.33422/ijarme.v3i4.505.

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In contemporary Project Management literature and practice, it is possible to distinguish two paradigms: the algorithmic-rational paradigm and the relational paradigm. The algorithmic-rational paradigm is characterized by a sequence of programming methodologies that constitute the classic corpus of knowledge on Project Management (WBS, CPM, PERT, Gantt diagrams). Following the diffusion of Agile methods, dissatisfaction with the algorithmic-rational paradigm has spread and a Visual Planning approach, based on the decentralization of planning and control and the abandonment of algorithmic techniques (such as CPM and Gantt diagrams) in favour of simpler, visual and physical tools, has become increasingly established. Visual Planning is the concrete manifestation of a relational project management paradigm. In this work, through an analysis of the key practices characterizing Visual Planning, we have identified the five fundamental principles that define this approach to project management. Then, to structure and guide the choice of a software application that can support Visual Planning, we have (1) identified several features which allow distinguishing one software from another, and (2) created a correlation matrix between the core principles of Visual Planning and the software features. Through this matrix, it is possible to evaluate and measure the adherence of project management software applications to the logic and practices of physical Visual Planning.

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Helles, Glennie. "A comparative study of the reported performance of ab initio protein structure prediction algorithms." Journal of The Royal Society Interface 5, no. 21 (December 11, 2007): 387–96. http://dx.doi.org/10.1098/rsif.2007.1278.

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Protein structure prediction is one of the major challenges in bioinformatics today. Throughout the past five decades, many different algorithmic approaches have been attempted, and although progress has been made the problem remains unsolvable even for many small proteins. While the general objective is to predict the three-dimensional structure from primary sequence, our current knowledge and computational power are simply insufficient to solve a problem of such high complexity. Some prediction algorithms do, however, appear to perform better than others, although it is not always obvious which ones they are and it is perhaps even less obvious why that is. In this review, the reported performance results from 18 different recently published prediction algorithms are compared. Furthermore, the general algorithmic settings most likely responsible for the difference in the reported performance are identified, and the specific settings of each of the 18 prediction algorithms are also compared. The average normalized r.m.s.d. scores reported range from 11.17 to 3.48. With a performance measure including both r.m.s.d. scores and CPU time, the currently best-performing prediction algorithm is identified to be the I-TASSER algorithm. Two of the algorithmic settings—protein representation and fragment assembly—were found to have definite positive influence on the running time and the predicted structures, respectively. There thus appears to be a clear benefit from incorporating this knowledge in the design of new prediction algorithms.

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Godler, Yigal, Zvi Reich, and Boaz Miller. "Social epistemology as a new paradigm for journalism and media studies." New Media & Society 22, no. 2 (January 20, 2020): 213–29. http://dx.doi.org/10.1177/1461444819856922.

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Journalism and media studies lack robust theoretical concepts for studying journalistic knowledge generation. More specifically, conceptual challenges attend the emergence of big data and algorithmic sources of journalistic knowledge. A family of frameworks apt to this challenge is provided by “social epistemology”: a young philosophical field which regards society’s participation in knowledge generation as inevitable. Social epistemology offers the best of both worlds for journalists and media scholars: a thorough familiarity with biases and failures of obtaining knowledge, and a strong orientation toward best practices in the realm of knowledge-acquisition and truth-seeking. This article articulates the lessons of social epistemology for two central nodes of knowledge-acquisition in contemporary journalism: human-mediated knowledge and technology-mediated knowledge.

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Rozov, K. V. "THE DEVELOPMENT OF ALGORITHMIC CULTURE AND PROGRAMMING CULTURE OF STUDENTS IN PROFILE CLASSES WHILE STUDING THE BASIS OF PROGRAMMING IN C++." Informatics in school, no. 6 (October 10, 2020): 24–33. http://dx.doi.org/10.32517/2221-1993-2020-19-6-24-33.

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The article presents the structure, content and results of approbation of the C++ programming course developed for the 10th grade students of physics and mathematics profile and implemented as part of the academic subject “Informatics”. The aim of the course is to develop in the student not only knowledge and skills in programming, but also his algorithmic culture and programming culture as important qualities of a potential IT-specialist. This is facilitated by special control of educational process by the teacher, which consists in monitoring the activities of students in writing programs and timely correction of this activity. The assessment of the level of development of student algorithmic culture and programming culture relative to the basic level of their formation (when mastering the basics of algorithmization and programming in the 9th grade) was carried out on the basis of a number of criteria presented in the article. The results of approbation showed that the specially organized teacher activity makes it possible to increase the level of algorithmic culture and programming culture of high school students when studying the basics of programming in C++.

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Holme, Thomas, and Kristen Murphy. "Assessing Conceptual and Algorithmic Knowledge in General Chemistry with ACS Exams." Journal of Chemical Education 88, no. 9 (September 2011): 1217–22. http://dx.doi.org/10.1021/ed100106k.

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Rouse, W. B., J. M. Hammer, and C. M. Lewis. "On capturing human skills and knowledge; algorithmic approaches to model identification." IEEE Transactions on Systems, Man, and Cybernetics 19, no. 3 (1989): 558–73. http://dx.doi.org/10.1109/21.31062.

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Baltacı, Serdal, Avni Yıldız, and Bülent Güven. "Knowledge Types Used by Eighth Grade Gifted Students While Solving Problems." Bolema: Boletim de Educação Matemática 28, no. 50 (December 2014): 1032–55. http://dx.doi.org/10.1590/1980-4415v28n50a02.

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This study aims to determine how primary school eighth grade (14 years old) gifted students use knowledge types while solving problems. In the context, the data were collected through clinical interviews conducted with three gifted students. The students’ voice recordings during problem solving and the solutions they wrote on the paper formed the data of the study. We found out that gifted students use more algorithmic knowledge and less schema knowledge in the problems that they had to solve. It can be said that the reduced usage of schema knowledge is likely to be a result of the fact that the gifted students produce different solutions using the field knowledge instead of remembering the schemas of similar problems they have encountered before.

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Journal articles on the topic 'Algorithmic knowledge'

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