Algorithmic Literacy and the Role for Libraries

Ridley, Michael; Pawlick-Potts, Danica

doi:10.6017/ital.v40i2.12963

Cited by 40 publications

(24 citation statements)

References 21 publications

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“…30 Libraries have a key role in advancing algorithmic literacy in their communities. 31 Just as libraries championed information literacy through the promulgation of standards and principles, the provision of diverse educational programming, and the engagement of the broad academic community, so too can libraries be central to efforts to enhance algorithmic literacy. Second is a requirement that XAI must be sensitive to the abilities and needs of different users.…”

Section: Prerequisites To An Xai Strategymentioning

confidence: 99%

Explainable Artificial Intelligence (XAI)

Ridley

2022

ITAL

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The field of explainable artificial intelligence (XAI) advances techniques, processes, and strategies that provide explanations for the predictions, recommendations, and decisions of opaque and complex machine learning systems. Increasingly academic libraries are providing library users with systems, services, and collections created and delivered by machine learning. Academic libraries should adopt XAI as a tool set to verify and validate these resources, and advocate for public policy regarding XAI that serves libraries, the academy, and the public interest.

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Section: Prerequisites To An Xai Strategymentioning

confidence: 99%

Explainable Artificial Intelligence (XAI)

Ridley

2022

ITAL

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“…En especial, se centra en las formas de gobernanza (Danaher et al, 2017), resistencia (Treré, 2019) y agenciamiento (Velkova & Kaun, 2021) algorítmicos. Además, se vincula el tema con las alfabetizaciones digitales críticas (Garay Cruz & Hernández Gutiérrez, 2019) y la literacidad transmedia (Scolari, 2016), en particular con la literacidad algorítmica (Ridley & Pawlick-Potts, 2021).…”

Section: Antecedentesunclassified

“…Este trabajo introduce un tipo específico de literacidad transmedia (Scolari, 2016;Lugo Rodríguez, 2016;Cruz Sánchez, 2019) que recientemente se ha denominado literacidad algorítmica (Ridley & Pawlick-Potts, 2021). Derivado del análisis presentado, hacia el final de este trabajo se describen las habilidades que conforman la literacidad algorítmica.…”

Section: Introductionunclassified

Entrenar al algoritmo: gobernanza, agencia y literacidad en el uso de YouTube

Sued

2022

Contratexto

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Este estudio aborda las experiencias de jóvenes usuarios mexicanos con los algoritmos de recomendación de la plataforma YouTube. Busca determinar si se encuentran subordinados a la gobernanza algorítmica o si, por el contrario, son capaces de desarrollar algunas tácticas para resistir las lógicas del poder algorítmico a través de su propia agencia. Utiliza una metodología cualitativa centrada en grupos de enfoque. Evidencia que los usuarios no se subordinan completamente a las plataformas, y que sus posibilidades de agenciamiento varían en función de sus diferentes modos de apropiación tecnológica, las teorías intuitivas acerca de su funcionamiento, la capacidad para evadir las distorsiones algorítmicas, y los recursos para evaluar la calidad de la información ofertada. Como resultado del análisis, se han identificado las habilidades específicas que constituyen la literacidad algorítmica.

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“…However, there is not yet a well-defined role for libraries in other activities defined in some national AI plans such as algorithmic literacy. In part, this can be attributed to a lack of clear definitions of algorithmic literacy and somewhat limited examples of implementation in libraries to date (Ridley & Pawlick-Potts, 2021). Other findings also indicate the potential of training, rather than instances where training is already taking place (Hervieux & Wheatley, 2021) However, expectations for librarians to have some knowledge of AI and machine learning like ALIA's will necessitate learning within the profession, and opportunities for recognition of library activities in higher level plans.…”

Section: Future Directions For Libraries and Aimentioning

confidence: 99%

Representation of Libraries in Artificial Intelligence Regulations and Implications for Ethics and Practice

Bradley

2022

Journal of the Australian Library and Information Association

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We are already living in an algorithmic society. AI policies and regulations are now emerging at the same time as more is learned about the implications of bias in machine learning sets, the surveillance risks of smart cities and facial recognition, and automated decision-making by government, among many other applications of AI and machine learning. Each of these issues raises concerns around ethics, privacy, and data protection. This paper introduces some of the key AI regulatory developments to date and engagement by libraries in these processes. While many AI applications are largely emergent and hypothetical in libraries, some mature examples can be identified in research literature searching, language tools for textual analysis, and access to collection data. The paper presents a summary of how library activities such as these are represented in national AI plans and ways that libraries have engaged with other aspects of AI regulation including the development of ethical frameworks. Based on the sector's expertise in related regulatory issues including copyright and data protection, the paper suggests further opportunities to contribute to the future of ethical, trustworthy, and transparent AI. Navigating AI definitions, applications, and challengesVarying definitions of artificial intelligence have emerged over the decades. These definitions are summarised as being concerned with systems that think like humans, act like humans, think rationally, and act rationally (Russell & Norvig, 2020). Yet there is no clear consensus among researchers on a particular definition, and AI thus remains somewhat difficult to define (Bringsjord & Govindarajulu, 2020). This is further complicated by the emergence of AI regulation which has spurred the creation of additional policy-focused definitions that differ from those preferred by AI researchers. This has consequences for developing a shared understanding of what AI is, and for developing effective regulation. In a recent study, researchers centre system and technical elements in their definitions, while policymakers focus on how systems compare to human thought or behaviour (Krafft et al., 2020). Krafft suggests that the OECD's policy-focused definition effectively reaches across the domains of research and policy and this definition also frames this paper, "An AI system is a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing

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Algorithmic Literacy and the Role for Libraries

Cited by 40 publications

References 21 publications

Explainable Artificial Intelligence (XAI)

Explainable Artificial Intelligence (XAI)

Entrenar al algoritmo: gobernanza, agencia y literacidad en el uso de YouTube

Representation of Libraries in Artificial Intelligence Regulations and Implications for Ethics and Practice

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