Creative Collaboration with the “Brain” of a Search Engine: Effects on Cognitive Stimulation and Evaluation Apprehension

Gozzo, Mélanie; Woldendorp, Michiel Koelink; Rooij, Alwin de

doi:10.1007/978-3-030-95531-1_15

Cited by 3 publications

(2 citation statements)

References 42 publications

(82 reference statements)

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“…The tools make use of natural language processing and unlike a conventional search engine, map to synonyms and related concepts, and link these synonyms and concepts to literature (Kricka et al, 2020;Polonioli, 2020). They harvest the power of neural networks, which are invaluable in identifying trends and novel associations between the concepts in a search query, which can both contribute to innovation and facilitate human understanding (Gozzo et al, 2022;Kricka et al, 2020). Time is something AI-search tool developers and searchers assign great value to, as discussed in Zhang et al (2022).…”

Section: Introductionmentioning

confidence: 99%

Reflections on tests of AI-search tools in the academic search process

Wildgaard,

Vils,

Sandal Johnsen

2023

LIBER

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Academic search literacy and artificial intelligence (AI) search are a strategic focus of future researcher support strategies at the Royal Library and affiliated university libraries in Denmark. The ambition is to integrate AI search tools in teaching and services that support literature seeking and hence improve the efficiency of the academic search process. This paper is a reflection on the results of tests of AI powered search tools conducted at the Royal Library, Denmark. Information specialists and researchers took part in think-aloud tests, Hackathon and expert quality assessment in the period of April 2021 – February 2022. Our observations point to a) opportunities in AI search to let go of traditional approaches to search and broaden our perception of how an academic search can be conducted, b) potential of AI search interfaces to challenge ones preconception and reduce cognitive bias in the search process, c) concerns about the quality of scientific literature AI search identifies, and d) barriers that need to be overcome before practical implementation of Ai search tools become viable in academic searches. More research is needed to show the usefulness of AI search tools in systematic search and guidance on how to report the use of them

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Section: Introductionmentioning

confidence: 99%

Reflections on tests of AI-search tools in the academic search process

Wildgaard,

Vils,

Sandal Johnsen

2023

LIBER

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“…Artificial intelligence (AI) has the potential to support the artistic process in new and unexpected ways [7]. AI can be used to gather, categorize, generate, and evaluate images and other data in ways that differ from, and in some ways exceed, human capabilities, due to the vast amounts of data these technologies can process [13]. However, the potential of AI for the artistic process also remains ambiguous [5].…”

Section: Introductionmentioning

confidence: 99%

Articulating (Uncertain) AI Futures of Artistic Practice: A Speculative Design and Manifesto Sprint Approach

Ashby

Hanna

Rooij

et al. 2023

Creativity and Cognition

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AI is rapidly becoming enmeshed in our professional and private lives. The ubiquity of such technologies raises a host of ethical questions, value clashes, and unforeseen consequences that must be confronted. Developments such as Ai-Da and DALL-E 2 are exciting in that they present robust new capabilities in AI and creativity. However, the futures such technologies unlock are also unpredictable. Given the speed with which such technologies are emerging and becoming adopted, the need to engage target audiences to weigh in on possible AI futures is critical. Our pilot project, Artistic Process Futures and AI, seeks to explore the role and potential implications of AI technologies with artists. In this paper, we show how participatory speculative design processes might be channeled into a public statement, or manifesto, regarding possible and preferable AI futures for supporting the artistic process, and how our workshop exposed uncertainty at the core of such deliberation. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; Interaction design process and methods; Empirical studies in HCI; Participatory design;

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The general attitudes towards artificial intelligence (GAAIS): A meta-analytic reliability generalization study

Şahin,

Yıldırım

2024

International Journal of Assessment Tools in Education

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This study aims to generalize the reliability of the GAAIS, which is known to perform valid and reliable measurements, is frequently used in the literature, aims to measure one of today's popular topics, and is one of the first examples developed in the field. Within the meta-analytic reliability generalization study, moderator analyses were also conducted on some categorical and continuous variables. Cronbach's α values for the overall scale and the positive and negative subscales, and McDonald's ω coefficients for positive and negative subscales were generalized. Google Scholar, WOS, Taylor & Francis, Science Direct, and EBSCO databases were searched to obtain primary studies. As a result of the screening, 132 studies were found, and these studies were reviewed according to the inclusion criteria. Reliability coefficients obtained from 19 studies that met the criteria were included in the meta-analysis. While meta-analytic reliability generalization was performed according to the random effects model, moderator analyses were performed according to the mixed effect model based on both categorical variables and continuous variables. As a result of the research pooled, Cronbach's α was 0.881, 0.828, and 0.863 for total, the negative, and positive subscales respectively. Also, McDonald's ω was 0.873 and 0.923 for negative and positive subscales respectively. It was found that there were no significant differences between the reliability coefficients for all categorical variables. On the other hand, all continuous moderator variables (mean age, standard deviation age, and rate of female) had a significant effect.

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Creative Collaboration with the “Brain” of a Search Engine: Effects on Cognitive Stimulation and Evaluation Apprehension

Cited by 3 publications

References 42 publications

Reflections on tests of AI-search tools in the academic search process

Reflections on tests of AI-search tools in the academic search process

Articulating (Uncertain) AI Futures of Artistic Practice: A Speculative Design and Manifesto Sprint Approach

The general attitudes towards artificial intelligence (GAAIS): A meta-analytic reliability generalization study

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