Conference Agenda

Yuval Harari proposes the dystopian view that an algorithm can understand us and our thoughts and feelings better than our mothers, without us even recognising that this is happening, and that this can lead to a threat to democracy (Harari in Thompson, 2018). Questions of responsibility for overcoming the power vested in technologies abound in the literature, with calls for regulation by technology companies and by nation-states through legislation. Although many people are resigned to the unregulated media environment, informed citizens can also take on some responsibility, through maintaining a high level of digital literacy. As Henninger (2021) notes, this is not new information. Lloyd (2019) calls for information literacy scholars and librarians to consider how they address the impact of algorithms on everyday activities. This study aims to heed this call, drawing on accounts of the information literacy practices of librarians.

Objectives

Algorithms influence our online interactions and have real impacts on individuals and on society, in ways that are rarely apparent and which can be detrimental to a democratic society. Librarians claim to have a significant responsibility for developing information and digital literacies, through which a level of algorithmic literacy might develop, but little is known about the professional processes through which they achieve this. The purpose of this study is to position the development of algorithmic literacy in the context of an inclusive and democratic society.

Methodology

Using a practice theory approach, this study has interviewed more than twenty academic librarians who provide programs and services in information literacy services to university students in New South Wales, Australia, in order to identify how they talk about these processes and interactions (Schatzki 2012). The transcripts of the interviews, as well as resources relevant to their practices, were analysed using thematic analysis to identify elements of algorithmic and digital literacies, considerations of democratic practices, active citizenship and wider societal implications.

Outcomes

There was little evidence of a focus on algorithmic culture. Librarians’ understanding of algorithmic literacy ranged from the naïve to passive acquaintance especially through social media, with few claiming conceptual or practical expertise. Perceptions of the relationship between information and digital literacies and active citizenship were influenced by the ethos of the university, presenting a fragmented perspective on the role of these literacies. Responsibilities for regulating the effects of algorithms on citizens in their everyday lives were mostly seen to lie beyond the scope of librarians, vested in government, in technology companies and the institutions of education from earliest childhood. Taken together, these factors are likely to weaken further the position of librarians as arbiters of authoritative sources of information in a society.

References

Thompson, N. (2018). When tech knows you better than you know yourself: Yuval Noah Harari and Tristan Harris interviewed by Wired. [Video]. Retrieved from https://www.wired.com/story/artificial-intelligence-yuval-noah-harari-tristan-harris/

Henninger, M. (2021). Information literacy: Importance and consequences. Philippine Journal of Librarianship and Information Studies, 41(2), 3–12. Retrieved from https://phjlis.org/index.php/phjlis/article/view/82/67

Lloyd, A. (2019). Chasing Frankenstein’s monster: Information literacy in the black box society. Journal of Documentation, 75(6), 1475–1485. https://doi.org/10.1108/JD-02-2019-0035

Schatzki, T. R. (2012). A primer on practices: Theories and research. In J. Higgs, et al. (Eds.), Practice-Based Education: Perspectives and Strategies, (pp. 13–26) Rotterdam: Springer.

The widespread use and impact of algorithms on almost every aspect of the individual and society is a significant challenge to the modern world. For effective and informed functioning in today’s societies, we need to develop algorithmic literacy (Iwasiński & Furman, 2022). So far there have been several studies aimed at defining and operationalizing this notion, but only few at developing standardized measures of algorithmic literacy (Latzer et al., 2020). In 2022 Dogruel, Masur, and Joeckel (Dogruel et al., 2022) constructed and validated a 22-item scale for measuring algorithmic literacy. It consists of two interrelated dimensions: awareness of algorithms use (11 items), and knowledge about algorithms (11 items). The first dimension relates to the awareness of the purposes for which algorithms are being used and awareness of areas and applications or devices, in which algorithms are actually used. The second dimension focuses on a more advanced understanding of the mechanisms of action of algorithmic systems and their consequences. The correlation between results in both dimensions, and the practical ability to interact with algorithms has been confirmed.

In our study, we apply this scale to measure and compare the algorithmic literacy of Polish students of several faculties. We also want to test the scale in the Polish context. Authors of the scale declare: “our original scale was developed in German (...) Items worked in the context of our study, but item length or use of words to increase or decrease item difficulty might be critical in other languages”. Our pilot research indicated that respondents had trouble understanding the intentions behind some of the items.

Our research has two main goals:

• Testing the scale in the Polish context

• Assessing algorithmic literacy among Polish students of selected faculties.

We regard our research as exploratory. Our sample is purposive. We have selected courses from Polish universities, which are available to us, and as we assume, include some form of algorithmic education in their curricula. These are: Architecture of Information Spaces at the University of Warsaw, Sociology of Media and Communication at the University of Warsaw, and Philosophy of New Media at the University of Silesia. All students of the last (third) year will be studied. We also intend to check if the items are understandable, using interviews. Moreover, we plan to study and compare the syllabuses of the above programmes, to find out if they include courses that sensitize students to the knowledge of algorithms.

We adopted two working hypotheses:

1. Not all items in the questionnaire are clear and understandable to our respondents.

2. Students of different faculties have different levels of algorithmic literacy.

The study combines elements of quantitative analysis (Algorithmic Literacy Scale) and qualitative analysis (interviews with students, sylabuses analysis). This is, to our knowledge, the first empirical research on algorithmic literacy in Poland. Furthermore, we are not aware of any other studies that use the scale developed by Dogruel, Masur, and Joeckel worldwide.

References

Dogruel, L., Masur P., & Joeckel, S. (2022) Development and validation of an algorithm literacy scale for internet users. Communication Methods and Measures, 16(2).

Iwasiński, Ł., & Furman, W. (2022). Jak być świadomym użytkownikiem algorytmów? O potrzebie rozwijania kompetencji algorytmicznych. Zagadnienia Informacji Naukowej, 2.

Latzer, M., Festic, N., & Kappeler, K. (2020). Awareness of algorithmic selection and attitudes in Switzerland. Report 2 from the project: The significance of algorithmic selection for everyday life: The case of Switzerland. University of Zurich.

Generative artificial intelligence tools such as ChatGPT are transforming how people interact with information, with significant implications for information literacy. Using ChatGPT and similar tools as information retrieval challenges many core ideas of information literacy, as it generates often quite adequate topic overviews, while claiming neither copyright nor any authority other than having been trained on a huge corpus of texts.

While this disruption is unique, it is not unprecedented. Twenty-five years ago, general purpose web search engines blurred formats and authorship on the Web, which itself had just reached a critical mass to make it a worthwhile starting point for general information needs. A few years later, Wikipedia explicitly challenged traditional notions of expertise. How librarians, and others interested in information literacy, responded to these tools, both in terms of how they thought about they discussed them among themselves and how they addressed them while teaching information literacy, can help us anticipate and understand our reactions to the use of AI today.

In this paper, I review the historical scholarly and trade literature, as well as less formal sources such as social media and email listservs, for discussions of Wikipedia, Google, and earlier dominant search engines as new tools that impact information literacy, looking for themes and approaches that might inform our response to ChatGPT and similar tools.

Broadly speaking, early analysis shows three broad categories of responses:

• Reinforcing, in other words, incorporating Wikipedia and Google into the pre-existing models of information behavior. For example, presenting Wikipedia as an encyclopedia that you might use to initially learn about a topic, but would not cite as a source.

• Rejecting or taking the stance that Google or Wikipedia are not appropriate tools and should not be used. For example, emphasizing the questionable quality of information in these sources.

• Revolutionizing or exploiting features of the tool that allow for new ways of engaging with information literacy. For example, presenting editing Wikipedia as a low stakes opportunity for learners to engage with concepts of scholarship as conversation, authority, and so on.

I discuss the strengths and weaknesses of all three responses, considering both the benefits of hindsight as well as the implications for how we approach artificial intelligence and other future disruptive tools.