Digital Libraries for People: Ethical Design, Adaptive Exploration, Analytical Support
Back in 2003, in a paper on digital library research developments and trends I suggested that collaborative digital work environments, social digital navigation, and new forms of digital environments for academic, educational, publishing, and recreational purposes could be viewed among the future digital library research and development directions. While these areas are still relevant and thriving, there are new and emerging trends in data science, information science, information retrieval, and artificial intelligence which have influenced and continue to influence our thinking and the ways in which we design and evaluate digital libraries.
—There are new and emerging trends in data science, information science, information retrieval, and artificial intelligence which have influenced and continue to influence our thinking—
Confluence of Information Science, Information Retrieval, and Data Science — A number of recent papers have explored and envisioned the future of information retrieval systems and digital libraries. In a SIGIR workshop titled BIRDS: Bridging the Gap between Information Science (IS), Information Retrieval (IR) and Data Science (DS), Frommholz et al. (2020) present a visual model of how Information Science, Information Retrieval and Data Science can complement each other by applying a more holistic approach to these disciplines that go beyond traditional domains (Figure 1). What is particularly interesting in the visual model is that digital libraries and document repositories are viewed as one facet within data science. Designing for People — Belkin (2020) argues that we need to support people not users and that information interaction is the foundation for “supporting people in achieving their goals, accomplishing their tasks, through effective (and pleasurable) interaction with information and/or Data. He also proposes radical personalization of information interaction and its ethical challenges and argues for collaborative and interdisciplinary methods, frameworks, and teams to develop systems that would support people. Adaptive Personalization — Fox in his 2020 Joint Conference on Digital Libraries keynote calls for the development of a “formal approach that will enable adaptive self-organization and tailored exploration” and stresses the importance of collaboration and AI-based optimizations and solutions. Ethical AI — In the last few years, many private corporations such as Google, Facebook, Axon, Amazon, IBM, and Microsoft have launched AI ethics boards. These corporations, in addition to AI ethics research institutes at Harvard, Stanford, and MIT, have faced backlash for the lack of diversity in their membership (Levin, 2019). Researchers argue for standardizing ethical design (Bryson & Winfield, 2017). One example is the IEEE Ethically Aligned Design (Shahriari, K. & Shahriari, M., 2017) that provides a vision and a set of guidelines to prioritize human wellbeing within artificial intelligence and autonomous systems usage, and personal data and individual access control. In December 2020, ASIS&T, ALISE, and the iSchools released a Statement on AI ethics and the contributions of diverse voices in the discussion. These statements reflect a social responsibility to advance rigorous scholarship and practice in the face of the prolific contributions to a topic that has captured the attention of the global academic enterprise, the information professions, and intercultural society (Huang, Samek, Shiri, 2021).
In envisioning the future landscape of digital library research and practice, I will draw upon the above research and development to particularly emphasize the importance of collaboration and interdisciplinary research work in order to meet the challenges of design and evaluation of responsible, ethically-informed, and AI-enabled digital libraries. Although AI applications and machine learning methods are not new to the digital library community, the ethical, inclusive, and people-oriented digital libraries are yet to be conceptualized, designed and implemented. I am proposing a revised version of the BIRDS model of relationships of IS, IR and DS (Figure 2) to show a) the place for digital library research in the model and b) to provide a holistic perspective of the way in which adaptive, ethical, and analytically-enabled research, development and practice could be imagined. The proposed revised model includes digital libraries as an interdisciplinary domain that has links with IS, IR, and DS and shows an overarching set of design challenges for the future of digital library research and practice.
Digital Library Design Challenge Areas
- Ethical design of privacy-aware digital libraries. This includes not only content creation and digitization for marginalized and underrepresented communities, but also the design of features that would support people in exercising control over their personal data/information and their information search and interaction behavior data.
- Consideration of ethical principles of privacy, confidentiality, security, transparency, and data protection.
- Design of digital libraries that would provide easy to use and easy to learn visualization and analytical functionalities for people in order to support their data/information exploration, navigation, and usage, and ultimately everyday problem solving.
- Design of personalized, adaptive, and AI-enabled functionalities that would support content exploration, retrieval, use, and reuse of digital objects in new and different ways. This will include popularizing machine learning and data mining functionalities that people can use to enhance their sense-making of and interaction with data and information.
This article is based on a presentation made at the 2021 Joint Conference on Digital Libraries Workshop on the Future of Digital Libraries.
Belkin, Nicholas J. “Challenges and Opportunities for IS, IR & DS in an Era of Information Ubiquity.” In BIRDS@ SIGIR, p. 5. 2020.
Bryson, J., & Winfield, A. (2017). Standardizing ethical design for artificial intelligence and autonomous systems. Computer, 50(5), 116-119.
Fox, E. A. (2020, August). How Should One Explore the Digital Library of the Future?. In Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020 (pp. 1-2).
Frommholz, I., Liu, H., & Melucci, M. (2020, July). BIRDS-bridging the gap between information science, information retrieval and data science. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2455-2458).
Huang, C., Samek, T., Shiri, A. (2021) AI and Ethics: Ethical Perspectives for LIS. Journal of Education for Library and Information Science. Published online August 12, 2021.
Levin, S. (2019). “Bias deep inside the code”: the problem with AI “ethics” in Silicon Valley. The Guardian. Retrieved from https://www.theguardian.com/technology/2019/mar/28/big-tech-ai-ethics-boards-prejudice
Shahriari, K., & Shahriari, M. (2017, July). IEEE standard review—Ethically aligned design: A vision for prioritizing human wellbeing with artificial intelligence and autonomous systems. In 2017 IEEE Canada International Humanitarian Technology Conference (IHTC) (pp. 197-201). IEEE.
Shiri, A. (2003). Digital library research: current developments and trends. Library review.
Cite this article in APA as: Shiri, A. (2022, March 24). Digital libraries for people: Ethical design, adaptive exploration, analytical support. Information Matters, Vol. 2, Issue 3. https://informationmatters.org/2022/03/digital-libraries-for-people-ethical-design-adaptive-exploration-analytical-support/