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Abstract

Purpose Belkin and Robertson (1976a) reflected on the ethical implications of theoretical research in information science and warned that there was potential for abuse of knowledge gained by undertaking such research and applying it to information systems. In particular, they identified the domains of advertising and political propaganda that posed particular problems. The purpose of this literature review is to revisit these ideas in the light of recent events in global information systems that demonstrate that their fears were justified. Design/methodology/approach The authors revisit the theory in information science that Belkin and Robertson used to build their argument, together with the discussion on ethics that resulted from this work in the late 1970s and early 1980s. The authors then review recent literature in the field of information systems, specifically information retrieval, social media and recommendation systems that highlight the problems identified by Belkin and Robertson. Findings Information science theories have been used in conjunction with empirical evidence gathered from user interactions that have been detrimental to both individuals and society. It is argued in the paper that the information science and systems communities should find ways to return control to the user wherever possible, and the ways to achieve this are considered. Research limitations/implications The ethical issues identified require a multidisciplinary approach with research in information science, computer science, information systems, business, sociology, psychology, journalism, government and politics, etc. required. This is too large a scope to deal with in a literature review, and we focus only on the design and implementation of information systems (Zimmer, 2008a) through an information science and information systems perspective. Practical implications The authors argue that information systems such as search technologies, social media applications and recommendation systems should be designed with the recipient of the information in mind (Paisley and Parker, 1965), not the sender of that information. Social implications Information systems designed ethically and with users in mind will go some way to addressing the ill effects typified by the problems for individuals and society evident in global information systems. Originality/value The authors synthesize the evidence from the literature to provide potential technological solutions to the ethical issues identified, with a set of recommendations to information systems designers and implementers.

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Abstract

Recent technological developments have increased the use of machine learning to solve many problems, including many in information retrieval. Multimedia information retrieval as a problem represents a significant challenge to machine learning as a technological solution, but some problems can still be addressed by using appropriate AI techniques. We review the technological developments and provide a perspective on the use of machine learning in conjunction with knowledge organization to address multimedia IR needs. The semantic gap in multimedia IR remains a significant problem in the field, and solutions to them are many years off. However, new technological developments allow the use of knowledge organization and machine learning in multimedia search systems and services. Specifically, we argue that, the improvement of detection of some classes of lowlevel features in images music and video can be used in conjunction with knowledge organization to tag or label multimedia content for better retrieval performance. We provide an overview of the use of knowledge organization schemes in machine learning and make recommendations to information professionals on the use of this technology with knowledge organization techniques to solve multimedia IR problems. We introduce a five-step process model that extracts features from multimedia objects (Step 1) from both knowledge organization (Step 1a) and machine learning (Step 1b), merging them together (Step 2) to create an index of those multimedia objects (Step 3). We also overview further steps in creating an application to utilize the multimedia objects (Step 4) and maintaining and updating the database of features on those objects (Step 5).