Information retrieval

Original

Through a Filtered Lens: How Information Retrieval Bias Shapes Users’ Information Consumption

Everyone is interacting with information systems to access, retrieve, and subsequently use information for diverse purposes. What if the information we are consuming to make life-staking decisions has been filtered by an invisible hand? Like the lens of a camera, the invisible hand filters what information we receive, decides for us what is most relevant to our search queries, what is emphasized in our search results, and the ranking order of the information we receive. Unfortunately, this invisible hand is with a “closed fist” (devoid of openness, clarity, and understanding) and is highly subjective.

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FeaturedTranslation

Exploring the Impact of Artificial Intelligence on Information Retrieval Systems

The study aims to comprehensively explore the impact of artificial intelligence (AI) on information retrieval systems, analysing the evolution, challenges, and future directions. It explores the role of AI in enhancing search relevance, user experience, and ethical considerations in information retrieval contexts. The findings highlight AI’s transformative capabilities in enhancing relevance, personalisation, and semantic understanding within information retrieval systems. Ethical considerations, such as bias mitigation and data privacy, are also addressed.

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