TOK EXHIBITION Object 1: Google’s PageRank Patent Document
- Theme: Knowledge and Technology
- Specific Example: The patent for Google’s PageRank algorithm, foundational to its search engine technology, exemplifies how algorithmic biases can shape access to information online. This document can be analyzed to understand the criteria used for ranking web pages, highlighting the built-in biases that affect which knowledge becomes prominent. Google’s search algorithm stands as a modern testament to the challenges of bias in the digital age. It shapes the information landscape, influencing what knowledge is readily accessible versus what remains obscured. This algorithm, by prioritizing certain sites based on complex, proprietary criteria, inadvertently embeds biases into the fabric of digital knowledge dissemination. It prompts examination of how technological tools, while designed to enhance access to knowledge, can also reflect and reinforce existing societal biases, raising critical questions about the neutrality of technology in knowledge production.
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TOK EXHIBITION Object 2: “Invisible Women: Data Bias in a World Designed for Men” by Caroline Criado Perez
- Theme: Knowledge and the Knower
- Specific Example: This book investigates gender bias in data collection and analysis across various sectors, including medicine, transportation, and technology. It serves as a tangible example of how gender bias in scientific research and data analysis can lead to knowledge that overlooks or misrepresents half of the population’s needs and experiences. Studies highlighting gender bias in scientific research, such as those examining the underrepresentation of women in clinical trials, underscore the systemic biases that can influence knowledge production in the sciences. These studies reveal how assumptions and norms within the scientific community can shape research questions, methodologies, and interpretations, potentially skewing findings and conclusions. This object encourages discussion on the implications of such biases for the reliability of scientific knowledge and the importance of reflexivity and diversity in mitigating bias.