{"product_id":"systemic-bias-algorithms-and-society-9781032002576","title":"Systemic Bias: Algorithms and Society","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eSystemic Bias: Algorithms and Society explores computational bias in cultural works, tech culture, and workplace psychometrics, examining how human biases impact data models and proposing strategies to overcome bias. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 72 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 25 September 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eSystemic Bias: Algorithms and Society delves into the intricate realm of computational bias, exploring its pervasive presence in various contexts. It examines the challenges posed by algorithmic bias in cultural works, the metaphors of magic and mathematics in tech culture, and the realm of workplace psychometrics. The output of computational models is intricately linked to not only their inputs but also the underlying relationships and assumptions embedded in their model design. These assumptions often stem from social and cultural factors rather than purely physical or mathematical considerations. Consequently, human biases inevitably find their way into these data models, raising important questions about their impact and potential mitigation strategies.\u003cbr\u003e\u003cbr\u003eTo address this critical issue, scholars and students from diverse backgrounds, including Communication, Art, and New Media, come together in a multidisciplinary pursuit of understanding algorithmic bias. This research encompasses a wide range of perspectives, methodologies, and tools to unravel the complexities of algorithmic bias. By integrating insights from these various fields, researchers aim to develop novel strategies and approaches to mitigate bias in computed products and promote fairness and equity in society.\u003cbr\u003e\u003cbr\u003eOne key area of exploration is the examination of how human biases manifest in algorithmic systems. Researchers investigate the mechanisms through which societal norms, cultural beliefs, and social structures influence the development and deployment of algorithms. They analyze the data used to train these systems, identifying potential biases and exploring ways to mitigate them. For instance, some studies have shown that algorithmic bias can perpetuate existing social inequalities, such as discrimination against marginalized groups. By recognizing and addressing these biases, researchers aim to create more inclusive and equitable algorithms that serve the needs of all individuals.\u003cbr\u003e\u003cbr\u003eAnother important aspect of the study is the exploration of new strategies to overcome bias in computed products. This involves developing and implementing algorithms that are more transparent, accountable, and robust. Researchers explore techniques such as fairness-aware training, which involves training algorithms on diverse datasets to mitigate bias. They also investigate the use of machine learning algorithms that can learn from human feedback and improve over time, reducing the likelihood of bias.\u003cbr\u003e\u003cbr\u003eIn addition to academia, policymakers, journalists, and the general reading public also play a crucial role in addressing algorithmic bias. By raising awareness about the potential impacts of biased algorithms, they can advocate for policies and regulations that promote fairness and transparency in the development and deployment of computational systems. This includes the implementation of ethical guidelines, the use of independent oversight mechanisms, and the promotion of diversity and inclusion in the tech industry.\u003cbr\u003e\u003cbr\u003eSystemic Bias: Algorithms and Society serves as a valuable resource for scholars, students, policymakers, and the broader public. It provides a comprehensive and interdisciplinary approach to understanding algorithmic bias, offering insights into its origins, manifestations, and potential solutions. By fostering collaboration and dialogue across different disciplines, the study aims to contribute to the development of a more equitable and inclusive digital society.\u003cbr\u003e\u003cbr\u003eIn conclusion, algorithmic bias is a complex and pervasive issue that requires a multidisciplinary approach to address. By examining the relationships between computational models, human biases, and social and cultural factors, researchers can develop innovative strategies to mitigate bias and promote fairness in society. Policymakers, journalists, and the general public also play a vital role in raising awareness, advocating for policies, and promoting transparency in the development and deployment of computational systems. Together, we can work towards a future where algorithms are designed and implemented with the utmost care, consideration, and respect for the values and needs of all individuals.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 126g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 138 x 216 x 8 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032002576\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44599445881082,"sku":"9781032002576","price":19.98,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1696007985610_book.jpg?v=1696329051","url":"https:\/\/shulphink.com\/products\/systemic-bias-algorithms-and-society-9781032002576","provider":"Shulph Ink","version":"1.0","type":"link"}