The tech industry thrives on innovation and disruption. Yet ageism remains a prime concern, and tech professionals over 50, a demographic brimming with experience and wisdom, often face significant hurdles in their careers. Layoffs, lower pay, and an undercurrent of bias can make it feel like the industry they helped build is pushing them out.

"Canada's colonial history continues to have a devastating impact on Indigenous peoples and communities. Decolonizing Data explores how ongoing structures of colonialization negatively impact the well-being of Indigenous peoples and communities across Canada, resulting in persistent health inequalities. In addressing the social dimensions of health, particularly as they affect Indigenous peoples and BIPOC communities, Decolonizing Data asks, should these groups be given priority for future health policy considerations? Decolonizing Data provides a deeper understanding of the social dimensions of health as applied to Indigenous peoples, who have been historically underfunded in and excluded from health services, programs, and quality of care; this has most recently been seen during the COVID-19 pandemic. Drawing on both Western and Indigenous methodologies, this unique scholarly contribution takes a sociological perspective, as well as the "two-eyed seeing" approach to research methods. By looking at the ways that everyday research practices contribute to the colonization of health outcomes for Indigenous peoples, Decolonizing Data exposes the social dimensions of healthcare, and offers a careful and respectful reflection on how to "unsettle conversations" about applied social research initiatives for our most vulnerable groups."--

From everyday apps to complex algorithms, Ruha Benjamin cuts through tech-industry hype to understand how emerging technologies can reinforce White supremacy and deepen social inequity. Benjamin argues that automation, far from being a sinister story of racist programmers scheming on the dark web, has the potential to hide, speed up, and deepen discrimination while appearing neutral and even benevolent when compared to the racism of a previous era. Presenting the concept of the "New Jim Code," she shows how a range of discriminatory designs encode inequity by explicitly amplifying racial hierarchies; by ignoring but thereby replicating social divisions; or by aiming to fix racial bias but ultimately doing quite the opposite. Moreover, she makes a compelling case for race itself as a kind of technology, designed to stratify and sanctify social injustice in the architecture of everyday life. This illuminating guide provides conceptual tools for decoding tech promises with sociologically informed skepticism. In doing so, it challenges us to question not only the technologies we are sold but also the ones we ourselves manufacture.

"In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem. Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, especially women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance--operating as a source for email, a major vehicle for primary and secondary school learning, and beyond--understanding and reversing these disquieting trends and discriminatory practices are of utmost importance."--Page 4 of cover

This post describes ongoing research by Kenny Peng, Arunesh Mathur, and Arvind Narayanan. We are grateful to Marshini Chetty for useful feedback. Computer

By Jessica Almeida, LISP-SIS During the AALL Virtual Meeting, the LISP-SIS sponsored program was the thought provoking “Understanding Bias in Artificial Intelligence: How Algorithms Impact Our Patr…

"Solutions to fix algorithmic bias could collide with law. Two scholars propose a solution."