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Technology Equity and Inclusion : Technology and Equity
MAY 7, 2019 from the Pew Research Center:
Roughly three-in-ten adults with household incomes below $30,000 a year (29%) don’t own a smartphone. More than four-in-ten don’t have home broadband services (44%) or a traditional computer (46%). And a majority of lower-income Americans are not tablet owners. By comparison, each of these technologies is nearly ubiquitous among adults in households earning $100,000 or more a year.
JULY 14, 2020 from WPR: Wisconsin currently ranks 30th in the nation for broadband coverage. More than 5.4 million residents, or roughly 93 percent of the state's population, now have access to broadband internet in Wisconsin, according to the most recent data from the Federal Communications Commission. However, challenges with access remain in rural areas of the state, where roughly 398,000 people or nearly 23 percent of the rural population lack high-speed internet. The number of rural residents lacking broadband access has decreased from 748,000 in 2018.
SEP 8, 2020 from the Reedsburg Times-Press: More than 40% of rural residents lack access to high-speed internet, according to the Public Service Commission of Wisconsin. Nationally, about 31 % of rural households lack access. Actual percentages might even be higher due to poor FCC mapping, experts say.
Race after Technology by Ruha BenjaminFrom 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. Visit the book's free Discussion Guide here.
Automating Inequality by Virginia EubanksWINNER: The 2019 Lillian Smith Book Award, 2018 McGannon Center Book Prize, and shortlisted for the Goddard Riverside Stephan Russo Book Prize for Social Justice Astra Taylor, author of The People's Platform: "The single most important book about technology you will read this year." Dorothy Roberts, author of Killing the Black Body: "A must-read." A powerful investigative look at data-based discrimination?and how technology affects civil and human rights and economic equity The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years--because a new computer system interprets any mistake as "failure to cooperate." In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems--rather than humans--control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely.
Call Number: 362.560285 E86
Publication Date: 2018
Diversifying Digital Learning by William G. Tierney (Editor); Zoë B. Corwin (Editor); Amanda Ochsner (Editor)How does the digital divide affect the teaching and learning of historically underrepresented students? Many schools and programs in low-income neighborhoods lack access to the technological resources, including equipment and Internet service, that those in middle- and upper-income neighborhoods have at their fingertips. This inequity creates a persistent digital divide--not a simple divide in access to technology per se, but a divide in both formal and informal digital literacy that further marginalizes youths from low-income, minoritized, and first-generation communities. Diversifying Digital Learning outlines the pervasive problems that exist with ensuring digital equity and identifies successful strategies to tackle the issue. Bringing together top scholars to discuss how digital equity in education might become a key goal in American education, this book is structured to provide a framework for understanding how historically underrepresented students most effectively engage with technology--and how institutions may help or hinder students' ability to develop and capitalize on digital literacies. This book will appeal to readers who are well versed in the diverse uses of social media and technologies, as well as less technologically savvy educators and policy analysts in educational organizations such as schools, afterschool programs, colleges, and universities. Addressing the intersection of digital media, race/ethnicity, and socioeconomic class in a frank manner, the lessons within this compelling work will help educators enable students in grades K-12, as well as in postsecondary institutions, to participate in a rapidly changing world framed by shifting new media technologies. Contributors: Young Whan Choi, Zoë B. Corwin, Christina Evans, Julie Flapan, Joanna Goode, Erica Hodgin, Joseph Kahne, Suneal Kolluri, Lynette Kvasny, David J. Leonard, Jane Margolis, Crystle Martin, Safiya Umoja Noble, Amanda Ochsner, Fay Cobb Payton, Antar A. Tichavakunda, William G. Tierney, S. Craig Watkins
Call Number: eBook
Publication Date: 2018
Weapons of Math Destruction by Cathy O'NeilWe live in the age of the algorithm. Increasingly, the decisions that affect our lives--where we go to school, whether we get a car loan, how much we pay for health insurance--are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated. But as Cathy O'Neil reveals in this urgent and necessary book, the opposite is true.
The models being used today are opaque, unregulated, and uncontestable, even when they're wrong. Most troubling, they reinforce discrimination: If a poor student can't get a loan because a lending model deems him too risky (by virtue of his zip code), he's then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a "toxic cocktail for democracy." Welcome to the dark side of Big Data.