John Bouman, Poverty Matters: Five Key Takeaways from the 2016 Census Data Poverty Matters: Five Key Takeaways from the 2016 Census Data, The Shriver Brief, September 13, 2017. [Slight improvements haven not translated into gains for those facing poverty.]
Dominic Rushe, Fran works six days a week in fast food, and yet she’s homeless: “It’s economic slavery”, The Guardian Aug. 21, 2017. [An account of the experiences of Fran Marion and others who are leading the charge for a raised minimum wage.]
Arthur Delaney, Bad Jobs and No Welfare Give Rise to A New Type of Charity: The Diaper Bank, Huffington Post Aug. 21, 2017. [“A network of diaper banks now alleviates some of the suffering cause by the 1996 gutting of welfare”]
Article: Mary Madden, et al., Privacy, Poverty and Big Data: A Matrix of Vulnerabilities for Poor Americans, Washington L. Rev. (forthcoming 2017).
This Article examines the matrix of vulnerabilities that low-income people face as a result of the collection and aggregation of big data and the application of predictive analytics. On the one hand, big data systems could reverse growing economic inequality by expanding access to opportunities for low-income people. On the other hand, big data could widen economic gaps by making it possible to prey on low-income people or to exclude them from opportunities due to biases that get entrenched in algorithmic decision-making tools. New kinds of “networked privacy” harms, in which users are simultaneously held liable for their own behavior and the actions of those in their networks, may have particularly negative impacts on the poor. This Article reports on original empirical findings from a large, nationally-representative telephone survey with an oversample of low-income American adults and highlights how these patterns make particular groups of low-status internet users uniquely vulnerable to various forms of surveillance and networked privacy-related problems. In particular, a greater reliance on mobile connectivity, combined with lower usage of privacy-enhancing strategies may contribute to various privacy and security-related harms. The article then discusses three scenarios in which big data – including data gathered from social media inputs – is being aggregated to make predictions about individual behavior: employment screening, access to higher education, and predictive policing. Analysis of the legal frameworks surrounding these case studies reveals a lack of legal protections to counter digital discrimination against low-income people. In light of these legal gaps, the Article assesses leading proposals for enhancing digital privacy through the lens of class vulnerability, including comprehensive consumer privacy legislation, digital literacy, notice and choice regimes, and due process approaches. As policymakers consider reforms, the article urges greater attention to impacts on low-income persons and communities.
News Article: Steven Mufson and Tracy Jan, If you’re a poor person in America, Trump’s budget is not for you, Washington Post (Mar. 16, 2017).
Posted in Family, Finance, Health, housing, Inequality, Legal Aid, Measuring Poverty, News Coverage of Poverty, Politics, Uncategorized, War on Poverty, Wealthy, Welfare
Article: Jonathan D. Glater, Student Debt and Higher Education Risk, 103 Cal. L. Rev. 1561 (2015).
To borrow for college is to take a risk. Indebted students may not earn enough to repay their loans after they graduate or, worse, may fail to graduate at all. For students who cannot pay for college without borrowing, this risk is both a disincentive and a penalty. Greater risk undermines the efficacy of federal financial aid policy that seeks to promote access to higher education. This Essay situates education borrowing within a larger cultural and political trend toward placing risk on individuals and criticizes this development for its failure to achieve any of the typical goals of legislation that allocates risk—such as prevention of moral hazard or other, particular public policy outcomes.
The Essay describes dramatic increases in student borrowing and explains the negative effects of greater reliance on debt, which increases the risk of investing in higher education. The Essay contends that recognizing student debt as a mechanism that transfers risk bolsters criticisms of increased borrowing and provides a consistent way to evaluate aid policy. The Essay outlines an insurance regime as the logical response to undesirable or unmanageable risk. Such a regime would preserve access to higher education and mitigate the danger of borrowing for college.
Letter to the Editor: How to make housing more affordable, Washington Post (Oct. 21, 2016).
Posted in Economic Crisis, Economic Mobility, Employment, Finance, Inequality, Measuring Poverty, News Coverage of Poverty, Politics, Uncategorized, Wealthy, Welfare