#mscedc Healthcare algorithm used across America has dramatic racial biases
Less money is spent on black patients with the same level of need as white patients, causing the algorithm to conclude that black patients were less sick, the researchers found
Predictive algorithms that power these tools should be continually reviewed and refined, and supplemented by information such as socio-economic data, to help clinicians make the best-informed care decisions for each patient,” an Optum spokesman, Tyler Mason, said.
Indifference to social reality is, perhaps, more dangerous than outright bigotry.
This article on the bias of algorithms reminds us that “We must not assume the transparency and necessity of automation”. (Knox 2015), and to maintain a “more general, critical account of algorithms, their nature and how they perform work” (Kitchin 2017). Businesses with products to sell, venture capital firms with return on investment to secure, think tanks with new ideas to promote, policy makers with problems to solve and politicians with agendas to set have all become key advocates for data driven education. (Williamson 2017)
https://t.co/7Cn39Sf3xG
References-
Kitchin, R. (2017) Thinking critically about and researching algorithms, Information, Communication & Society, 20:1, 14-29, DOI: 10.1080/1369118X.2016.1154087
Knox, J. 2015.Algorithmic Cultures. Excerpt from Critical Education and Digital Cultures. In Encyclopedia of Educational Philosophy and Theory. M. A. Peters (ed.). DOI 10.1007/978-981-287-532-7_124-1
Williamson, B. 2017. Introduction: Learning machines, digital data and the future of education (chapter 1). In Big Data and Education: the digital future of learning, policy, and practice
