Healthcare Algorithm Used Across America Has Dramatic Racial Biases
The U.S. health care system uses commercial algorithms to guide health decisions. A study found evidence of racial bias in one widely used algorithm, such that black patients assigned the same level of risk by the algorithm are sicker than white patients.
Knowledge in the dark: scientific challenges and ways forward
A key dimension of our current era is Big Data, the rapid rise in produced data and information; a key frustration is that we are nonetheless living in an age of ignorance, as the real knowledge and understanding of people does not seem to be substantially increasing. This development has critical consequences.
Big Qual - Why We Should Be Thinking Big About Qualitative Data for Research, Teaching and Policy
When social scientists think about big data, they often think in terms of quantitative number crunching. However, the growing availability of ‘big’ qualitative datasets presents new opportunities for qualitative research.
Up to now, STI (Science, Technology, Innovation) studies are either rich but small scale (qualitative case studies) or large scale and under-complex. However, progress in the STI research field depends in our view on the ability to do large-scale studies with often many variables specified by relevant theories: There is a need for studies which are at the same time big and rich. To enable that, combining and integration of STI data and beyond is needed – in order to exploit the huge amount of data that are ‘out there’ in an innovative and meaningful way.
The aim of the Semantically Mapping Science (SMS) platform as the technical core within the RISIS EU project is to produce richer data to be used in social research – through the integration of heterogeneous datasets, ranging from tabular statistical data to unstructured data found on the Web.
Fitbit's 150 Billion Hours of Heart Data Reveal Secrets About Health
Fitibit's wristbands have collected 150 billion hours' worth of heart-rate data from people around the world. For the first time, the company offered a look inside that data, to see how lifestyle, location, age, and gender affects our health and longevity.