Skip to main content

Home/ GAVNet Collaborative Curation/ Group items tagged speculation

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
Steve Bosserman

Are You Creditworthy? The Algorithm Will Decide. - 0 views

undark.org/...redit-scoring-machine-learning

algorithms discrimination bias credit scoring

shared by Steve Bosserman on 12 May 18 - No Cached
  • The decisions made by algorithmic credit scoring applications are not only said to be more accurate in predicting risk than traditional scoring methods; its champions argue they are also fairer because the algorithm is unswayed by the racial, gender, and socioeconomic biases that have skewed access to credit in the past.
  • Algorithmic credit scores might seem futuristic, but these practices do have roots in credit scoring practices of yore. Early credit agencies, for example, hired human reporters to dig into their customers’ credit histories. The reports were largely compiled from local gossip and colored by the speculations of the predominantly white, male middle class reporters. Remarks about race and class, asides about housekeeping, and speculations about sexual orientation all abounded.
  • By 1935, whole neighborhoods in the U.S. were classified according to their credit characteristics. A map from that year of Greater Atlanta comes color-coded in shades of blue (desirable), yellow (definitely declining) and red (hazardous). The legend recalls a time when an individual’s chances of receiving a mortgage were shaped by their geographic status.
  • ...1 more annotation...
  • These systems are fast becoming the norm. The Chinese Government is now close to launching its own algorithmic “Social Credit System” for its 1.4 billion citizens, a metric that uses online data to rate trustworthiness. As these systems become pervasive, and scores come to stand for individual worth, determining access to finance, services, and basic freedoms, the stakes of one bad decision are that much higher. This is to say nothing of the legitimacy of using such algorithmic proxies in the first place. While it might seem obvious to call for greater transparency in these systems, with machine learning and massive datasets it’s extremely difficult to locate bias. Even if we could peer inside the black box, we probably wouldn’t find a clause in the code instructing the system to discriminate against the poor, or people of color, or even people who play too many video games. More important than understanding how these scores get calculated is giving users meaningful opportunities to dispute and contest adverse decisions that are made about them by the algorithm.
Bill Fulkerson

Living The Good Life In A Non-Growth World: Investigating The Role Of Hierarchy, Part 2 - 0 views

econintersect.com/...analysis.php

hierarchy living

shared by Bill Fulkerson on 26 Feb 21 - No Cached
  • Bill Fulkerson on 26 Feb 21
     
    Humanity's most pressing need is to learn how to live within our planet's boundaries - something that likely means doing without economic growth. How, then, can we create a non-growth society that is both just and equitable? I attempt to address this question by looking at an aspect of sustainability (and equity) that is not often discussed: the growth of hierarchy. As societies consume more energy, they tend to become more hierarchical. At the same time, the growth of hierarchy also seems to be a key driver of income/resource inequality. In this essay, I review the evidence for the joint relation between energy, hierarchy and inequality. I then speculate about what it implies for achieving a sustainable and equitable future.
Bill Fulkerson

trace origins - 0 views

www.nature.com/...d41586-020-01541-z

coronavirus

shared by Bill Fulkerson on 09 Jun 20 - No Cached
  • Bill Fulkerson on 09 Jun 20
     
    SARS-CoV-2 came from an animal but finding which one will be tricky, as will laying to rest speculation of a lab escape.
Bill Fulkerson

Thousands of tons of ocean pollution can be saved by changing washing habits - 0 views

phys.org/...ns-ocean-pollution-habits.html

pollution washing ocean

shared by Bill Fulkerson on 05 Jun 20 - No Cached
  • Bill Fulkerson on 05 Jun 20
     
    Every time you wash your clothes, thousands of tiny microfibres from the fabric are released into rivers, the sea and the ocean, causing marine pollution. Scientists have speculated for some time that these microfibres may cause more harm than microbeads, which were banned from UK and US consumer products in recent years. Researchers from Northumbria University worked in partnership with Procter & Gamble, makers of Ariel, Tide, Downy and Lenor on the first major forensic study into the environmental impact of microfibres from real soiled household laundry. Their forensic analysis revealed an average of 114 mg of microfibres were released per kilogram of fabric in each wash load during a standard washing cycle.
1 - 7 of 7
Showing 20▼ items per page