Contemporary Issues in
Computer Science
Algorithm Bias
We often idealize technology as a way to
completely eliminate human error and bias.
But, unless we are brutally self-aware in the design stage (and probably
even if we are), our technology will mimic our own weaknesses.
So,
read:
https://www.technologyreview.com/s/601775/why-we-should-expect-algorithms-to-be-biased/
http://www.theverge.com/2016/5/25/11773108/research-method-measure-algorithm-bias
http://spectrum.ieee.org/tech-talk/computing/software/computer-scientists-find-bias-in-algorithms
Answer these two questions. Focus on the connection between technical
issues and societal/ ethical impact.
1.
Choose
one specific problem domain in which sophisticated, data-driven, and probably
biased algorithms are already making important decisions. Then answer these questions:
a)
Very
briefly describe the problem and the algorithm(s).
b)
What
data do they use as training sets?
c)
What
is the evidence for bias? What
features (for example, race or gender or socioeconomic status or ethnicity) may
be involved? Can you suggest
reasons why available data could lead to bias?
d)
Briefly
analyze the likely impact of this bias.
On whom?
e)
Is
anyone trying to solve the problem?
[Write about 500 words,
more if you really get into the issue.
If possible, find an example different from the ones mentioned in these
articles. Or choose one of these
and tell us more about it.]
2.
What
techniques can or should we as a society use to reduce algorithmic bias as much
as possible without giving up the positive features of the systems that rely on
sophisticated algorithms and the machine learning on which they’re
based? Make an argument in favor of
or against one or more of these solutions.
[Write about 300 words.]
Be
sure to cite your sources.