Hi James,
thanks a lot for your interest in our work!
The problem of crowdworkers being biased is a problem definitely not to
be neglected. Majority vote can help to sort out single extremist views
of workers but if many workers are strongly biased then I agree that
this might not be enough. We are actually already thinking about methods
to improve future crowdsourced bias datasets. One way to improve the
quality is to have a very well defined task that leaves only little room
for subjective interpretation. For example, instead of letting the
workers decide whether a statement is biased or not, we asked more
specifically whether the statement reflects an opinion or contains bias
words. Of course, the decision if a statement reflects a fact or an
opinion is still subjective in many cases.
Given your example it is hard to make a decision (even when being
unbiased) without having the proper background knowledge. That is why
our work mostly focuses on language bias, i.e. bias that is introduced
through the use of judgemental language. Since there are many cases of
bias without using judgemental language, we are definitely interested to
come up with good approaches that cover these cases as well. Ideas and
suggestions are always welcome!
One other thing that we are planning to do for future crowdsourcing jobs
is to ask workers for their political opinions and to take this
background information into account when creating ground truth data.
Best regards,
Christoph
Am 4/18/2018 um 2:22 PM schrieb James Salsman:
... Accepted papers
Christoph Hube and Besnik Fetahu
Detecting Biased Statements in Wikipedia
http://wikiworkshop.org/2018/papers/wikiworkshop2018_paper_1.pdf
...
Hi Christoph and Besnik,
Having worked with several thousand of Amazon Mechanical Turkers over
the past year, I am not convinced that their opinions of bias, even in
aggregate, are not biased. Did you take any steps to measure the bias
against accuracy in your crowdworkers?
Here is an example of what I expect they would get wrong:
"Tax cuts allow consumers to increase their spending, which boosts
aggregate demand."
That statement, added by en:User:Bkwillwm in 2012,[1] is still part of
the English Wikipedia's Economics article. However, the statement is
strictly inaccurate, and heavily biased in favor of trickle-down
economics and austerity policy.[2] It and statements like it,
pervasive through many if not most of the popular language Wikipedias,
directly support increases in income inequality, which in turn is a
terrible scourge affecting both health[3] and economic growth.[4]
How can you measure whether your crowdworkers are truly unbiased
relative to accuracy, instead of just reflecting the
propaganda-influenced whims of the populist center?
Sincerely,
James Salsman
[1]
https://en.wikipedia.org/w/index.php?title=Economics&diff=prev&oldid=511580566
[2]
https://en.wikipedia.org/wiki/Talk:Economics/Archive_7#Tax_cut_claim_in_Fiscal_policy_section
[3] http://talknicer.com/ehip.pdf
[4] http://talknicer.com/egma.pdf
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