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everybody knows that misinformation is a
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big problem in the world right now but
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when we talk about misinformation we
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almost always mean false information our
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work leads us to believe that in fact
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bias can be a much bigger problem so
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that's what this project is really
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intended to uncover developed by the CSS
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Lab at Penn a joint venture between
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Warden pen engineering and the annenburg
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school for community ation the media
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bias detector tracks and classifies the
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top stories published by 10 prominent
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Publishers spending the political
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Spectrum in close to real time articles
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are fed into GPT 4 the large language
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model developed by open AI that
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underlies Chad GPT and classified by
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topics and events news type tone and
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political lean every week research
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assistants then monitor a random sample
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of the gpt's labels to ensure the
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model's accuracy remains high and
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identify any necessary
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adjustments there are two highlevel ways
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in which uh we think bias can manifest
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itself in journalism one is selection
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which stories journalists choose to
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write about which facts they choose to
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highlight which people they choose to
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quote and also framing how they spin the
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evidence that they present to you you
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can make your tone positive you can make
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your tone negative and both these forms
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of bias can have lot of impact on the
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way the story reads and on the takeaway
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that the reader gets from the story even
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to the point where one can get a highly
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misleading or even false impression of
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what is going on even though every
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sentence in the story might be correct
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this year's US presidential election
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presents a real-time high stakes
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environment to observe and analyze the
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choices media Publications are making
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every day in their coverage the media
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bias detector is a free resource
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designed to help you as a consumer
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better understand those choices and the
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biases that exist behind them
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