Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Kamala Harris
Caution! Due to inherent human biases, it may seem that reports on articles aligning with our views are crafted by opponents. Conversely, reports about articles that contradict our beliefs might seem to be authored by allies. However, such perceptions are likely to be incorrect. These impressions can be caused by the fact that in both scenarios, articles are subjected to critical evaluation. This report is the product of an AI model that is significantly less biased than human analyses and has been explicitly instructed to strictly maintain 100% neutrality.
Nevertheless, HonestyMeter is in the experimental stage and is continuously improving through user feedback. If the report seems inaccurate, we encourage you to submit feedback , helping us enhance the accuracy and reliability of HonestyMeter and contributing to media transparency.
Using language that subtly favors one side over the other.
The phrase 'potentially troubling sign for the Democratic nominee' suggests a negative outlook for Harris without providing a balanced perspective on the overall polling data.
Rephrase to 'The new survey showed a 12 percent drop in support from Wisconsin voters aged 18 to 29 for Harris, compared with the earlier poll.'
Focusing more on one side's negative aspects while downplaying or omitting the other's.
The article highlights Harris's drop in support among Gen Z voters but does not equally emphasize Trump's loss of support among millennial voters.
Provide a more balanced view by equally emphasizing both Harris's and Trump's changes in support across different demographics.
Selecting data that supports a particular viewpoint while ignoring data that may contradict it.
The article mentions Harris's drop in support among Gen Z voters but does not equally highlight her gains among millennial voters.
Include a balanced discussion of both Harris's and Trump's changes in support across all age groups.
- This is an EXPERIMENTAL DEMO version that is not intended to be used for any other purpose than to showcase the technology's potential. We are in the process of developing more sophisticated algorithms to significantly enhance the reliability and consistency of evaluations. Nevertheless, even in its current state, HonestyMeter frequently offers valuable insights that are challenging for humans to detect.