Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Maureen Howieson
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.
Exaggerating or sensationalizing aspects of the story to attract attention.
The headline 'Eye-Rolling Turns Pricey' sensationalizes the issue by focusing on the monetary award and the act of eye-rolling.
Use a more neutral headline such as 'UK Nurse Wins Tribunal Case Over Workplace Bullying'.
Providing more coverage or detail to one side of the story over the other.
The article provides detailed accounts of Howieson's experiences and the tribunal's decision but lacks detailed responses or perspectives from Iqbal.
Include more information or statements from Jisna Iqbal or her representatives to provide a balanced view.
- 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.