Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Former Police Officer
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 emphasizing certain aspects to provoke public interest or excitement.
The article mentions that the deaths 'shocked the LGBTQ+ community of Australia,' which could be seen as sensationalizing the impact without providing specific evidence of the community's reaction.
Provide specific examples or statements from the LGBTQ+ community to support the claim of shock.
Avoid using emotionally charged language without evidence.
Using language that unfairly favors one side over another.
The article describes the backlash against the NSW Police Force and the prohibition of officers from marching in the Sydney Pride parade, which could imply a bias against the police without presenting their perspective.
Include statements or responses from the NSW Police Force regarding the backlash.
Present a balanced view by including perspectives from both the police and the LGBTQ+ community.
- 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.