Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Israel
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.
Use of language that favors one side over another.
Statements like 'they should hit back' and 'if they are not good, they are going to be terminated' reflect a bias towards justifying Israeli actions.
Use neutral language when describing actions of both sides.
Avoid using language that implies justification or condemnation without evidence.
Claims made without sufficient evidence or support.
The article states 'Hamas had planted the remains at an excavation site' without providing concrete evidence.
Provide evidence or sources to support claims.
Clearly distinguish between verified facts and allegations.
Relying on sources that support one side while ignoring others.
The article quotes Israeli and U.S. officials extensively but lacks direct quotes from Hamas or Palestinian officials.
Include quotes and perspectives from both sides equally.
Seek comments from a diverse range of sources 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.