Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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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 exciting or shocking stories at the expense of accuracy, to provoke public interest or excitement.
The article title suggests LeBron James and Steph Curry are discussing teaming up under Steve Kerr, which is sensational and misleading as it pertains to the Olympics, not the NBA.
Clarify in the title that the discussion is about the Olympics, not an NBA team-up.
Headlines that do not accurately reflect the content of the article.
The headline implies a potential NBA collaboration, which is not the case as the article later clarifies they discussed playing together for the USA Men's basketball team.
Rewrite the headline to accurately reflect the content of the article.
Claims that are presented without sufficient evidence or support.
The article relies on speculative statements from analysts like Brian Windhorst and Skip Bayless without providing concrete evidence for the claims made.
Provide evidence or statements from the involved parties to support the claims.
- 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.