Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
CLICK ANY SECTION TO GIVE FEEDBACK, IMPROVE THE REPORT, SHAPE A FAIRER WORLD!
None
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.
The use of language that favors one side or presents information in a subjective manner.
The article includes biased language when describing the meetings between US and Chinese diplomats. For example, it states that the meetings were a 'good opportunity' to keep lines of communication open between two geopolitical rivals, implying a positive outcome. This language can influence the reader's perception of the meetings.
Use neutral language to describe the meetings without implying a positive or negative outcome.
Provide a balanced perspective by including statements from both sides about the significance of the meetings.
The deliberate exclusion of important details or context that could provide a more complete understanding of the topic.
The article omits key information about the specific policy differences between the US and China that were discussed during the meetings. This omission prevents readers from fully understanding the nature of the disagreements between the two countries.
Include specific examples of policy differences discussed during the meetings to provide a more comprehensive view of the issues at hand.
Provide context on the historical background of the policy differences to help readers understand the broader context of the discussions.
- 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.