Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
- Objectivity Score
Media Manipulation and Bias Detection
Auto-Improving with AI and User Feedback
HonestyMeter - AI powered bias detection
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Trump
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 article selectively presents information that supports the Trump defense while omitting contradictory evidence.
The article highlights the defense's argument that the financial statements were not misleading and that different people can come up with different values for the same property. However, it fails to mention any evidence presented by the New York Attorney General's Office that contradicts this argument.
Include information about the evidence presented by the New York Attorney General's Office that challenges the defense's argument.
Provide a more balanced presentation of the arguments and evidence from both sides.
The article fails to include important details that could provide a more complete understanding of the case.
The article does not mention the specific allegations made by the New York Attorney General's Office, such as conspiracy, falsifying business records, issuing false financial statements, and insurance fraud. This omission prevents readers from fully understanding the scope of the case.
Include a summary of the specific allegations made by the New York Attorney General's Office.
Provide more context about the overall goals and implications of the case.
The article uses language that favors the Trump defense and portrays the New York Attorney General's Office in a negative light.
The article refers to the New York Attorney General's Office as the 'state attorney' and describes their questions as 'quizzing' and 'insisting' on 'yes' or 'no' responses. This language suggests a bias in favor of the Trump defense.
Use neutral language to describe both sides of the case.
Avoid using language that implies bias or favoritism.
The article provides more detailed information about the Trump defense than the case presented by the New York Attorney General's Office.
The article includes specific details about the defense's strategy, the witnesses they plan to call, and the arguments they will make. In contrast, it provides limited information about the case presented by the New York Attorney General's Office.
Provide more balanced coverage of both the defense's case and the case presented by the New York Attorney General's Office.
Include more information about the witnesses and evidence presented by the New York Attorney General's Office.
The article includes statements that lack evidence or supporting sources.
The article states that the Trumps have argued that the banks did not lose any money and that none have claimed they were defrauded or misled by the financial statements. However, it does not provide any evidence or sources to support these claims.
Include evidence or sources to support the claims made by the Trumps.
Provide a more balanced presentation of the banks' perspectives and any claims they may have made.
- 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.