Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Law enforcement (FBI, Providence Police, Rhode Island State Police)
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.
Using emotionally charged language to influence readers’ feelings rather than just presenting neutral facts.
The phrase from Brown University President Christina H. Paxson: "the shooting amounted to 'devastating gun violence.'" This wording emphasizes emotional impact and aligns with a broader political framing of gun violence, going slightly beyond a purely descriptive account of the incident.
Replace the emotionally charged quote with a more neutral paraphrase, e.g., "Brown University President Christina H. Paxson described the shooting as a tragic event for the campus community."
If the quote is retained, add context to separate fact from opinion, e.g., "In a statement expressing her personal reaction, Brown University President Christina H. Paxson called the shooting 'devastating gun violence.'"
Balance the emotional framing by including additional factual details (time, location, confirmed casualty numbers, investigation status) immediately around the quote so it does not dominate the narrative.
Leaving out relevant contextual information that could help readers fully understand the situation.
The article does not provide any information about possible motive, relationship between suspect and victims, or whether there is an ongoing threat to the wider public. While this may be due to an active investigation, the absence of explicit clarification can leave readers uncertain about risk and context.
Add a clarifying sentence about what is and is not yet known, e.g., "Authorities have not yet released information about a possible motive or any relationship between the suspect and the victims."
Include any available official statements about public safety, e.g., whether police believe this was a targeted incident or if there is concern about further attacks.
Explicitly note investigative limits, e.g., "Police said they are withholding certain details to protect the integrity of the ongoing investigation."
Presenting one side’s perspective more fully than others, even if not overtly biased in tone.
The article heavily features law enforcement and official institutional voices (FBI Director, Governor, university president, police) and does not include any direct perspectives from students, faculty, victims’ families, or independent experts. This is common in breaking news but still creates a structural imbalance in whose voices are heard.
Include at least one brief, factual comment from a student, faculty member, or campus community representative about the impact of the event, clearly labeled as their perspective.
Add a short statement from an independent public safety or criminology expert to contextualize the use of FBI resources and rewards in such cases.
Clarify that the article is based on official statements only, e.g., "As of Tuesday, information about the incident has come primarily from law enforcement and university officials."
- 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.