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!
Government / New Ministers
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.
Presenting individuals only through their positive titles, expertise, and achievements can create an overly favorable impression and imply competence or virtue beyond what is evidenced.
Examples: - "Minister Ingam is a professor at Kathmandu School of Law, known for his expertise in international trade law, arbitration, and financial crime." - "Newly appointed Labour Minister Bhandari is a former Additional Inspector General of Nepal Police and founding chief of the Central Investigation Bureau (CIB)." - "Forest Minister Chaulagain is a public health expert recognized for his research on the Karnali region, while Shrestha is a senior manager at the Nepal Tourism Board and former head of its Sustainable Tourism project." These descriptions selectively highlight only positive credentials and recognition, which can subtly frame the appointments as unquestionably meritorious without offering any neutral or critical context.
Clarify that these are professional background details, not value judgments, e.g.: "According to their official biographies, Minister Ingam is a professor..."
Balance the profiles by noting that the article does not assess their performance or suitability, e.g.: "The article provides only basic professional background and does not evaluate the ministers' past performance or policy positions."
If available and relevant, add neutral context such as prior roles, key policy positions, or any notable debates about their appointments, presented in a factual, non-judgmental way.
Leaving out relevant contextual information can unintentionally favor one side or narrative, even if the tone is neutral.
The article states: "This marks the fourth expansion of the interim cabinet formed after the Gen-Z Movement, bringing the council to 14 members." but does not explain: - Why the cabinet is being expanded repeatedly. - Whether there is any public or political debate about these expansions. - Any implications for governance, coalition dynamics, or policy. While this is typical for a brief news item, the lack of any mention of differing views or context structurally favors the government narrative that the expansion is routine and uncontroversial.
Add one or two neutral sentences on context, e.g.: "The repeated expansions have drawn mixed reactions from opposition parties, with some leaders questioning the need for a larger cabinet, while the government says the additions are necessary to manage the workload."
If no significant controversy exists, state that explicitly, e.g.: "The appointments have so far drawn little public or political controversy."
Clarify the purpose of the expansion if known, e.g.: "According to the Prime Minister's Office, the expansion aims to fill portfolios that had remained vacant in the interim cabinet."
- 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.