Media Manipulation and Bias Detection
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HonestyMeter - AI powered bias detection
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Cashew sector / All India Cashew Association
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 only one side or perspective on an issue without including other relevant viewpoints.
The entire article focuses solely on the positive reaction of the cashew sector: "The cashew sector has hailed the Interim Trade Agreement..." and quotes only the Secretary of the All India Cashew Association. No other stakeholders, such as consumers, other agricultural sectors, trade experts, or US counterparts, are mentioned.
Include comments from additional stakeholders, such as trade economists, consumer groups, or representatives from other export sectors, to provide a broader view of the agreement's impact.
Mention any known or potential drawbacks or concerns related to the Interim Trade Agreement, if they exist, to balance the overwhelmingly positive framing.
Clarify that the article is reporting the reaction of one stakeholder group (the cashew sector) and explicitly note that other perspectives were not available or not covered in this brief report.
Presenting claims or predictions without evidence, data, or clear sourcing beyond a single interested party.
The statement "the deal will benefit 10 lakh people involved in the sector" and "the reduction of tariffs will also provide the opportunity to increase the export of cashews to the US" are presented as outcomes, but only attributed to the Secretary of the All India Cashew Association, who has a vested interest. No data, official projections, or independent analysis are provided to support these claims.
Attribute clearly that these are projections or opinions: e.g., "Ramakrishnan said he expects the deal to benefit around 10 lakh people..." rather than implying it as a settled fact.
Add supporting data or references, such as government estimates, trade statistics, or expert analysis, to substantiate the claim about the number of people benefiting and the expected export increase.
Qualify the language to reflect uncertainty, e.g., "could benefit" or "may provide an opportunity to increase exports," unless there is strong evidence that these outcomes are guaranteed.
Relying on the opinion of an authority figure as primary evidence without additional support.
The article relies solely on the statement of "Secretary of All India Cashew Association Ramakrishnan" to assert the benefits of the agreement. His position lends authority, but no independent corroboration or data is provided.
Supplement the authority’s statement with independent sources, such as official trade data, government documents on the agreement, or analysis from neutral experts.
Clarify that the Secretary represents an interested party whose perspective may emphasize benefits to his sector.
Include at least one neutral or critical viewpoint to avoid over-reliance on a single authority figure.
- 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.