Bneutrality
Bneutrality is a principle in information ethics and technology governance that seeks to minimize biased influence in the processing, presentation, and dissemination of information. It defines neutrality as a state in which system outputs do not unduly favor, penalize, or silence particular demographic groups, viewpoints, or narratives. Proponents describe Bneutrality as a proactive approach to reduce discriminatory effects in algorithms, data selection, and decision rules while preserving useful distinctions where they are required to meet legitimate goals.
Origins and scope: The term has appeared in speculative discussions and academic writing about fair and responsible
- Bias minimization: efforts to reduce disproportionate impacts across groups.
- Representational balance: inclusion of diverse perspectives in datasets and outputs.
- Transparency and auditability: clear methods and the ability to verify results.
- Accountability: mechanisms to address harms and adjust processes.
Applications: In artificial intelligence, Bneutrality guides training data selection, model evaluation, and deployment monitoring; in search
Criticisms: Critics warn that perfect neutrality is difficult or impossible, may obscure legitimate value judgments, or
See also: neutrality, bias, algorithmic fairness, net neutrality.