G, Vinky. “Black Box Ai Explained: Understanding Ai’s Hidden Mechanisms.” RPATech, 13 Aug. 2025, www.rpatech.ai/black-box-ai/. Accessed 29 Sept. 2025.
This article explains the AI ‘black-box’ problem, where black-boxes symbolize a system that is not “…transparent or easily interpretable…” for humans to assess. Many users of AI programs are content to make use of these tools, yet are unaware of how they function, that is if the average person can even obtain this information whatsoever. Taking measures to address this issue is of key importance if we ever wish to see accountable and just AI regulation that protects humanity and the public broadly, as well as allows for companies and private interest to exist within a just legal framework. To arrive at a conclusion without a clear understanding of how one gets there leaves significant room for informational and epistemic vulnerability that can result in exploitation, misinformation, and other potential harms.
As the article itself concludes with, AI is too far developed and invested in to completely discard as a tool. What must be done instead is work to create comprehensive and capable systems, but do so with respect to the capacity to interpret the system and its outputs. Much akin to how we must support our own claims with evidence, “show our work” per se, we must hold the same standards to generative AI. This premise sets the groundwork that indicates the necessity of addressing the black-box problem and maintaining industrial accountability.
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