Description

Science is about making the world clearer and more understandable. By classifying the world into observable, repeatable, verifiable phenomena we move towards a shared sense of reality rather than an individual, subjective one. A cornerstone of contemporary science is how well any research stands up to the rigour of peers questioning and responding to it. But to question, we must first know, to repeat we must first see. This requires openness and transparency. The clarity of contemporary science is giving way to more opaque systems in the digital era, where complex algorithms are guarded by intellectual property, commercial patents and secret code, and the inner workings of significant global products are hidden from us. This is increasingly moving us towards a black box society, where we no longer see or understand the world around us, as everyday products and platforms become opaque systems of code, algorithms and AI that we can’t reach, and therefore can’t hope to comprehend. A society where we don’t know how key decisions are made, and which specific individuals or groups can be held to account for those decisions.

Summary

The article addresses the societal challenges posed by AI's increasing opacity due to proprietary algorithms and restricted access to technological decision-making processes. It underscores the transition towards a 'black box' society, where key decisions become inscrutable, posing risks to accountability and transparency. While it does not delve deeply into existential risks, it highlights a significant governance issue pertinent to global AI safety policy. The text suggests the need for new frameworks to ensure AI systems operate transparently and are held accountable, with implications for the broader AI governance discourse.

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