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An answer is not an explanation. As AI systems optimise for performance, the gap between output and understanding becomes harder to ignore. What we ask machines to explain reveals what we are willing—or unwilling—to understand ourselves.
In the United Arab Emirates, AI is moving from advice to execution. As systems begin to act, the challenge shifts from performance to accountability—raising fundamental questions about control, responsibility and the conditions under which autonomous decisions can be trusted.
Speed made AI usable. Explainability makes it accountable. As systems move into critical domains, trust can no longer rely on performance alone. It requires transparency, traceability and the ability to question how decisions are made.
Decisions are increasingly made by systems that cannot explain themselves. As performance improves, understanding fades. Between efficiency and accountability, a structural tension emerges—one that challenges how we define reasoning, responsibility and control in the age of AI.
