Algorithmic Dissonance
The whopper of a contradiction at the heart of AI governance
EAON PRITCHARD
Mar 10, 2026
The biggest incoherence in the modern debate about AI is actually surprisingly simple. Publicly, AI is discussed as a safety problem. Institutionally, it is treated as an economic growth technology. Most of the confusion surrounding AI governance flows from this whopping contradiction.
If you listen to the public language of AI governance, the tone is cautious. Governments talk about AI safety, alignment, model evaluations, and responsible deployment. Conferences convene panels of ethicists and researchers to discuss bias, hallucinations, misuse, and long-term existential risks.
And yet, if that framing genuinely governed institutional behaviour, then surely we would expect to see a cautious and incremental approach to development. But that is exactly not what is happening.
Governments across the world are investing massive amounts into AI development and adoption. The US is pouring billions into semiconductor manufacturing and advanced compute. China has declared AI leadership a national priority.
So we end up with two incompatible narratives operating simultaneously. One narrative says AI must be handled cautiously because it introduces serious risks to society. The other says AI must be developed rapidly because it represents a once-in-a-generation economic opportunity.
The result is something that sociologists call performative governance.
Institutions construct a layer of responsible language and ethical frameworks that signal caution and legitimacy. But underneath that window dressing, the operational system continues to push toward rapid capability growth.
This is the fundamental incoherence in the governance debate. We are trying to regulate a technology using the same institutions that are simultaneously committed to accelerating its expansion.
Until those incentives align, the discussion about AI risks will continue to oscillate between two competing claims: that AI is too powerful to release without careful safeguards, and that AI is too important to slow down. Both claims can be defended. But they cannot both serve as the guiding principle of institutional behaviour at the same time.