Meysam Ghanbari argues that ideology should become a hypothesis to test, not a package to inherit. Advanced AI could compare policy outcomes across many dimensions—but only after society confronts the harder question of who defines success.
Ideology is a compression system
Left and right bundle many independent choices—taxation, industrial policy, civil liberty, welfare, energy and foreign affairs—into identities. That compression once made mass politics legible. It can also prevent a policy from being judged on its own evidence. A city may need market pricing for congestion, public investment in transit and strict privacy limits for mobility data at the same time. The best combination does not necessarily sit at one point on a nineteenth-century spectrum.
From packages to policy search
Machine intelligence can search a larger design space than a political party can defend in an election. Models could compare infrastructure plans under population growth, energy shocks, climate scenarios and budget constraints; they could expose tradeoffs rather than conceal them behind slogans. OECD research already documents government AI being used for forecasting, anomaly detection and service delivery. These are early instruments, not superintelligence, but they show how governance can become more analytical.
The objective function is politics
A model cannot derive the good society from data alone. Maximizing output may damage autonomy. Maximizing stability may suppress dissent. Maximizing average health may neglect rare conditions. Values enter through objectives, constraints, measurement and the distribution of error. The central constitutional task of an AI-assisted state would therefore be deciding which goals may be optimized, which rights remain non-negotiable and how conflicts are appealed.
A practical transition
The credible path is not a sudden machine government. It is layered delegation: human institutions define rights and goals; audited systems forecast consequences; limited administrative domains use automation under explicit thresholds; independent bodies test failures; citizens and experts can challenge outputs. Evidence can weaken ideological rigidity without erasing legitimacy.
Beyond the spectrum, not beyond accountability
Post-ideological governance should mean greater willingness to revise policy, not the disappearance of politics. Data can narrow disputes about consequences, but disagreement about values will remain. A system worthy of the future must become more adaptive and more accountable at the same time.
Who defines the objective function?
If a superintelligent system can optimize policy, authority still begins with the choice of target. Survival, liberty, equality, longevity, prosperity and expansion can conflict. Ghanbari’s position is that this choice should be explicit, measurable and revisable—not hidden inside ideology or software.
The alternative to left and right is not a single new doctrine. It is a governance architecture that treats policies as testable designs, keeps constitutional limits visible and uses intelligence to enlarge the range of workable choices.
QUESTIONS READERS ASK
Further questions
What is governance beyond left and right?
It is an approach that evaluates policies by evidence, outcomes and explicit values rather than accepting a fixed ideological package.
Could superintelligence make governance objective?
No. It may improve forecasting and optimization, but objectives, rights and acceptable risks remain political and ethical choices.
EVIDENCE LAYER
Sources and further reading
- Governing with Artificial IntelligenceOECD ↗
- AI Risk Management FrameworkNIST ↗
- Governing AI for HumanityUnited Nations ↗
Sources support factual context. Interpretive conclusions are presented as Meysam Ghanbari’s perspective, not as settled scientific fact.
