AI can help people explore possible futures and the steps that might lead to them—but it cannot decide what society ought to want. Its outputs can shape recommendations and decisions in the real world, so the important distinction is between AI as a tool for informing choices and AI as an authority over collective values. The goals, tradeoffs and safeguards must come from people and legitimate public institutions.
What makes AI different from traditional analytics?
Traditional analytics often look for patterns in existing data to describe what has happened or optimize a process against established measures. That can be useful, but it also means the analysis may inherit the limits and biases of the data and the objectives already in place. The DataScienceCentral archive describes Bill Schmarzo’s April 29, 2024 essay as contrasting that backward-looking tendency with AI’s potential to focus attention on future aspirations and the learning required to move toward them. The essay’s full text was not available from the archive, so that is the extent of what can be attributed to its argument.
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“Future-oriented” does not mean AI knows which future is best. The OECD defines an AI system as machine-based and describes it as inferring from inputs how to generate outputs—such as predictions, content, recommendations or decisions—that can influence physical or virtual environments. That influence can help people consider options, but it does not give a system moral judgment or democratic legitimacy. OECD AI Principles
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Who decides what society should aspire to?
People and institutions do. A model can estimate consequences under specified assumptions, surface patterns, or generate possible approaches. It cannot settle contested questions such as whose needs should take priority, what risks are acceptable, or how benefits and costs should be shared. Those decisions require human judgment and legitimate public processes, not just a technical objective embedded in software.
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UNESCO’s Recommendation on the Ethics of Artificial Intelligence offers a values-based reference point. Adopted in November 2021 by UNESCO’s 193 Member States, it identifies human dignity and rights, just and peaceful societies, diversity and inclusion, and environmental flourishing among its core values. UNESCO summarizes its central requirement plainly: “At its core, it states that AI must respect human rights and human dignity.” UNESCO Recommendation on the Ethics of Artificial Intelligence
How can aspirations become practical criteria?
Broad ideals are more useful when translated into questions that can guide a proposal, a policy or a deployment decision. The following questions synthesize themes in UNESCO’s Recommendation and the OECD Principles; they are a practical framing, not a verbatim checklist issued by either organization.
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- Purpose and beneficiaries: What social objective is being pursued, and who is expected to benefit? Who may bear costs or be left out?
- Evidence and uncertainty: What supports the expected outcome? What assumptions, data limits or unknowns could change it?
- Rights and fairness: Could the system affect privacy, dignity, equal treatment or access to essential opportunities?
- Oversight and accountability: Who can question or override an AI-supported outcome, and who is answerable if it causes harm?
- Safety and security: What could fail or be misused, and what protections are in place?
- Sustainability and reversibility: What are the environmental or social costs, and can the intervention be changed or stopped if its effects are unacceptable?
The OECD’s principles connect trustworthy AI with inclusive growth and well-being, human rights and democratic values, transparency, safety and accountability. UNESCO also emphasizes proportionality, privacy, human oversight, fairness, sustainability, AI literacy and multi-stakeholder governance. Together, these ideas make aspirations testable without pretending every value conflict has a technical solution.
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Principles need to be paired with operational risk management. The U.S. National Institute of Standards and Technology’s AI Risk Management Framework is voluntary guidance intended to help organizations integrate trustworthiness considerations into AI design, development, use and evaluation. NIST released the framework on January 26, 2023. Its page says AI RMF 1.0 is being revised as part of the White House AI Action Plan; that revision should not be treated as complete. NIST AI Risk Management Framework
A framework can help an organization identify and manage risks, but it does not choose society’s goals or replace laws, accountability or public participation. Governance is strongest when the people affected can understand how an AI-supported process works, raise concerns, and reach a human decision-maker where appropriate. AI literacy matters for the same reason: people need enough understanding to evaluate claims about what a system can and cannot do.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What should readers conclude from the claim that AI can “guide” aspirations?
The word “guide” is defensible if it means AI can help people explore futures, anticipate effects and inform decisions. It becomes misleading if it suggests that AI independently determines what is good for society. The difference between those interpretations is not semantic: it determines who sets the objective, who is heard, and who is accountable for consequences.
Use AI to widen the evidence and options available to human decision-makers. Set the destination through human judgment and public legitimacy, then evaluate whether the system’s effects remain consistent with rights, inclusion, safety and well-being.
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