Introduction
The modern world is facing a paradox: while our power to transform reality grows, our ability to predict the consequences of those changes is drastically declining. In the face of advancements in AI and biotechnology, the future is becoming illegible.
The reader will discover why traditional forecasting fails and how to replace it with strategic anticipation. This article explains how to build institutional resilience rather than searching for a single, optimal path of development in a world of deep uncertainty.
From Naive Forecasting to Strategic Anticipation
Classical forecasting fails in complex systems where human reactions and technological breakthroughs change the rules of the game. It is no longer enough to ask what is most likely to happen.
The solution is strategic foresight. Instead of a single version of tomorrow, it explores multiple plausible scenarios, utilizing tools such as horizon scanning and backcasting.
An example of this is the futures literacy promoted by UNESCO. This is the ability to use images of the future to better understand uncertainty and make wiser decisions in the present.
The Trap of Linear Thinking Regarding Progress
A common error is treating the future as today's world equipped with more efficient tools. This is a naive extrapolation, suggesting that AI is simply current algorithms made a thousand times more powerful.
In reality, breakthroughs do not consist of intensifying existing features, but of changing the architecture of solutions. The author illustrates this with the metaphor of airplanes with twelve wings—more wings do not make a machine better if the fundamental principle of flight changes.
Understanding this mechanism allows us to avoid technological determinism. Technical development is not an autonomous process; it is society that decides on the funding and legal norms that steer progress.
From Optimization to Resilience in the Face of Deep Uncertainty
It is crucial to distinguish between risk and deep uncertainty. Risk can be estimated statistically, whereas uncertainty occurs when we do not even know the catalog of possible outcomes.
In such an environment, striving for optimization is dangerous because it relies on a single model of the world. We must move toward building resilience, designing systems that remain safe across many different scenarios.
This approach protects against the trap of feasibility. The fact that something is technically possible does not mean it is desirable. Decisions should be based on values and an analysis of the asymmetry of consequences, rather than efficiency alone.
Summary
The future is not an empty space, but a field of competition between different projects. To avoid the dominance of particular capital interests, we must institutionalize agency and the ethics of responsibility.
By designing tools to modify our own bodies and minds, we cease to be merely products of evolution and become its architects. The question remains: who must we remain as humans to still possess the moral right and capacity to decide who we want to become?
👤 About the book's author
A C Grayling
Northeastern University London
Anthony Clifford Grayling (born 1949) is a British philosopher and author. He is Professor of Philosophy and the founding Master of New College of the Humanities (now Northeastern University London), as well as a Supernumerary Fellow of St Anne's College, Oxford. He previously served as Professor of Philosophy at Birkbeck, University of London. Grayling specializes in epistemology, metaphysics, philosophical logic, and ethics. As a prominent public intellectual and proponent of secular humanism, he has contributed extensively to public discourse on human rights, democratic governance, civil liberties, and the history of ideas. In addition to technical work on philosophical scepticism and realism, Grayling has published more than thirty books aimed at bringing philosophy, critical inquiry, and ethical reflection to a broad global audience.
Frequently Asked Questions
Why is traditional forecasting insufficient in today's times, and what should replace it?
Traditional forecasting is insufficient because the pace of contemporary change outstrips societies' ability to predict its effects, and the future has become 'illegible.' It should be replaced by a foresight approach and futures literacy, which, instead of one version of tomorrow, explore many possible scenarios and use imaginings of the future as a tool for making decisions in the present.
1. Is the future simply current technology in a more efficient version?
2. No, the future does not consist solely of increasing the efficiency of current technologies. As with AI, transport, or education, it is a mistake to assume that the future is merely current solutions implemented more smoothly or powerfully.
3. What is the difference between risk management and dealing with deep uncertainty in the context of future technologies?
4. Risk management is applied when possible outcomes and their probabilities can be estimated, whereas deep uncertainty occurs when there is a lack of agreement regarding causal models, system parameters, or outcome evaluation criteria. In situations of deep uncertainty, standard prediction techniques lose their effectiveness because unknown variables cannot be reliably described by probability distributions.
5. Since the future is unpredictable, does that mean every scenario is equally probable?
6. No, the uncertainty of the future does not mean that every scenario is equally plausible. Reliable forecasting must be based on argumentative discipline and knowledge of trends, physical constraints, and signals of change, rather than on free fantasy.
7. Why does the fact that something is technically possible not mean it is desirable, and who actually decides which vision of the future will be realized?
8. The decision as to which vision of the future will be realized is made by entities possessing capital, infrastructure, and influence over regulators, as they can transform their own goals into material reality. The fact that something is technically possible does not mean it is desirable; however, according to "Grayling's Law," feasible solutions have a strong tendency to be implemented if they benefit the entities with the means to deploy them.
9. Is technological development inevitable and independent of human will?
10. Technological development is neither an autonomous process nor one independent of human will, but rather the result of technology itself, institutions, and adopted values. It is society that shapes the direction of change, deciding, among other things, on funding, property law, safety standards, and the permissibility of experiments.
How to move from passive prediction of the future to actively shaping it based on values?
The backcasting method should be applied, which consists of defining a desired future state based on adopted values and analyzing the conditions necessary to achieve it. This requires combining epistemic discipline (data verification) with axiological discipline, meaning the explicit identification of the goods we wish to protect.
How to avoid technological determinism in a world of radical uncertainty?
The capacity for learning must be institutionalized by noticing weak signals, conducting experiments, and ensuring a pluralism of knowledge. It is crucial to build anticipatory governance that systematically tests assumptions and creates relationships between technology and values to maintain the ability to choose goals.
