Decision-making under uncertainty.
Many important decisions must be made before uncertainty disappears. Philosophy, finance, behavioral economics and institutional experience offer different tools for dealing with that fact — without promising what no method can deliver: complete certainty.
The problem is not to choose between “certainty” and “ignorance”. It is to learn to distinguish degrees of knowledge, risk, hypothesis, judgment and what remains open.
Deciding does not mean waiting until every doubt has disappeared.
In many contexts, postponing a decision until perfect information is available is not a real option. Markets change, projects must move forward, extreme events require responses, careers evolve, and human relationships do not offer complete probabilities.
Rationality, in such cases, does not consist in manufacturing certainty. It consists in organizing what we know, acknowledging what we do not know, making assumptions visible, comparing alternatives, and accepting that some decisions will remain open to revision.
The same problem seen through different traditions.
None of these perspectives solves decision-making on its own. What matters is precisely what happens when they correct and limit one another.
Skepticism & judgment
Skepticism helps us distrust the rush to turn belief into certainty and preserve room for inquiry, revision and experience.
Biases & forecasting
Behavioral economics shows that judgment and forecasting can be systematically shaped by shortcuts, framing, overconfidence and other patterns.
Risk & scenarios
Financial models make it possible to quantify parts of the problem, compare scenarios and make assumptions explicit — without turning the model into the world itself.
Coordination & consequences
Public and organizational decisions involve multiple actors, time horizons, responsibilities and effects that cannot be reduced to a single objective function.
Not all uncertainty behaves like calculable risk.
Probabilities, data and scenarios can help a great deal.
There are situations in which frequencies, distributions, sensitivities and scenarios allow alternatives to be compared in a disciplined way. Even then, decision quality depends on assumptions and on how results are interpreted.
Judgment remains unavoidable.
Some decisions involve novelty, structural change, conflicting values or effects that are difficult to measure. In such cases, assigning a number may organize the problem — but it does not dissolve uncertainty.
Five movements before, during and after the choice.
This is not a universal formula. It is a discipline of inquiry that can reduce blind spots without pretending to eliminate contingency.
Define the problem
Before looking for an answer, ask what decision actually needs to be made, by whom, over what horizon and under what constraints.
Separate knowledge from assumption
Distinguish facts, estimates, inferences, hypotheses and gaps. Clarity about the degree of knowledge prevents rhetorical confidence from being mistaken for evidence.
Make criteria explicit
Identify what counts as success, which values are involved, who bears the costs, and which consequences are absent from the main indicator.
Compare alternatives and scenarios
Use models, probabilities and sensitivities when they are informative — and also discuss what remains outside them.
Decide while remaining open to revision
A good decision need not be irrevocable. When new information appears, revising a choice can be a sign of rationality rather than weakness.
Doubt need not mean paralysis.
A practical reading of skepticism can contribute to decision-making precisely because it removes from rationality the obligation to produce certainty where none exists.
This does not make “any choice” a reasonable one. On the contrary: it requires examining reasons, confronting positions, distinguishing evidence from the appearance of evidence, and remaining available for correction.
Between dogmatism and paralysis lies a field of provisional, responsible and revisable judgment.
Different contexts, similar structure.
The concrete content changes, but the need to decide with incomplete information reappears across several areas of my work.
Capital, risk and return
Valuation, scenarios and probabilities help compare choices without eliminating uncertainty about the future.
Strategy and behavior
Business decisions combine incentives, biases, imperfect data and effects that emerge over different time horizons.
Response and resilience
Extreme events and reconstruction require urgent action involving multiple actors and long-term consequences.
Choices without an algorithm
Career, transitions and conflicts of values also require judgment when no calculation can provide the answer.
One central question, different areas of the site.
Philosophy & Pesquisa
Skepticism, Montaigne, experience, judgment and action without ultimate foundations.
Explore →Education
How to form judgment in finance, investments, sustainability and behavioral economics.
Explore →Professional Work
Engineering, development, climate and reparation in highly complex environments.
Explore →Uncertainty is not the absence of thought.
Precisely when there is no complete guarantee, it becomes more important to examine how we judge, which models we use and what reasons support our choices.
Translated essays
Four essays available in English that deepen the work on skepticism, uncertainty and practical philosophy.