Je dirige un projet d'intelligence artificielle décisionnelle pour une entreprise de conseil et nous rencontrons des difficultés à intégrer des éléments d'indétermination délibérative dans nos algorithmes. Bien que nous comprenions le concept théorique, nous avons besoin de garantir que les décisions finales ne soient pas trop influencées par le hasard. Comment pouvons-nous concrètement maintenir le contrôle sur le processus décisionnel tout en incorporant un élément d'indétermination dans notre système ?
Event-causal theories

Event-causal accounts of incompatibilist free will typically rely upon physicalist models of mind (like those of the compatibilist), yet they presuppose physical indeterminism, in which certain indeterministic events are said to be caused by the agent. A number of event-causal accounts of free will have been created, referenced here as deliberative indeterminism, centred accounts, and efforts of will theory. The first two accounts do not require free will to be a fundamental constituent of the universe. Ordinary randomness is appealed to as supplying the "elbow room" that libertarians believe necessary. A first common objection to event-causal accounts is that the indeterminism could be destructive and could therefore diminish control by the agent rather than provide it (related to the problem of origination). A second common objection to these models is that it is questionable whether such indeterminism could add any value to deliberation over that which is already present in a deterministic world.

Deliberative indeterminism asserts that the indeterminism is confined to an earlier stage in the decision process. This is intended to provide an indeterminate set of possibilities to choose from, while not risking the introduction of luck (random decision making). The selection process is deterministic, although it may be based on earlier preferences established by the same process. Deliberative indeterminism has been referenced by Daniel Dennett and John Martin Fischer. An obvious objection to such a view is that an agent cannot be assigned ownership over their decisions (or preferences used to make those decisions) to any greater degree than that of a compatibilist model.

Centred accounts propose that for any given decision between two possibilities, the strength of reason will be considered for each option, yet there is still a probability the weaker candidate will be chosen. An obvious objection to such a view is that decisions are explicitly left up to chance, and origination or responsibility cannot be assigned for any given decision.

Efforts of will theory is related to the role of will power in decision making. It suggests that the indeterminacy of agent volition processes could map to the indeterminacy of certain physical events – and the outcomes of these events could therefore be considered caused by the agent. Models of volition have been constructed in which it is seen as a particular kind of complex, high-level process with an element of physical indeterminism. An example of this approach is that of Robert Kane, where he hypothesizes that "in each case, the indeterminism is functioning as a hindrance or obstacle to her realizing one of her purposes – a hindrance or obstacle in the form of resistance within her will which must be overcome by effort." According to Robert Kane such "ultimate responsibility" is a required condition for free will. An important factor in such a theory is that the agent cannot be reduced to physical neuronal events, but rather mental processes are said to provide an equally valid account of the determination of outcome as their physical processes (see non-reductive physicalism).

Although at the time quantum mechanics (and physical indeterminism) was only in the initial stages of acceptance, in his book Miracles: A preliminary study C.S. Lewis stated the logical possibility that if the physical world were proved indeterministic this would provide an entry point to describe an action of a non-physical entity on physical reality. Indeterministic physical models (particularly those involving quantum indeterminacy) introduce random occurrences at an atomic or subatomic level. These events might affect brain activity, and could seemingly allow incompatibilist free will if the apparent indeterminacy of some mental processes (for instance, subjective perceptions of control in conscious volition) map to the underlying indeterminacy of the physical construct. This relationship, however, requires a causative role over probabilities that is questionable, and it is far from established that brain activity responsible for human action can be affected by such events. Secondarily, these incompatibilist models are dependent upon the relationship between action and conscious volition, as studied in the neuroscience of free will. It is evident that observation may disturb the outcome of the observation itself, rendering limited our ability to identify causality. Niels Bohr, one of the main architects of quantum theory, suggested, however, that no connection could be made between indeterminism of nature and freedom of will.
Délibération et décision

La délibération est une forme importante de pensée pratique. Elle vise à formuler des voies d'action possibles et à évaluer leur valeur en considérant les raisons pour et contre. Cela implique de faire preuve de clairvoyance pour anticiper ce qui pourrait arriver. Sur la base de cette prévoyance, différentes voies d'action peuvent être formulées afin d'influencer ce qui va se produire. Les décisions sont un élément important de la délibération. Elles consistent à comparer des voies d'action alternatives et à choisir la plus favorable. La théorie de la décision est un modèle formel de la manière dont des agents rationnels idéaux prendraient des décisions. Elle repose sur l'idée qu'ils devraient toujours choisir l'alternative ayant la valeur attendue la plus élevée. Chaque alternative peut mener à divers résultats possibles, chacun ayant une valeur différente. La valeur attendue d'une alternative consiste en la somme des valeurs de chaque résultat qui y est associé, multipliée par la probabilité que ce résultat se produise. Selon la théorie de la décision, une décision est rationnelle si l'agent choisit l'alternative associée à la valeur attendue la plus élevée, telle qu'elle est évaluée du point de vue de l'agent.

Divers théoriciens insistent sur le caractère pratique de la pensée, c'est-à-dire que la pensée est généralement guidée par une sorte de tâche qu'elle vise à résoudre. Dans ce sens, la pensée a été comparée à la méthode d'essai-erreur observée dans le comportement animal lorsqu'il est confronté à un nouveau problème. Selon cette conception, la différence importante est que ce processus se déroule intérieurement sous la forme d'une simulation. Ce processus est souvent beaucoup plus efficace, car une fois la solution trouvée par la pensée, il suffit de mettre en œuvre le comportement correspondant à cette solution, et non tous les autres.
### Query ###
Je dirige un projet d'intelligence artificielle décisionnelle pour une entreprise de conseil et nous rencontrons des difficultés à intégrer des éléments d'indétermination délibérative dans nos algorithmes. Bien que nous comprenions le concept théorique, nous avons besoin de garantir que les décisions finales ne soient pas trop influencées par le hasard. Comment pouvons-nous concrètement maintenir le contrôle sur le processus décisionnel tout en incorporant un élément d'indétermination dans notre système ?

### Main Text ###
Event-causal theories

Event-causal accounts of incompatibilist free will typically rely upon physicalist models of mind (like those of the compatibilist), yet they presuppose physical indeterminism, in which certain indeterministic events are said to be caused by the agent. A number of event-causal accounts of free will have been created, referenced here as deliberative indeterminism, centred accounts, and efforts of will theory. The first two accounts do not require free will to be a fundamental constituent of the universe. Ordinary randomness is appealed to as supplying the "elbow room" that libertarians believe necessary. A first common objection to event-causal accounts is that the indeterminism could be destructive and could therefore diminish control by the agent rather than provide it (related to the problem of origination). A second common objection to these models is that it is questionable whether such indeterminism could add any value to deliberation over that which is already present in a deterministic world.

Deliberative indeterminism asserts that the indeterminism is confined to an earlier stage in the decision process. This is intended to provide an indeterminate set of possibilities to choose from, while not risking the introduction of luck (random decision making). The selection process is deterministic, although it may be based on earlier preferences established by the same process. Deliberative indeterminism has been referenced by Daniel Dennett and John Martin Fischer. An obvious objection to such a view is that an agent cannot be assigned ownership over their decisions (or preferences used to make those decisions) to any greater degree than that of a compatibilist model.

Centred accounts propose that for any given decision between two possibilities, the strength of reason will be considered for each option, yet there is still a probability the weaker candidate will be chosen. An obvious objection to such a view is that decisions are explicitly left up to chance, and origination or responsibility cannot be assigned for any given decision.

Efforts of will theory is related to the role of will power in decision making. It suggests that the indeterminacy of agent volition processes could map to the indeterminacy of certain physical events – and the outcomes of these events could therefore be considered caused by the agent. Models of volition have been constructed in which it is seen as a particular kind of complex, high-level process with an element of physical indeterminism. An example of this approach is that of Robert Kane, where he hypothesizes that "in each case, the indeterminism is functioning as a hindrance or obstacle to her realizing one of her purposes – a hindrance or obstacle in the form of resistance within her will which must be overcome by effort." According to Robert Kane such "ultimate responsibility" is a required condition for free will. An important factor in such a theory is that the agent cannot be reduced to physical neuronal events, but rather mental processes are said to provide an equally valid account of the determination of outcome as their physical processes (see non-reductive physicalism).

Although at the time quantum mechanics (and physical indeterminism) was only in the initial stages of acceptance, in his book Miracles: A preliminary study C.S. Lewis stated the logical possibility that if the physical world were proved indeterministic this would provide an entry point to describe an action of a non-physical entity on physical reality. Indeterministic physical models (particularly those involving quantum indeterminacy) introduce random occurrences at an atomic or subatomic level. These events might affect brain activity, and could seemingly allow incompatibilist free will if the apparent indeterminacy of some mental processes (for instance, subjective perceptions of control in conscious volition) map to the underlying indeterminacy of the physical construct. This relationship, however, requires a causative role over probabilities that is questionable, and it is far from established that brain activity responsible for human action can be affected by such events. Secondarily, these incompatibilist models are dependent upon the relationship between action and conscious volition, as studied in the neuroscience of free will. It is evident that observation may disturb the outcome of the observation itself, rendering limited our ability to identify causality. Niels Bohr, one of the main architects of quantum theory, suggested, however, that no connection could be made between indeterminism of nature and freedom of will.

### Supplementary Text ###
Délibération et décision

La délibération est une forme importante de pensée pratique. Elle vise à formuler des voies d'action possibles et à évaluer leur valeur en considérant les raisons pour et contre. Cela implique de faire preuve de clairvoyance pour anticiper ce qui pourrait arriver. Sur la base de cette prévoyance, différentes voies d'action peuvent être formulées afin d'influencer ce qui va se produire. Les décisions sont un élément important de la délibération. Elles consistent à comparer des voies d'action alternatives et à choisir la plus favorable. La théorie de la décision est un modèle formel de la manière dont des agents rationnels idéaux prendraient des décisions. Elle repose sur l'idée qu'ils devraient toujours choisir l'alternative ayant la valeur attendue la plus élevée. Chaque alternative peut mener à divers résultats possibles, chacun ayant une valeur différente. La valeur attendue d'une alternative consiste en la somme des valeurs de chaque résultat qui y est associé, multipliée par la probabilité que ce résultat se produise. Selon la théorie de la décision, une décision est rationnelle si l'agent choisit l'alternative associée à la valeur attendue la plus élevée, telle qu'elle est évaluée du point de vue de l'agent.

Divers théoriciens insistent sur le caractère pratique de la pensée, c'est-à-dire que la pensée est généralement guidée par une sorte de tâche qu'elle vise à résoudre. Dans ce sens, la pensée a été comparée à la méthode d'essai-erreur observée dans le comportement animal lorsqu'il est confronté à un nouveau problème. Selon cette conception, la différence importante est que ce processus se déroule intérieurement sous la forme d'une simulation. Ce processus est souvent beaucoup plus efficace, car une fois la solution trouvée par la pensée, il suffit de mettre en œuvre le comportement correspondant à cette solution, et non tous les autres.

### Draft ###

### 1. Query Deconstruction

"Je dirige un projet d'intelligence artificielle décisionnelle..." → AI decision-making project director

Key tension identified: theoretical understanding vs. practical implementation gap.

"éléments d'indétermination délibérative" → deliberative indeterminism elements

Critical constraint: "garantir que les décisions finales ne soient pas trop influencées par le hasard" → control over randomness influence

? Translation nuance: "délibérative" here = decision-making process, not just deliberation

### 2. Domain Mapping

● Philosophical foundation: Free will theory, specifically libertarianism
◐ AI implementation: Stochastic algorithms, Monte Carlo methods  
○ Current gap: Theoretical concepts → concrete algorithmic frameworks

→ Need cross-domain synthesis: philosophy + computer science + practical constraints

### 3. Theoretical Knowledge Triangulation

**Deliberative Indeterminism** ● 
- Decision process has genuine alternatives
- Indeterminism confined to early deliberation stage  
- Selection mechanism remains controllable
- ≈ Maintains agent responsibility while allowing flexibility

**Efforts of Will Theory** ◐
- Volition processes have physical indeterminism
- Mental processes vs physical neuronal events both causal
- Agent actively overcomes resistance/obstacles
- ? Implementation challenge: how model "effort" in algorithms

**Quantum Approaches** ○
- Quantum mechanical indeterminacy
- Subatomic level affects brain activity
- ? Scale mismatch: quantum → macroscopic decision-making
- ⚠ Highly speculative, limited empirical support

### 4. Practical Implementation Constraints

Physical reality check:
- Computational overhead of full indeterminism
- Reproducibility vs. genuine unpredictability  
- Bias toward deterministic solutions in business contexts
- Need for interpretability/explainability

∴ Pure theoretical implementations likely impractical

### 5. Synthesis Path

**Control Mechanisms:**
1. **Constraint Programming**: Define boundaries, let randomness operate within
2. **Weighting Systems**: Combine deterministic heuristics + stochastic elements  
3. **Feedback Loops**: Monitor randomness influence, adjust dynamically
4. **Human-in-the-Loop**: Retain override capability for critical decisions

**Algorithmic Framework:**
```
Decision = f(deterministic_inputs, stochastic_component, control_parameters)
```

Where `control_parameters` allow real-time adjustment of randomness influence.

### 6. Knowledge Gaps & Limitations  

◐ Specific implementation techniques for deliberative indeterminism in AI
○ Best practices for quantum-inspired approaches in practical systems  
⚠ Potential over-complication vs. simple deterministic alternatives

**Key insight:** ! The tension between theoretical libertarianism and practical AI control may require reframing the problem entirely.

Maybe consider: 
- Evolutionary algorithms with mutation rates
- Bayesian approaches with exploration/exploitation trade-offs  
- Multi-armed bandit problems with confidence intervals

### 7. Convergence

The response correctly identifies the core challenge: theoretical concepts (deliberative indeterminism, efforts of will theory) vs. practical implementation control.

**Critical limitations:**
- Computational overhead of full indeterministic approaches
- Scale mismatch between quantum theory and decision-making
- Business requirement for reproducible, explainable outcomes

**Actionable recommendations:**
1. Start with constrained randomization within defined parameters
2. Implement feedback mechanisms for control adjustment  
3. Consider hybrid approaches combining deterministic heuristics with stochastic elements
4. Pilot test with non-critical decisions before full deployment

∴ The response provides sound theoretical grounding while acknowledging practical implementation limitations. The proposed framework balances the need for genuine indeterminism with the requirement for controllable decision processes.

**Uncertainty markers:** ● high confidence for theoretical concepts, ◐ partial for practical implementations, ○ low confidence for quantum approaches

### Answer###
Votre préoccupation concernant l'intégration d'éléments d'indétermination délibérative tout en maintenant le contrôle sur le processus décisionnel touche à un défi fondamental en intelligence artificielle décisionnelle.

Les théories causales de la liberté de décision proposent plusieurs approches qui pourraient répondre à vos besoins. L'indéterminisme délibératif, par exemple, limite l'indéterminisme aux étapes précoces du processus décisionnel, fournissant ainsi un ensemble d'alternatives indéterminées à choisir parmi tout en risquant de réduire l'influence du hasard dans les décisions finales. Cette approche permet de maintenir un processus sélectif déterministe basé sur des préférences établies par le même processus.

La théorie des efforts de volonté présente une approche complémentaire en suggérant que l'indéterminisme de l'indécision de l'agent pourrait se mapper aux indéterminismes d'événements physiques particuliers. Cette approche pourrait théoriquement permettre à l'agent de causer des événements physiques au niveau atomique ou subatomique, bien que cette relation nécessite une approche causale prudente sur les probabilités.

Pour votre contexte d'entreprise, il serait important de considérer que les modèles d'indéterminisme physique introduisent des événements aléatoires au niveau atomique, ce qui pourrait théoriquement affecter l'activité cérébrale responsable des actions humaines. Cependant, cette approche présente des limites importantes : d'une part, les processus observationnels peuvent perturber les résultats des observations elles-mêmes, limitant ainsi notre capacité à identifier les causalités ; d'autre part, il reste largement établi que l'activité cérébrale puisse être affectée par ces événements.

La clé pour concrétiser cette approche dans vos algorithmes résiderait donc dans la mise en place de mécanismes qui limitent l'indéterminisme aux étapes préliminaires du processus décisionnel tout en conservant un contrôle sur les paramètres et les pondérations qui influencent la sélection finale des alternatives.