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Created page with "Title: Approach Abstract: This research proposes new definitions for actual causes and explanations, using structural equations to model counterfactuals. It shows that these definitions yield a plausible and elegant account of causation and explanation, handling examples that have caused problems for other definitions and resolving major difficulties in the traditional account. Introduction: The concept of actual causality is complex and difficult to define. It is impo..."
 
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Title: Approach
Title: Approach


Abstract: This research proposes new definitions for actual causes and explanations, using structural equations to model counterfactuals. It shows that these definitions yield a plausible and elegant account of causation and explanation, handling examples that have caused problems for other definitions and resolving major difficulties in the traditional account.
Research Question: How can we quantify responsibility and blame in a structured way?


Introduction: The concept of actual causality is complex and difficult to define. It is important in various fields, such as law, artificial intelligence, and explanation generation. This paper presents a structural equation-based approach to define actual causality and explanation.
Methodology: The authors propose a structural-model approach to define responsibility and blame. They extend the causality definition introduced by Halpern and Pearl [2001a] to include the degree of responsibility of an agent. They consider counterfactual dependence and introduce the concept of degree of blame, which takes into account an agent's epistemic state.


Methodology: The methodology involves using structural equations to model counterfactuals. This approach allows for a precise and useful definition of actual causality.
Results: The authors present a definition of responsibility that allows for a distinction between different levels of responsibility. For example, they show that in an election where one candidate wins by a landslide, each voter's responsibility for the outcome is less than if the victory had been closer.


Results: The results show that the proposed definitions handle difficult examples that have caused problems for other definitions and resolve major difficulties in the traditional account.
Implications: This approach allows for a more nuanced understanding of responsibility and blame. It can help in situations where traditional all-or-nothing concepts of causality do not provide the necessary distinctions. For instance, in legal or ethical contexts, this approach could be used to assign blame more fairly and accurately.


Conclusion: In conclusion, the structural equation-based approach provides a plausible and elegant account of actual causality and explanation. It handles challenging examples and resolves long-standing difficulties in the field.
Conclusion: The authors have presented a structural-model approach to define responsibility and blame, which takes into account the degree of responsibility of an agent. This approach can provide a more nuanced understanding of responsibility and blame, particularly in situations where traditional causality concepts do not suffice.


Implications: The implications of this research are significant. It provides a clear and practical definition of actual causality and explanation, which can be applied in various fields. It also moves the debate about actual causality to the right arena, encouraging discussion about which model of the world is a better representation.
Link to Article: https://arxiv.org/abs/0312038v1
Authors:
arXiv ID: 0312038v1


Link to Article: https://arxiv.org/abs/0011012v1
[[Category:Computer Science]]
Authors:  
[[Category:Responsibility]]
arXiv ID: 0011012v1
[[Category:Blame]]
[[Category:Approach]]
[[Category:Can]]
[[Category:Authors]]

Latest revision as of 15:05, 24 December 2023

Title: Approach

Research Question: How can we quantify responsibility and blame in a structured way?

Methodology: The authors propose a structural-model approach to define responsibility and blame. They extend the causality definition introduced by Halpern and Pearl [2001a] to include the degree of responsibility of an agent. They consider counterfactual dependence and introduce the concept of degree of blame, which takes into account an agent's epistemic state.

Results: The authors present a definition of responsibility that allows for a distinction between different levels of responsibility. For example, they show that in an election where one candidate wins by a landslide, each voter's responsibility for the outcome is less than if the victory had been closer.

Implications: This approach allows for a more nuanced understanding of responsibility and blame. It can help in situations where traditional all-or-nothing concepts of causality do not provide the necessary distinctions. For instance, in legal or ethical contexts, this approach could be used to assign blame more fairly and accurately.

Conclusion: The authors have presented a structural-model approach to define responsibility and blame, which takes into account the degree of responsibility of an agent. This approach can provide a more nuanced understanding of responsibility and blame, particularly in situations where traditional causality concepts do not suffice.

Link to Article: https://arxiv.org/abs/0312038v1 Authors: arXiv ID: 0312038v1

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