Philosophy of Computing: Themes from IACAP 2019 (Philosophical Studies Series, 143)

✍ Scribed by Björn Lundgren (editor), Nancy Abigail Nuñez Hernández (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 264
• Category: Library

✦ Synopsis

This book features a unique selection of works presented at the 2019 annual international conference of the International Association for Computing and Philosophy (IACAP). Every contribution has been peer-reviewed, revised, and extended. The included chapters are thematically diverse; topics include epistemology, dynamic epistemic logic, topology, philosophy of science and computation, game theory and abductive inferences, automated reasoning and mathematical proofs, computer simulations, scientific modelling, applied ethics, pedagogy, human-robot interactions, and big data, algorithms, and artificial intelligence.
The volume is a testament to the value of interdisciplinary approaches to the computational and informational turn. We live in a time of tremendous development, which requires rigorous reflection on the philosophical nature of these technologies and how they are changing the world. How can we understand these technologies? How do these technologies change our understanding of the world? And how do these technologies affect our place as humans in the world? These questions, and more, are addressed in this volume which is of interest to philosophers, engineers, and computer scientists alike.

✦ Table of Contents

Foreword
Preface
References
Contents
1 Knowledge and Simplicial Complexes
1.1 Introduction
1.2 An Informal Introduction to Epistemic Logic on Simplicial Complexes
1.3 Logical and Topological Tools
1.3.1 Logical Tools
1.3.2 Topological Tools
1.3.3 Epistemic Logic on Simplicial Models
1.4 Bisimulation for Simplicial Complexes
1.4.1 Bisimulation
1.4.2 Why Defining Bisimulation Between Vertices Does Not Work
1.4.3 Elementary Results for Bisimulation
1.4.4 Subdivision and Bisimulation
1.4.5 Covering Complex and Bisimulation
1.5 Local Semantics for Simplicial Complexes
1.5.1 From Semantics for Facets to Semantics for Simplices
1.5.2 A Semantics for Simplices Including Facets
1.6 Group Epistemic Notions for Simplicial Complexes
1.6.1 Mutual, Common, and Distributed Knowledge
1.6.2 Common Distributed Knowledge for Simplicial Complexes
1.6.3 Bisimulation for Distributed Knowledge
1.7 Belief for Simplicial Complexes
1.8 Simplicial Action Models
1.9 From Global to Local Epistemic Models
1.10 Conclusion and Further Research
References
2 Meta-Abduction: Inference to the Probabilistically Best Prediction
2.1 Introduction
2.2 Abduction
2.3 Inference to the Probabilistically Best Explanation
2.4 Simplicity and the Akaike Information Criterion
2.5 Meta-Induction and the Justification of Induction
2.6 Meta-Abduction: Inference to the Probabilistically Best Prediction
2.7 Conclusion
References
3 On the Conciliation of Traditional and Computer-Assisted Proofs
3.1 Introduction
3.2 An Overview of Computer-Assisted Proofs: The Case of Coq
3.3 Transitional Proofs
3.4 A Notion of Formal Backward Proof
3.5 A Case Study on Modal Logic
3.6 Discussion
Appendix: CAP Counterparts for No Natural Between 0 and 1
References
4 Is There Anything Special About the Ignorance Involved in Big Data Practices?
4.1 Introduction
4.2 Epistemological Worries About Big Data
4.2.1 Preliminaries
4.2.2 The Methodological Worries
4.2.3 But, Why Big Data?
4.2.4 The Understanding-Directed Worries
4.3 Types of Ignorance
4.3.1 A Common Ground
4.3.2 Ignorance(s)
4.4 Big Data, Big Ignorance?
4.4.1 The Landscape
4.4.2 The Ignorance Behind Big Data
4.4.3 Understanding Big Data
4.5 Cosmology and Big Data
4.5.1 The Story
4.5.2 Evaluating the Case Study
4.6 Final Remarks
References
5 Predictive Fairness
5.1 Necessary Biases
5.2 Possible Solutions
5.3 Accepting Biases
5.4 Concluding Remarks
References
6 Castigation by Robot: Should Robots Be Allowed to Punish Us?
6.1 Introduction
6.2 Authoritative Roles for Robots
6.3 The Necessity of Punishment
6.4 Applications Potentially Warranting Robot Punishment
6.5 Ethical Justification and Limitations of Robot Punishment
6.6 Conclusions
References
7 Implementing Algorithmic and Computational Design in Philosophical Pedagogy
7.1 Introduction
7.2 Situating Philosophy Within the Digital Humanities
7.2.1 Algorithms and Algorithmic Elaboration
7.2.2 Philosophy's Special Role in the Digital Humanities
7.3 Pedagogical Virtues of Diagrammatic Methods
7.4 Three Compositional Diagrammatic Examples
7.4.1 Introduction to Philosophy: Argument Diagrams
7.4.2 Modern Philosophy: Conceptual Algorithms
7.4.3 Contemporary Philosophy: Wiring Diagrams
7.5 Analysis and Prognosis
7.5.1 From Visualization to Formalization
7.5.2 Integrating Philosophical Pedagogy and Research
7.6 Conclusion
References
8 Our Technology Fetish
8.1 Introduction
8.1.1 What Is Technology?
8.1.2 What Is the Fetish?
8.2 Evidence of a Fetish
8.2.1 Monitoring and Surveillance Technology
8.3 Can and Should Anything Be Done?
8.4 Where to from Here?
8.5 Conclusion
References
9 Models, Explanation, Representation, and the Philosophy of Computer Simulations
9.1 Introduction
9.2 The Received View of Simulation Models
9.2.1 The Reception of the Received View of Simulation Models
9.3 The Syntax of Simulation Models
9.3.1 A Response by the Received View
9.4 Three Examples of Computer Simulations
9.4.1 Example I: Simulating an Orbiting Satellite
9.4.2 Example II and III: Simulating Highly Infectious Outbreak Dynamics
9.5 Why Should We Care? Explanation and Representation
9.5.1 A Logic of Scientific Explanation that Accounts for Computer Simulations
9.5.2 A Theory of Representation for Computer Simulations
9.6 Final Remarks: A Very Short Proposal for a Philosophy of Computer Simulations
References
Index