Half 3: Causality

My hope is that by the tip of this text you’ll have a superb understanding of how philosophical considering round causation applies to your work as an information scientist. Ideally you’ll have a deeper philosophical perspective to offer context to your work!

That is the third half in a multi-part collection about philosophy and knowledge science. Half 1 covers how the idea of determinism connects with knowledge science and half 2 is about how the philosophical discipline of epistemology may also help you suppose critically as an information scientist.

Introduction

I really like what number of philosophical matters take a seemingly apparent idea, like causality, and make you understand it isn’t so simple as you suppose. For instance, with out trying up a definition, attempt to outline causality off the highest of your head. That may be a troublesome activity — for me at the least! This train hopefully nudged you to comprehend that causality isn’t as black and white as you might have thought.

Here’s what this text will cowl:

1. Challenges of observing causality
2. Deterministic vs probabilistic causality
3. Regularity concept of causality
4. Course of concept of causality
5. Counterfactual concept of causality
6. Bringing all of it collectively

Causality’s Unobservability

David Hume, a well-known skeptic and one among my favourite philosophers, made the astute statement that we can not observe causality straight with our senses. Right here’s a traditional instance: we are able to see a baseball flying in the direction of the window and we are able to see the window break, however we can not see the causality straight. We can not…