Philosophy and Information Science — Considering Deeply about Information | by Jarom Hulet | Jan, 2024


Thank you for reading this post, don't forget to subscribe!

Half 3: Causality

Jarom Hulet

Towards Data Science
Picture by Cottonbro Studios from Pexels.com

My hope is that by the top of this text you should have an excellent understanding of how philosophical pondering round causation applies to your work as a knowledge scientist. Ideally you should have a deeper philosophical perspective to present context to your work!

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

Introduction

I really like what number of philosophical subjects take a seemingly apparent idea, like causality, and make you notice it’s not so simple as you assume. For instance, with out wanting up a definition, attempt to outline causality off the highest of your head. That could be a tough activity — for me a minimum of! This train hopefully nudged you to comprehend that causality isn’t as black and white as you’ll 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 certainly one of my favourite philosophers, made the astute commentary that we can’t observe causality straight with our senses. Right here’s a basic instance: we will see a baseball flying in the direction of the window and we will see the window break, however we can’t see the causality straight. We can’t…



Leave a Reply

Your email address will not be published. Required fields are marked *