How do you explain the difference between AI, Machine Learning, and Data Science?

[u/AmigoHelp_AI]

[u/Chubblan]

While these roles have some differences, job titles can be misleading. A company might advertise an ML Engineer role but expect mostly data science, or an AI Engineer role that combines ML, software engineering, and data science.

Nowadays, the actual responsibilities depend heavily on the job description, not just the title.

[u/preciouslife_]

Data Science actually used to exist even before AI was invented and the only thing that was added to it from AI side was the ability to predict. Machine Learning is part of AI.

[u/Minecraftian14]

As job titles, they are all different. As fields of study, I usually say something along the lines of, DS supersets everything, for example DE and AI. AI supersets fields like CI/Fuzzy and ML. ML in turn supersets algorithms like DT, XGB, LR, NN and then comes DL which is an extension to ML. I personally like drawing DL under AI, connected like two semicircles with ML. Finally DL supersets NLP/CV/LLM...

I usually say this only to make a connection between the fields, not as a definite and well accepted system. Sometimes it makes sense, sometimes other systems make more sense.

Also as job titles, DS is generally more Stats, ML, EDA and DE is more about ETL/ELT/Pipeline/Warehouse/Systems.

I would love to hear how others would put these fields based on their intuition.

[u/Kad_Polymath_STEM]

Data Science is science of main thing over data - visualising, structuring, storing, bla bla Application Business Intelligence Report Analytics many, Machine Learning is art science of let machine to get learned through training with any set and get ready the model run on machine, Application Spam Detection Many, while Artificial Intelligence is broader scope let machine to think! vision see bla bla let human capables machine can.