AI And Data Science - What Is The Difference? Posted on : Nov 10 - 2022

AI is everywhere. The advances in AI have benefited virtually every commercial industry - but there is as much (or more!) hype about AI as there is real AI. In the midst of this are the terms - AI, Data Science, Machine Learning, Deep Learning, etc. - that are adding to the confusion. In this post, I offer perspective on two of these terms - AI and Data Science, and what they (commonly) mean relative to each other.

What is AI?

Artificial Intelligence (AI) is an umbrella term for any technology where a computer program is attempting tasks that come naturally to the human brain. Skills such as understanding written language, detecting speech, recognizing objects from images, and making plans to optimize time, are all examples of intelligence that humans display every day. Most are learned by our brains naturally as we grow and interact with the world around us, and are then refined and advanced by formal learning.

These tasks come naturally to humans but are quite challenging for computers. Computer algorithms (ways to structure programs) that can learn and perform these tasks are usually classified as AI.

What is Data Science?

In the same way that AI is an umbrella term for intelligence, Data Science is an umbrella term for insights from data. Data Science is a set of methods and practices for gathering insights (information, learnings, etc.) from data. The data can be anything (stock prices, voice recordings, sensor data from rainfall meters, satellite images, etc.). Data Science can include processing the data, performing statistical analysis of the data, presenting the data in ways that others can understand (called data storytelling), and so on. Sometimes these analyses are simple (like average rainfall). Sometimes they are far more complex. But it is all data science. View More