Automation Vs. Artificial Intelligence

Artifical Intellignece Jan 07, 2022

These terms are highly trending in the current world. However, there are often misconceptions about the both. For one, Artificial Intelligence is more than automation. This article has been prepared by subject matter experts to give a comprehensive view into each section. That is, the concepts of Automation as well as AI will be explained clearly along with their differences. The objective of SchoolforAI is to impart the most complex knowledge in a simple and direct fashion. Here we go.

Automation

The definition of automation is evident in its name. It is the use of technology or other tools to automate tasks; that is complete jobs with minimum or no human intervention. Let us consider some real-life examples. You wake up late because you feel comfortable in bed? What if your fan/air conditioner could automatically get switched off at 6:00 am in the morning? Won’t that force you to wake up? That’s the simplest form of automation.

Now let us get a little more professional. What about automation in workplaces and/or industries? What if machines (especially those used in manufacturing units) could process themselves automatically? For example, have you seen or heard about a factory that manufactures cool drinks? Different machines are made to pick raw material, mold bottles from glass or plastic, cool them, and then fill drinks. Human intervention or rather human instructions are needed at every stage. A person switches on the machine makes it pick raw material and controls the entire process until the final creation of the cool-drink. Automation enables a machine to do all this for thousands of bottles in the shortest time and with accuracy.

Which Industries Can We Use Automation?

The biggest advantage is that automation requires minimum or no supervision to accompany a task. Hence, it can be applied to several mundane or repetitive tasks, which could take a lot of time. For example, welding, bolting, and painting in an automobile manufacturing unit could be automated. could be assigned to automation and surprisingly they could do the job with more precision, higher speeds, and 24x7. In the past automation has greatly reduced the number of workers required in the manufacturing industry.

Manufacturing
IT
Defence
Transport
Customer Support
Public Service
And More!

Automation is also applicable to various industries including IT where automation is widely used in software testing, service support, data backup & restoration and so on. Hence, we could say that automation is not only those physical moving Robot arms but also software that silently completes the task.

Artificial Intelligence

The simplest definition of AI is that machines are made to imitate human actions with a few sets of instructions. Think of the concept like this. What if you could teach a system or machine to give a correct response when someone asks, “What is the time?” Or, or get a machine to hand you a cup of water when you say you are feeling thirsty? That’s AI for you! Some applications of AI are:

Expert Systems- An expert system is a computer program that is designed to solve complex problems. It also has decision making abilities like a human expert. That is, a computer program can understand logic. For example, a patient who is 37 years old, 5 ft 8 inches height and 75 kgs weight wishes to know how to stay fit. An expert system can immediately diagnose the patient and refer to tons of records on the patient’s health history to give an apt solution. There will be no need to supervise the patient’s health for a long time and/or check several files for the same. Everything can be completed in seconds with the help of expert systems.
Natural Language Processing – Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that enables machines to understand the human language. To understand, we must consider normal human languages such as English, Tamil, Telugu, Hindi, and more. There will be several dialects and each person may sound different when he/she utters a word. Natural Language processing helps a machine to make sense of these words automatically perform tasks that include translation, spell check, or topic classification.
Speech Recognition- Speech recognition, also known as automatic speech recognition (ASR), is the capability to process human speech into a written format. That is, a machine can create written texts from whatever you speak. This type of AI can be very useful in documenting speeches during campaigns and also for recording conversations to conduct inquiries later. For example, everything spoken between two people in a crime scene can be documented and analyzed for evidence using speech recognition.
Machine Vision- Machine Vision enables systems to identify objects, analyze scenes as well as activities in real-life visual environments. In other words, a system can identify people, places, shapes or anything that is not ordinary. A computer is fed with lots of visuals and images of every recognized person, object and/or shape in a building. For anything the attached camera notices is different from what was recorded, it raises alarms. This concept can be very useful for CCTV cameras and to notify people about unauthorized entry, to analyze medical images, monitor buildings and inspect construction areas.

We have secured conceptual understanding about AI and Automation. However, there has always been confusion between Automation and AI which we intend to clear through highlighting their differences in a tabular form.

AI VS AUTOMATION

Artificial Intelligence	Automation
Automation is the technique and method that uses electronic devices or methods to reduce human intervention in a routine task.	Automation is the technique and method that uses electronic devices or methods to reduce human intervention in a routine task.
Performs beyond the repetitive tasks and is flexible.	Fixed, defined and repetitive applications
It deals with learning from the experience	It does not involve learning
Does not follow rule-based but learning-based system	Follows rule-based system
Learning is the primary part of the AI process	Learning is not part of the process.
Imitates human behaviours or brain	Does not imitate human behaviours or brain
Training is an integral part of the process	No training involved
Accuracy and efficiency may increase with the exposure to quality and versatile data	Fixed accuracy or efficiency
Uses an algorithm that is flexible	Uses a fixed logic
Output is all about prediction and probability.	Prediction or probability is not involved

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