AI without ML

Can Artificial Intelligence Exist Without Machine Learning?

We have already talked about artificial intelligence and machine learning in our previous blog. We have seen how machine learning is just a subset of AI and that it helps AI accomplish its goals. Now let’s discuss if AI can exist without ML.

Surely not, right? If there’s no ML, how can AI work? ML is a tool used by AI, surely. But wait.. Not so fast !!

You see, the term artificial intelligence existed long before Machine Learning was commonly used. We are talking about the 1950’s and 60’s here. There were systems which claimed to use AI to work. They are known as GOFAI systems but they didn’t use ML. So what’s going on here? What’s the catch?

What is GOFAI?

Before machine learning, AI generally used a form of AI called GOFAI. GOFAI stands for Good Old Fashioned AI. It is also referred to as Symbolic AI. 

The core belief of GOFAI is that any complex system can be defined using human readable symbols and rules. The rules would define the processes that take place within the system. Some examples of Symbolic systems are,

  1. Algebra – Here we use x,y,z to represent variables and +,-,x,/ to represent operations between variables. So an equation like x = 3y + z is termed as a rule.
  2. Chess – The pieces like king, queen, bishop are symbols and the moves are the operations between the pieces.
  3. Programming languages – many languages use certain keywords like “for, while, class, object” etc. So they would be symbols. Statements like “for x in list: x = x + 2″ would be called rules.

These are obviously not AI systems. But they serve as examples of Symbolic systems. The idea behind Symbolic AI systems is that we can take any complex real world interaction and encode it in this manner.

GOFAI also deals with a class of AI problems called Strong AI

What is Strong AI?

AI problems which fall under Strong AI usually deal with complex real world scenarios. But the best way to understand Strong AI is to look at what weak AI means.

Weak AI problems are narrow in nature. They deal with a specific scenario and nothing else. Most modern machine learning and deep learning tasks are Weak AI problems. It tries to solve simple problems like image classification, text classification etc.

Consider the case where we have to identify accidents in traffic cam feed. The solution would be to build a system which takes the video stream as an input and look for specific signs of accidents in real time. It needs to be able to identify a car crash and the like. This is considered to be a Weak AI problem as it solves a narrow task. This AI would not be capable of doing other tasks.

A Strong AI system is to model more complex systems such as a general artificial intelligence which can act, feel and do as a human would.

GOFAI was seen to be trying to solve these problems. Although unsuccessfully.

Expert Systems

There are many examples of GOFAI systems out there. They are also called expert systems which solve problems in a specific domain. These systems use Symbolic AI to create symbols and collect data from domain experts to form production rules. Examples being

  1. Phone IVR systems – These systems are created by collecting data about what users generally call about. Using this information, an IVR flow chart is created which guides the user through its various functions. These systems encode production rules as flow charts and use symbols on the phone keypad which it can recognise (e.g. 1, 2, 3)
  2. Automated Medical Diagnosis – Systems are capable of identifying specific conditions using patient data, reports, scans, etc. Some of these systems rely on a vast amount of data from domain experts. The final GOFAI system is used to check this knowledge base to find a match. This type of system uses a knowledge base and an inference system.
  3. Simple chat bots – Chatbots fulfilling a simple flow of customer service, food ordering, and ticketing, etc also use a form of GOFAI. They are quite similar to Phone IVR systems, just with a better interface. They follow a flow chart, guiding you through button clicks to reach a specific goal.

Is GOFAI really AI?

So we have seen how AI can exist without ML. Such systems use the concept of GOFAI and symbols. But GOFAI has its detractors. Many do not consider it to be AI at all. There are many arguments against GOFAI and whether or not Strong AI is achievable.

One of the more interesting arguments against Strong AI is John Searle’s Chinese Room Argument in his paper “Minds, Brains, and Programs”. In it Searle asks us to consider that he is sitting inside a closed room. He accepts small pieces of paper from a slot box in the door. His task is to translate from English sentences to Mandarin sentences. He would then use phrase books within the room to help him finish the translation.

He compares Symbolic AI systems to this chinese room experiment. The person within does not understand Mandarin, but is still capable of completing the task. But this does not mean that he truly understands the language at all.


Although GOFAI and Symbolic AI has its opposers, it is true that these systems are all around us. They do not use machine learning, instead they use symbols and rules but still many claim that they use AI. Detractors of GOFAI, on the other hand, argues that systems which uses symbolic AI are not really intelligent and therefore cannot be treated as AI systems.

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