Looking Back, Looking Ahead: Symbolic versus Connectionist AI

The words sign and symbol derive from Latin and Greek words, respectively, that mean mark or token, as in “take this rose as a token of my esteem.” Both words mean “to stand for something else” or “to represent something else”. The botmaster then needs to review those responses and has to manually tell the engine which answers were correct and which ones were not. Machine learning can be applied to lots of disciplines, and one of those is NLP, which is used in AI-powered conversational chatbots.

Without some innately given learning device, there could be no learning at all. This involves showing it data so it can understand and form a relationship between the data and the expected result. This relationship takes shape in the form of coefficients or parameters, much like how we tweak a musical equalizer to achieve optimal sound. Legacy systems, especially in sectors like finance and healthcare, have been developed over the decades. Symbols play a vital role in the human thought and reasoning process. If I tell you that I saw a cat up in a tree, your mind will quickly conjure an image.

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Rule-based systems, machine learning, whether supervised, unsupervised, or reinforced are all simply tools. In the end, RL is an amazing, but extremely costly way of doing machine learning. While the feats are truly a testament to the capabilities of AI, it still isn’t perfect.

The Disease Ontology is an example of a medical ontology currently being used. Symbols also serve to transfer learning in another sense, not from one human to another, but from one situation to another, over the course of a single individual’s life. That is, a symbol offers a level of abstraction above the concrete and granular details of our sensory experience, an abstraction that allows us to transfer what we’ve learned in one place to a problem we may encounter somewhere else.

Agents and multi-agent systems

If machine learning can appear as a revolutionary approach at first, its lack of transparency and a large amount of data that is required in order for the system to learn are its two main flaws. Companies now realize how important it is to have a transparent AI, not only for ethical reasons but also for operational ones, and the deterministic (or symbolic) approach is now becoming popular again. Using symbolic AI, everything is visible, understandable and explainable, leading to what is called a ‘transparent box’ as opposed to the ‘black box’ created by machine learning. In a nutshell, symbolic AI involves the explicit embedding of human knowledge and behavior rules into computer programs. As you can easily imagine, this is a very heavy and time-consuming job as there are many many ways of asking or formulating the same question.

An orange resembles a round object with a stem emerging from its top. We learn these rules and symbolic representations through our sensory capabilities and use them to understand and formalize the world around us. Symbolic AI is more concerned with representing the problem in symbols and logical rules (our knowledge base) and then searching for potential solutions using logic. In Symbolic AI, we can think of logic as our problem-solving technique and symbols and rules as the means to represent our problem, the input to our problem-solving method.

Symbolic Reasoning (Symbolic AI) and Machine Learning

To properly understand this concept, we must first define what we mean by a symbol. The Oxford Dictionary defines a symbol as a “Letter or sign which is used to represent something else, which could be an operation or relation, a function, a number or a quantity.” The keywords here represent something else. We use symbols to standardize or, better yet, formalize an abstract form. At face value, symbolic representations provide no value, especially to a computer system.

A slightly different picture of your cat will yield a negative answer. For instance, if you take a picture of your cat from a somewhat different angle, the program will fail. It may seem like Non-Symbolic AI is this amazing, all-encompassing, magical solution which all of humanity has been waiting for. You’ve likely heard of the amazing accomplishments of reinforcement learning.

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