How ancient rules of logic could make artificial intelligence more human

Artificial intelligence is a term that comes from the ability of computer systems to be able to process things and arrive at decisions without human intervention. Scientists and Engineers have been working on Artificial intelligence for a better part of the last decade trying to build algorithms and logic that would allow artificial intelligence to grow and make decisions. The studies by ancient philosophers such as Aristotle have provided logics that have been great at producing human-like results. 

What is Logic?

The discovery of logic is attributed to Aristotle in his work, the Oreganon. He explained a set of premises that can be used to arrive at conclusions. Lately, the study of logic has moved to a more mathematical approach, which is expected to be infallible unlike the human logic. A human being learns by comparing events and figuring out reasons behind the events to form premises. These premises are later applied to other situation to perform deductions. 

Chatbots

Chatbots are simple AI systems that are capable of conversing with users and answer them in a human-like fashion through the use of machine learning. When mathematical logic is applied to chatbots, the outputs are extremely mechanical and do not yield to proper conversations. But human logic on the other hand is very effective and yields more meaningful conversations due to the presence of fallibility that allows human being to connect better with the chatbot. 

Term-Logic

Term logic is the concept of associating an object with its attributes using copula. For example, “a lion is a cat” can be denoted using the copula “->” and the logic can be denoted as: Lion->Cat. Applying this at a larger scale can lead to the formation of a complex system of logic. This system has the capability of comparing situations and arriving at conclusions using the premises that have been formed through term logic and syllogism. Such logics are used in simple systems like chatbots and more complex systems such as bio-robots as well.

Fallibility

The process of applying ancient logic to AI requires the use of Term Logic. But Term logic employs the use of syllogisms between various copula. This can lead to uncertain conclusions or conclusions that are not entirely correct. For example, is Harold has grey hair and Harold has a grandfather, then the induction rule dictates a relationship between Grandfather and grey hair. Now, this may or may not be true but drawing this conclusion based on the given information might not be correct. Similarly, if there are No trains during rain and Flooding during rain, then abduction rule dictates that there are No trains during flooding. While this may be correct, but it is fallible and creates and issue with using term logic.

Beliefs and Truths

We can use the term logic to define beliefs which will have a degree of truth to them. These may be fallible and the fallibility will be dependant on the degree of truth that can be associated with the beliefs. Using the Ancient logic for Artificial intelligence uses a system similar to human belief system. Here the AI considers the factors that support and oppose a belief and then use these factors to define the confidence in these beliefs, much like the humans do.