There is a risk of that happening with Artificial Intelligence (AI). Many talk about it, but with the exception of specialists, there is still lack of knowledge on the subject.
But then, what is AI in reality, what is it made of and what is it good for?
Artificial Intelligence is “the simulation of processes of human intelligence carried out by machines, especially informatics systems. In general, AI systems function by taking in great quantities of labelled training data, analyzing such data in the search for correlations and patterns, and using those patterns to make predictions about future states”.
In other words, AI implies the use of computers to do things that traditionally require human intelligence. This implies the creation of algorhythms to classify, analyze and extract predictions from data. It also implies acting on the data, learning from new data and improving with time.
AI programming is centred in three cognitive abilities: learning – acquisition of data and creation of rules (or algorhythms) for turning them into information that can be processed – reasoning – choosing the adequate algorhythm to reach the desired result – and self correction – the continuous adjustment of the algorhythms to guarantee they offer the most precise results possible.
Artificial Intelligence is used for the solution of problems. Even sharing some elements with automation, as data dependency, they are not synonyms. AI benefits from aspects of automation, but goes beyond the simple execution of tasks as it learns to make decisions by itself, imitating human behaviour.
Roughly, it can be said that one trains an application for a specific task, in such a way that it allows it to explore and improve by itself. And also, good AI “sorts out” what to do when faced with unknown situations.
Anyway, it should also be noted that AI is as powerful as the data fed to it. It is like an engine that runs on data: “It consumes data, recognizes patterns in them, learns from those patterns and can make decisions based on those patterns”. In fact, AI algorhythms are trained using large sets of data so they can identify patterns, make predictions and recommend actions.
Artificial Intelligence can offer companies information about their operations they may have not known previously. And, in some cases – particularly when dealing with repetitive and detail oriented activity – it can carry out tasks with great efficiency. Besides, AI reduces times for tasks that involve a large amount of data.
This discipline is very present in different daily activities nowadays. For example, it is used to make recommendations about what can be purchased online, to understand what is said to virtual assistants, to detect spam, to recognize who and what there is in a picture or detect credit card fraud.
In order to make viable this and other concrete developments, AI is incorporated to different techniques and technologies, such as robotic process automation (RPA), machine learning, deep learning, data science, neuronal net, machine vision, natural language processing (NLP), data mining, data analytics, robotics itself, etc.