What is Artificial Intelligence (AI)?

In the last couple of decades, technological advancement has been relentless. Little by little, increasingly modern resources have been incorporated both into our daily lives and within business, making tasks easier and increasing productivity. Artificial Intelligence is no different.

Although AI might seem like a futuristic and distant reality, appearing in science fiction movies like Blade Runner or series like Black Mirror, this branch of technology has been around since the 50’s. In simple terms, Artificial Intelligence is a branch of computer science that aims to create machines capable of performing tasks that would usually require human intelligence.

Despite being around for decades, according to a study made by Blue Fountain Media (a digital marketing company based in New York), 43% of adults residing in the US are not sure about what is Artificial Intelligence and what are its applications – 7% simply are not interested in the subject. However, 32% fear losing their jobs to AI. 


But Artificial Intelligence is already part of our everyday lives

While science fiction may portray AI as robots that appear human and want to take over the world, the evolution of Artificial Intelligence is not that frightening. This technology already benefits several different sectors of economy, being applied in a variety of ways.

In the health sector, for example, AI can help with diagnosis, analysing tests results. Of course, a doctor will always validate the answers given by the algorithm, but the use of technology can speed up the process.   

Finding patterns in consumer behaviour can help sales and marketing with personalized recommendations of products. You can see these recommendations in action when you shop on Amazon, or are browsing platforms such as Youtube or Netflix.

In financial institutions, AI can be used to identify fraudulent transactions, provide a quick and assertive credit score and optimize data management processes that were previously done manually.

All of these uses are made possible by a series of developments in Artificial Technology, such as Machine Learning, Deep Learning and Neural Networks, which will be explained shortly.

 

Machine Learning: using data to solve problems

Machine Learning is a way to automate analytical model building. Based on calculations of algorithms, computers can then recognize patterns and make decisions.

Basically, computers are given a large amount of data, and through statistical techniques, are able to learn and predict outcomes, becoming increasingly better at the task they were created for, without having been specifically programmed to do these tasks through written code.

Thus, Machine Learning can cut down the time required to design and program applications for problem solving, and can even find patterns that will help with the task at hand that were overlooked by humans. This technology can increase our capacity for problem solving and anticipate risks, all thanks to the data we provide it.

 

Deep Learning and Neural Networks

Deep Learning is a type of machine learning that uses neural networks to process data, allowing the machines to make connections and act in a more “natural” way. Neural networks are models inspired by the human nervous system, in particular the brain, and contain a number of “hidden” layers that help process data in increasingly complex ways.

In sum, they can solve problems through the discovery of new patterns within data sets. These technologies require a large amount of data, but can deliver more complex and refined results than seen previously, and some common uses involve image and speech recognition.


The limits of Artificial Intelligence 

As with any technology, AI has its limitations. The main one being it relies on data sets to be created, learn and improve. Without data, it’s impossible to develop Artificial Intelligence systems. Furthermore, the quality of the results AI delivers will depend on the quality of the data it is given. If a system is created with incomplete or biased data, the algorithm will reflect that.

Another current limitation is that each use is very specific. A machine trained to provide a credit score, for example, will not be able to do other tasks such as identify fraudulent transactions.

Finally, although AI is capable of making predictions based on data analysis, the final decisions and actions are ultimately the responsibility of the people that are using this technology to support their work. In other words Artificial Intelligence is here to help people make better decisions, not to replace them entirely.

Comments are closed.