When IBM’s cognitive system Watson competed and won against Brad Rutter and Ken Jennings on the quiz show Jeopardy! in 2011, it became clear that a new kind of computer was emerging – one that could learn, think, and understand and process natural language.
But what exactly is a cognitive system?
Cognitive computing, a new approach to computer technology, simulates the human thought process in a computer-controlled model or causes computer technology to act like a human brain.
It involves self-learning systems that use data mining, pattern recognition and natural language processing to mimic the way the human brain works. The goal of cognitive computing is to create automated IT systems that are able to solve problems without human assistance.
Although computers have become faster and more powerful in the past, they still have difficulty understanding voice commands, recognizing objects, or translating languages.
Today, the Internet provides enough data to allow machine learning – that is, to allow machines to think independently.
However, a prerequisite for this system is correct programming: Since you want the system to function independently, not all possible problem solutions can be programmed in advance.
What is needed are machine learning algorithms to incorporate more and more data into the system in order to expand it and make it „smarter“. This approach, which is also called deep learning, can be discovered by all of us in everyday life: whether it is the autopilot in an airplane or the self-driving car, whether it is the dictation version on the cell phone or the increasingly personal Google search: cognitive systems have quickly crept into our everyday lives.
The reason why such systems are needed today is quite simple: the ever-increasing growth of data. Data that was previously not only unstructured and unfiltered, but also very complex.
Not only are we now able to collect vast amounts of real-time data about people, places and things, but far greater amounts can be derived from the existing data that such systems create using feature extraction and contextual analysis. They help us bring humans and machines closer together, allowing them to interact naturally to extend and augment human competence and knowledge.
These systems will learn to work alongside experts and assist them to expand their know-how in any field of knowledge. Complex decisions can be made by the system with the help of the ever-expanding big data that has been fed into it.
These systems will assist and assist scientists, engineers, lawyers, doctors and other professionals. Cognitive systems are not intended to replace our human thinking at work, but rather to expand our thoughts and allow us to think more creatively.
An example of this is the cognitive system IBM Watson, which was already mentioned in the last report.
In healthcare, IBM Watson for Oncology helps oncologists treat cancer patients with personalized, evidence-based treatment options. This is possible by analyzing patient data and comparing it with thousands of previous similar cases to narrow down the treatment options for doctors and help them find the best possible solution for their patients. The doctor remains a doctor – he is not replaced by a system. He is just helped to make faster, more careful decisions, since a human is not capable of evaluating so much data in a short period of time.
What does this mean for the future?
According to a predictive study by Forrester, robots, artificial intelligence, machine learning and other cognitive technologies will replace around 16% of all jobs by 2025. In addition, 9% of all jobs are newly developed professions that have adapted to the digital age, such as data scientists, robot surveillance experts and automation specialists.
Jobs will be lost, but new jobs will be created, which will then be needed. According to Wolfgang Wahlster, the director of the German Research Center for Artificial Intelligence (DFKI), all of these new jobs can only be financed by a successful economy – which would only work through digitalization, with artificial intelligence as the spearhead.
