Multidisciplinary approach

Automation can be defined as replacing people with machines, computers, and robots in certain tasks. In recent decades, machines and computers have dealt mainly with this automation. In subsequent years, with the improvement of the capabilities of robots, robotization will also occur. On the other hand, the intensification of digitization, that is, the conversion of paper information flows into digital format, will lead to a huge amount of invaluable data.

Authorities digitize their administration and services. Citizens and organizations exchange information with each other on social networks and semi-intelligent systems such as smartphones. Finally, robots exchange data without the need for human intervention. Every minute, 1.7 million billion bytes of data are produced in the world. Finding recursive patterns in this data is a process called big data. In the 21st century, automation mainly affected routine tasks. However, technological advances are driven by the recent release of larger and more complex big data.

Digital tools. Computerization is no longer limited to routine tasks that can be decrypted in the form of software requests. This also applies to non-standard tasks where big data is available. Sensor data is one of the main sources of big data. The ever-increasing accuracy of sensors and the advent of the Internet of Things (IoT), the connection of computers and technologies to the Internet, are the source of this phenomenon. A sensor is a device that detects events or changes in quantity and provides an output for measuring them, usually in the form of an electrical or optical signal. Computers are able to better interpret this big data. This is called artificial intelligence (AI).

The advantage of AI is that computer systems can now autonomously establish communications that were previously impossible. And computers are always faster, AI continues to evolve. For example, it may happen that in the future, intelligent systems can predict how Ebola will spread, or that accurate weather forecasts can avoid long-term crop losses. Therefore, technology can perform an increasing number of tasks that were previously considered possible only for men. In addition to distinguishing between routine and non-standard tasks, we can also distinguish between the cognitive or manual nature of the task.

The next section briefly discusses the latest developments in the field of automation of non-standard cognitive and manual tasks. Non-standard cognitive tasks The presence of big data automates a wide range of non-standard cognitive tasks. The computerization of cognitive tasks is also supported by a great advantage at the level of algorithms, namely the absence of certain human errors in judgments. Changes in the user interface also allow computers to respond more directly to people’s needs. These achievements create work for highly qualified people, while at the same time making some types of functions fully automatic. For example: an application that recognizes voice clips, gives them meaning and reacts accordingly.

Classes based on judgment and the ability to evaluate people are also increasingly becoming automated. For many of these tasks, the impartial decision-making process of algorithms is an advantage over human operators. Technological advances in the 21st century will contribute to solving a variety of cognitive tasks that have long remained with man. 

Many professions that will be affected by these developments are not yet fully automated. Therefore, automation of some tasks will give 6 employees more time to complete other tasks. The trend is clear: computers are a problem for a person to work in a wide range of cognitive tasks. Non-standard manual tasks Robots are equipped with increasingly sophisticated sensors and manipulators that allow them to perform non-standard manual tasks.

For heavy client interfaces (desktops) used in a two-level client-server architecture, it uses one or more object-oriented programming languages that can vary in different projects, as well as libraries of graphic components and objects. existing. Web interfaces use tag and style sheet languages, as well as client and server scripting languages and, possibly, related infrastructures. To manipulate data, it uses a query language, which may be specific to the type of data that is being accessed. To perform unit tests, he can use testing tools. As part of a project for several developers, he uses code sharing tools.