Artifical Intelligence is changing our life

Self-learning systems represent the next step of digitalisation. They independently solve tasks given by humans and react to their environment. The relationship of man and machine is thus changing fundamentally – and has to be designed according to human needs.

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Self-learning systems have become part of everyday life: Robots, assistance and software systems are already tackling complex problems and adapting to a wide variety of situations. Self-learning systems are based on methods in Artificial Intelligence such as machine learning. These methods signal a paradigm shift in that programmers are no longer coding every work step of a system but rather learning methods. They are teaching machines to learn from input information. Self-learning systems use this information to recognize the structure of an environment, to continuously expand their knowledge based on experience, and are able to execute tasks in a complex environment.

Topics

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Technologies and Data Science

Artificial Intelligence and Data Science form the basis for self-learning systems and are essential for their design from the data collection and analysis stage through to the development of key technologies.

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Human-Machine Interaction

Machines and digital devices have become a part of our private and work lives. Their benefit for people must be a paramount consideration in their design.

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Work and Skilling

Self-learning systems bring about fundamental changes to the world of work: Artificial Intelligence will be supporting humans in all spheres of life.

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IT Security

Self-learning systems have the potential to make numerous processes more efficient and more comfortable and secure for humans, for example in road traffic or work life.

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Law and Ethics

As with nearly all technical innovations, self-learning systems raise new issues which must be discussed in public and put into a legal framework.

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Business Models

Artificial Intelligence and self-learning systems process data into knowledge, enabling burgeoning volumes of data to be utilized for the development of goods and services.

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Mobility

Application

Self-learning systems will form part of the mobility of tomorrow. Transport systems on land, water and in the air will become increasingly automated.

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Medicine and Care

Application

Smart data holds the promise of great progress in medical research, diagnostics and preventative medicine. Acceptance and security are essential prerequisites.

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Hostile-to-Life Environments

Application

The deep sea, outer space, crisis zones: Self-learning systems can take on tasks in places that are dangerous, pose unreasonable hardship for humans or are harmful to their health.