Since the 1950s, computer scientists have been working on programs which resemble human intelligence to such an extent that they can replace it in certain applications. This is known as Artificial Intelligence (AI) as well as cognitive computing. After considerable hype in the 1980s and the subsequent “winter of AI” in which the forecasts failed to come true, recent spectacular successes have convinced the research community that AI will not only lead to smart machines taking over tasks from human beings but will also give rise to brand new technologies.
by Katrin Nikolaus
Siemens researchers were among the first in the 1990s to harness artificial neural networks for innovative solutions, namely for the optimization of energy-intensive steel plants. Today, roughly 200 experts at Siemens are occupied with data analysis and neural networks.
In the computer sciences, Artificial Intelligence is an interdisciplinary field of research dealing with solutions from mathematics, informatics, speech recognition and computer vision and robotics, depending on the objectives. Since efforts began to teach computers feelings like pity, pleasure and willingness to help, work has also entailed models from psychology and philosophy. And because computer programs can also make decisions, for instance in the context of autonomous driving or administrative tasks at insurance companies, many questions have to be answered from the field of law — especially in relation to liability claims.
In the future, robots that learn simple processes with the aid of AI will be used to support people in factories, warehouses, hospitals and care homes. Programs that make autonomous decisions will soon be able to handle simple administrative activities like archiving and correspondence concerning standardized procedures. Connected e-mobility, in which autonomous vehicles coordinate matters among themselves to optimize the flow of traffic, could protect megacities against the collapse of transport and make life more livable in them. Experts see huge benefits in medical diagnostic systems that are trained to detect anomalies and deliver initial interpretations.
Experts think that AI technologies are bringing a paradigm shift to economic affairs. It is neither capital nor labor that will be the key factor in economic growth but how the industrial nations manage to exploit the opportunities that are opened up by technologies based on artificial intelligence. Data is the foundation for this new growth. The value of this data for business and the working environment in the future is comparable to that of mineral oil in the 1970s. Data is the base material for machine learning: the more data a program processes, the more accurately it can, for example, detect faults, make predictions, recognize speech or carry out movements.
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