Enthusiasm for is steadily growing. What implications this will have for the future of the human workforce and what and where exactly is the starting point for – these are issues, which have yet to be clarified.
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The C Level Manager Community has conducted a survey on () among their members. 70 percent of those surveyed stated that they were able to define and explain . However, this is a very sporting and self-reliant assessment – the field is wide and complicated. If you restrict to UI (User Interface: the interface, on which the man-machine interaction takes place) and UX (User Experience: how the user deals with and reacts to platforms) respectively to their optimisation, you do not do justice to . And to state that “fuzzy” algorithms, or algorithms with a certain lack of clarity, are somewhat “smarter” than “linear” algorithms, this does not get to the heart of the matter either. Fuzzy logic is much more than having the courage to be inaccurate.
– attempting to narrow it down
It is very difficult to find a generally valid definition of . Therefore we have to understand in its widest possible sense as something, which helps humans to achieve their full potential. This help can present itself in the form of computer systems, algorithms, robots or other technologies. What is common to all of them is that people can be helped to perform certain tasks only while they are able to grasp and solve other problems more quickly and more accurately. There is a range of definitions and distinctions for , which in some cases differ widely from one another. Therefore, for instance, research and industry differentiate between different forms of . The current state of research differentiates between weak and strong .
Weak denotes all computer systems or physical objects (robots), which are programmed to perform a specific action in specifically delimited areas (e.g. facial recognition, Internet searches or playing chess). Strong on the other hand denotes systems, which possess general human cognitive abilities and thus are no longer able to perform unknown tasks. At the present time it is still not totally clear whether it is at all possible to programme strong respectively. In principle it enables constantly to improve its ability to “feel”, “understand”, “learn” and “act on” the systems controlled by it. These refinements and optimisations ultimately open whole new possibilities to the entire economy – and change the entire business environment.
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