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Systems thinking

Most of the current AI offerings on the market can identify associations in large quantities of data, but can not work out complex phenomena of cause and effect or identify modifiable factors that can engender desired outcomes. Yet. We don't know what is more dangerous (in terms of super-rational stances resulting from such left-hemisphere dominance), a world run by Black Rock Aladdin-like machines as if they can, or development of machines that can and then making ourselves dependent on these even more.

Systems thinking revolves around understanding correlations, causes and effects and is more than just a handy collection of tools and methods to explore complex systems with – it is also an underlying philosophy, an awareness of the role of structure in creating what we face, of that which gets often overlooked, of powerful patterns operating on us, and of consequences of our actions.

Basic methods

Examples

 
 
en/facilitation/systems/start.txt · Last modified: 2020/07/03 16:58 by Digital Dot