What is artificial intelligence?

Language assistants in smartphones, navigation systems in cars or face detection photo and video apps: More and more people are using artificial intelligence. But few really know how and where artificial intelligence already surrounds them in everyday life - and what actually makes it so special.

Coming up with a concrete answer is difficult, because already the term “human intelligence” is not fully defined either. The term "artificial intelligence" was coined in 1956 by computer scientist John McCarthy at a conference at Dartmouth University.

The main difference between conventional computer programs and systems with artificial intelligence is that the programs only do what people have taught them to do through predefined processing rules (algorithms). Artificial intelligence, on the other hand, learns independently and responds to tasks or problems, regardless of what people might do.

This might sound simple, but the difference is huge. Because while simple computer programs only process series of complex if-then tasks, an artificial intelligence may be modeled after the human brain in the form of neural networks. These are similar to the functioning of neurons and can process a lot of information simultaneously. The networks pass on information via artificial synapses and are able to learn – they have been specifically trained through so-called deep learning. Like their natural role models, humans, they learn through experience.

For intelligent systems to enrich our everyday lives, they need huge amounts of data. Big data is an important prerequisite for a well-functioning AI. Because they learn constantly by continually analyzing data, for example, user data. In sports, analysis of biometric data can be used to see how an athlete’s training affects their probability of injury. Farmers can determine the optimal timing for irrigating their fields. Cities use data for energy management. Medicine uses AI to detect diseases and track treatments.

The fact that artificial intelligence can lead to unexpected solutions is exemplified by the message service Twitter chat-bot "Tay". Developers wanted to use it to learn how artificial intelligence might learn in an everyday setting. "Tay" was turned off after less than 24 hours. The experiment to let an artificial intelligence learn through exchange with everyday people went very badly. This is because the chat-bot, who was modeled to be an average teenager, quickly became an internet troll full of hatred and incitement, in a matter of hours. Twitter users had detected a flaw in the bot and taught it negative behaviors.

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