Machines are slowly taking over. Every day, complicated algorithms serve up targeted advertisements; dictate the search results on Google, and serve to protect our sensitive data from other algorithms trying to steal them.
It would probably surprise most people to learn just how much-advanced computer programs assist and influence our everyday lives. Their increasing efficiency and semi-autonomy make the trillions of daily computations they perform practically invisible around us.
One particularly taken-for-granted form of machine labour is the computational shifts put in to keep our payment details safe and guard against fraud. Artificial intelligence systems are locked in an arms-race with malicious programs. They have to keep adapting (i.e. ‘learning’) to stay ahead of their ‘rivals’. Not only that, but the AI has to know to reconfigure to the tune of the PCI DSS and GDPR requirements — complex security demands from both North America and Europe.
In the global, transnational age, our AI systems are constantly juggling data — and increasingly outpacing and outperforming humans.
But what is artificial intelligence? And how do integrated circuits and electrical currents manage anything at all — never mind learning to manage new tasks?  To understand, we will need to briefly cover a topic that is still unresolved after nearly a century of debate.
Defining intelligence
It is surprisingly hard to define intelligence, and there is no uncontested definition for it. Some AI researchers think intelligence entails a capacity for logic, understanding, planning, self-awareness, creativity, and learning, to name a few. But opponents would argue that these are human-centric viewpoints.
Instead, it might be easier to give intelligence a broad and malleable definition: rather that intelligence is “the ability to accomplish complex goals”. What this means is, there can be broad and narrow forms of intelligence. A calculator, for example, is narrowly intelligent in that it can solve arithmetic much

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