AI’s memory is perfect for insight into collective behaviour

AI was never intended to give insights into collective behaviour, yet it’s becoming an increasingly efficient method of doing so. 

In an age of the GDPR fearful, collective behaviour is the way forward to understanding consumer preferences and AI’s memory of data allows this to happen without jeopardising individual behaviour. 

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Early beginnings

Alan Turing was recently named as the most ‘iconic’ figure of the 20th century. Perhaps this is because of the explosive interest and power that artificial intelligence is set to have on our world in the near future. 

He was a mathematician who cracked codes during World War II and praised with shortening the war by several years due to his work at Bletchley Park. Here, he was tasked with cracking the ‘Enigma’ code and, with another code-breaker, invented a machine known as the Bombe which has had a huge influence on the development of computer science and artificial intelligence.

Turing suggested that humans use available information as well as reason in order to solve problems and make decisions, so machines should, in theory, be able to do the same. This was the logical framework of his 1950 paper, Computing Machinery and Intelligence, in which he discusses how to build intelligent machines and how to test their intelligence.

After a conference in 1956 where, what is considered by many, to be the first AI programme was presented, a flurry of interest in AI ensued. Computers could store more information and became faster, cheaper, and more accessible. Machine learning algorithms improved and people got better at knowing which algorithm to apply to their problem. However, a mountain of