Posts
While computers have been used to assist with creative processes for some time, the creative input has largely been human. However, recent advances in machine learning software have changed all this.
Using machine learning, computers now have the ability to 'learn' without being explicitly programmed with any task-specific rules. As a result, AI is already writing new articles, poems and books, creating paintings and artistic works, producing video games, and composing music. The Associated Press uses machine learning (so-called 'robojournalism') to report on 10,000 minor baseball league games and on a wider range of public companies than had previously been possible. Google announced last year that it was providing funding to the Press Association for an AI project aimed at producing 30,000 local news stories per month (see our article on Robojournalism - AI and the Media). Similarly, Google has taught its AI to write poetry, predict the next sentence in a book and the art of conversation. Back in 2012, a team at the University of Malaga taught its software, Iamus, to compose an orchestral piece, which was performed by the London Symphony Orchestra at an event to mark the 100th anniversary of Alan Turing's birth. And in 2016, J Walter Thompson Amsterdam taught a computer to paint like Rembrandt by having it study his works. The resulting artwork was, according to experts, completely original and indistinguishable from a genuine Rembrandt. But it has not all been plain-sailing. Only last year, Facebook took the decision to shut down its AI chatbots after they appeared to start communicating with one another in their own language.
The interest in using machine learning is only likely to increase in the creative industries with the demand for fast, smart and original works without the need for human endeavour and expense. However, the use of machine learning gives rise to a number of legal issues relating to copyright, defamation, privacy and data protection. Particular issues surrounding copyright where machine learning is used for creative tasks, include the risk of infringing copyright by the use of machine learning and the subsistence and ownership of copyright in works produced by machine learning.
How does machine learning work?
Machine learning can work on the basis that the software 'learns' how to undertake a particular task by considering examples. For example, it might learn how to recognise pictures of cars by being exposed to examples of pictures that have been labelled as containing a car or not containing a car. Crucially, it would not have been programmed with any prior knowledge of cars such as the presence of four wheels, a bonnet, doors, a boot and the like. In a more complex scenario, the examples might be creative works such as books, poetry, pieces of music or paintings.
Read more...
Source: Lexology
