How machine learning is transforming the innovation game Machine learning has its roots back in experiments with ‘artificial intelligence’ in the 1970s but has come to represent a powerful technological trajectory as the idea of mimicking human neural networks and their learning capabilities has been explored. And now we have generative AI, which does what it says on the tin — generates something new. And this brings the uncomfortable challenge to our perception of ourselves as the only ones capable of creativity — generating novel and useful solutions to challenges.
A quick review of the growing literature on ‘artificial creativity’ shows that there are grounds for worrying. Machine learning models can now ‘create’ music, literature or visual art to a standard which makes it increasingly difficult to detect its non-human origin.
With the advent of models like Chat-GPT has come the recognition that many fields are likely to be impacted by these developments. This blog explores the possible impact on how innovation is undertaken — and by whom.
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