Learning as imitation or mimesis: how ‘smart’ is machine learning for its planning controllers?

ABSTRACT

The idea to be explored in this contribution is that to understand change as society evolves is useless without Learning that a little knowledge can be a dangerous thing and may look ‘smart’ but is likely to be unwise. This in turn requires an understanding of why the label ‘knowledge economy’ came into substantial usage by opinion-formers at about the same time. Thus a first wave of injunctions in favour of ‘Learning’ by governments and corporate leaders occurred about 30 years ago. The change in question was led by information technology and the production and consumption practices it entailed. In a second wave of ‘Learning from Leaders’, especially how to be ‘Smart’, the lesson quickly became ‘Learning from Losers’. Here some of the most-vaunted - for example – ‘smart’ visions for various functions nevertheless failed to deliver. Perhaps the greatest failure to learn has been the sight and sound of ‘Flailing by Failing’ from Science Policy ‘led’ governments in response to the SARS2-Covid-19 pandemic when the lessons of at least moderate success involved ‘Learning from Life’ after being prepared by previous experience.

KEYWORDS:

• Social learning
• knowledge economy
• machine learning
• learning regions
• planning

Disclosure statement

No potential conflict of interest was reported by the author(s).