Page 57 - Monocle Quarterly Journal Vol 3 Issue 2 Spring

ethical codes that govern human behaviour? Can we trust it?
In a 2017 MIT Technology Review article, Will Knight highlights that the neural networks that make up AI have become so complex that often the very engineers who design them may not be able to isolate the reason for any one particular action that their creation takes. In a bid to better understand how AI “thinks”, Google researchers experimented with a deep learning image recognition algorithm in 2015, altering it to generate images rather than identifying features in them. Essentially, the image recognition algorithm was run in reverse, using
THE BLACK BOX PROBLEM
great journey undertaken without consulting the Oracle first.
Modern historians have since found
evidence to suggest that the pneuma
that emerged from the fissure in the
temple was actually a combination of
gases, produced naturally owing to
the geology of the region and capable
of producing a high in the individual
who breathed them in. Although the
ancient Greeks believed deeply in
the advice the Oracle provided, the
reality is that it was likely they were
basing their most important decisions
on the words of a woman who was
intoxicated by something much more
banal than the spirit of a god. In her
drugged state, we can only wonder whether she had any clear understanding of the problems that were posed to her, or of the consequences of the advice she provided her anxious audiences. But people simply trusted that what she advised would help them.
Today, the oracle we consult requires far less ceremony than those of Ancient Greece. No goats need to be slaughtered or mysterious fumes inhaled. We do not need to journey up mountains or wait for the right time of the year to ask our questions. We only need to input large datasets, coded in a way that makes sense to our diviner, and await its response to the queries we have posed. But like the Oracle of Delphi, the layman has no idea how our deep learning AI is reaching its conclusions. And it has no way to tell us.
Developments in big data and machine learning have rapidly advanced the capabilities of AI in recent years. Machines are learning to do ever-more difficult and impressive tasks daily – often faster and more accurately than humans possibly can. AI has also reached the point of being able to teach itself how to do things, no longer relying on the rules and commands of programmers. Last year, for example, technology company Nvidia’s self-driving car taught itself how to drive by using an algorithm that it had developed on its own, simply by watching a human drive. This kind of technology does not rely on a human to give it rules for its decision- making, and so the question arises, how does it make its decisions? And can we assume that it will always make choices that are in line with the formal and informal
THE ORACLE OF DELPHI
AI has also reached the point of being able to teach itself how
to do things, no longer relying on the rules and commands of
programmers.
the various elements it had previously identified in an image to re-create that image. The experiment revealed the features that the algorithm concentrates on during image recognition – such as a bird’s beak or the scales of an amphibian in an animal scene. But the modified algorithm – known as Deep Dream – instead accentuated these features in often grotesque ways, producing a series of artworks that looked like something from a psychedelic-fuelled nightmare. It inadvertently over- emphasised certain features, whilst under-representing
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