Why Robot Cars Should Kill our Children

It is estimated that over 90% of vehicular accidents are caused by human error and inattention (Eugensson, Brännström, Frasher, Rothoff, Solyom & Robertsson, 2013 and Goodall, 2014b) and with the gathering momentum of autonomous vehicle (AV) technology, we are close to the cusp of eliminating a large number of fatalities associated with personal transport. While advances in machine vision and learning are propelling the industry forward, the field of machine ethics still lags (Powers, 2011) but with each technological advance, we are getting closer to an inevitability: our vehicles will soon be making ethical decisions on our behalf.

This paper will discuss whether autonomous vehicles should always swerve around children, even if that means hitting other people. To understand the complexities behind a seemingly simple question, we must look more holistically at the state of decision-making technologies and borrow ‘value of life’ quantisation metrics from the healthcare and insurance fields but first it is important to look more generally at the wider questions of how humans make ethical and moral decisions using abstract thought experiments and modelling. Continue reading “Why Robot Cars Should Kill our Children”

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Kohonen Neural Network Experimentations

A few weeks ago I updated my Kohonen neural network code to support circular rows and columns as well as some simple additional visualizations which allowed for some interesting experimentation.

Circular rows and columns follow a simple premise — the neighbourhood influence effect of training can now wrap around both row and column, allowing for circular, cylindrical and torodial geometries.

Think of it like this, a network with a single row wrapped around allows for a network to learn a circular topology. A nice, simple example of this is the Travelling Salesman Problem as you need one continuous, circular route to be determined. Below there is an example of a Kohonen network run over 350 iterations. The initial phase starts to spread the nodes out over the map, with the second phase making more localized adjustments:

Kohonen-based TSP Solver

It is worth noting that the Kohonen-based solver isn’t perfect, sometimes choosing interim junctions where there is no city, but it is an interesting, reasonably practical use of a different kind of Kohonen topology. Continue reading “Kohonen Neural Network Experimentations”

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