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”→
I’ve barely touched Twitter in the last 3 months — it isn’t that I’m not tweeting, I’m not even checking it. This seemed to happen shortly after I read The Shallows by Nicholas Carr, another great book talking about humanity’s adolescent approach to the Internet at the moment. While the overall tone of the book was a little too “doomsday” for me, he had some fantastic ideas on the importance that immediacy has gained in the last few years.
24 hour news, Twitter feeds, Facebook statuses, news aggregators and near real-time search engines are pumping information at us at a pace we’ve never experienced before. As consumers, we’re all expecting and demanding this sort of information, as we’d check Facebook and expect the latest news from our friends, check the BBC News website for minute-by-minute updates etc. However, over time this has had the undesired fact that this immediacy (or at least desire for) is now pervasive.
How many people have noticed their attention span has significantly decreased over the last few years? How many people feel like they’re undergoing withdrawal symptoms when they leave their phone at home? How many of you actively crave your information fix?
After reading Richard Dawkins’ The Selfish Gene, John Cribben’s In Search of the Multiverse and Philip Balls’ Critical Mass, my interest in evolution as a generic or more universal concept has been revived. Is evolution a concept much broader than Darwin ever envisaged? Can it apply to human behaviours? Natural structures? How about our entire universe?
With the current socio-political climate in the US being driven more and more toward the extreme right, where so-called “respected” politicians harp on about intelligent design and other such bullshit, I found it interesting to see that evolution may extend from explaining how our genes have changed over the millena, to actually understanding everything from our place in the universe to the inherent behaviours that we exhibit. Darwin’s work may have uncovered a greater universal truth. As Daniel Dennett once said:
“If I were to give an award for the single best idea anyone has ever had, I’d give it to Darwin, ahead of Newton and Einstein and everyone else. In a single stroke, the idea of evolution by natural selection unifies the realm of life, meaning, and purpose with the realm of space and time, cause and effect, mechanism and physical law.”
My first proper exposure to the theory of evolution beyond basic biology class was when I was about 17 and learnt about genetic algorithms (GA) when writing the Generation5 website I put together for the ThinkQuest competition along with Samuel Hsuing and Edward Kao.
Sam had written an article (which I later expanded upon) about using a GA to solve a diophantine equation. I found it amazing that computer scientists had taken Darwin’s idea of “survival of the fittest” and applied it to something as abstract as solving mathematically equations. Not only that, it was bloody efficient at doing it!
Two years later, I interviewed Steve Smith, one of the engineers behind that massive radar that sits atop the AH-64D Apache Longbow (right). The Apache’s radar can automatically detect the target from the radar signature, and the software that powers this intelligence was evolved via genetic programming.
At the time though, the deeper meaning behind all this “cool technology” never really dawned on me. Fast forward many years and my fascination with genetic algorithms remained. I was stunned by the ability of evolution to seemingly solve huge problems if you could simply assign a fitness to any given solution. Now with that said, this post isn’t meant as a lesson on genetic algorithms as I’ve written plenty in the past (including this bad boy if you’re feeling adventurous). Continue reading “Universal Darwinism: The Evolution of Everything?”→