Category Archives: Algorithms

Repeat: Christmas, Until …

Sorry folks, I haven’t had time to write a CS-based Christmas story this year so here’s one from a few years ago!

Merry Christmas!


No More Privacy Any More? (Just putting this out there)

OK, some of this material isn’t new but I’ve been asked to edit a special (Information) journal edition on (something like) ‘Will AI, Big Data and the IoT Mean the End of Privacy?’  The plan is to circulate a ‘discussion paper’ to encourage submissions.  What follows is an early draft of that (extended from The Prof on a Train Game) so it won’t hurt to get it ‘out there’ as soon as possible.  Comments welcome below, by email, message, whatever …

Abstract

The embodiment of the potential loss of privacy through a combination of AI, big data and IoT technology might be something like an integrated app capable of recognising anyone, anytime, anywhere: a sort of ‘Shazam for People‘, but one capable of returning seriously personal material about the individual.  How credible is such a system?  And what might stop it?

Introduction: A Future Scenario?

It’s 2025 or thereabouts.  You meet someone at an international conference.  Even before they’ve started to introduce themselves, your IoT augmented reality glasses have told you everything you needed to know … and a lot more you didn’t.

Jerry Gonzales. Born (02/11/1970): Glasgow, UK, dual (plus USA) citizenship; 49 years old. Married 12/12/1994 (Ellen Gonzales, nee Schwartz), divorced 08/06/2003; two daughters (Kate: 23, Sarah: 17); one son (David: 20). Previous employment: Microsoft, IBM, University of Pwllheli; current: unemployed. Health: smoker, heavy drinker, recurrent lung problems, diabetic, depression. Homeowner (previous); now public housing. Credit rating: poor (bankruptcy 10/10/2007); Insurance risk: high. Politics: Republican. etc., …,  Sport: supports Boston Red Sox and Manchester United FC. …,  Pornography: prefers straight but with mild abuse …,  etc., etc.

Continue reading


And So It Begins?

OK, this blog has made some pretty wild predictions over the years; from loss of privacy & security, through societal decay from social media & 24/7 connectivity, mass unemployment by AI & automation, to industrial environmental catastrophe and a technocapitalist Armageddon.  Now there’s clear evidence of the first of these forecasts coming true, any chance of taking any of the others seriously?  Maybe before it’s too late might be a good idea?

Continue reading


A ‘Reasonable Amount of Time’

The concept of a ‘reasonable amount of time’ figures a fair bit in abstract computational complexity theory; but what is a ‘reasonable amount of time’ in practice?  This post outlines the problem of balancing between the two competing ideals of determinism and adaptability and offers a flexible working definition.  (Not to be taken too seriously: it’s summer vacation time.)

A standard text on combinatorial problems and optimisation algorithms – perhaps discussing the TSP, for example – might read something like:

“… so we tend not to be as interested in particular complexity values for individual problem instances as how these complexities change as the input problem size (n) increases.  Suppose then, that for a given problem, we can solve a problem instance of size n = L in a reasonable amount of time.  What then happens if we increase the size of the problem from n = L to n = L+1?  How much harder does the …?”

or, filling in a few gaps:

“… so we tend not to be as interested in particular complexity values for individual problem instances as how these complexities change as the input problem size (n) increases.  Suppose then that we can solve a TSP of 20 cities on a standard desktop PC in a reasonable amount of time.  What then happens if we increase the number of cities from 20 to 21?  How much longer does …?”

All good stuff, and sensible enough, but what’s this ‘reasonable amount of time’?

Continue reading