declining big data, colour me rimbaud

first you beg for data
then you bag the data
then you de-bug the data
then you get bog-ged down in the data
finally, you big up the data

so what's new in this , i beseech you from the depth of my vowels?

appear to peer - ideas for glastonbury from 2017

so standing in the middle of a very large field surreounded by 200,000 people, but within about 100 peoples' handshakes of a bar, why not build a massive p2p version of uber for beer? you register and then people literally pass beer across to you and you pass money back.....you'd need a trust/reputation system - there'd be some spillage....but that's true anyway (I got wrong change at least 3 times at the bar the traditional way)

the world's first firechat-style beer-to-beer network.....


could also work for snack deliveries...and recycling

meanwhile, in the traditional Real Life, observing someone walk from the Village Pub to the center of the crowd in front of the Pyramid (watching The National, if you want to know) carrying 2 pints + 2 plates of fine ethnic stacked high food, narrowly avoiding many scurrying people, we are a Very Long Way Away Indeed from self driving AI robots navigating a space this complex & dynamic.

if you care  about music, what was good? most stuff, like Thundercat, Joseph, the Lemon Twigs, and some oldies like Barry Gibb and Chic, and a blistering opening set from the Pretenders, with la Hynde in excellent voice. Radiohead? Nah, a bit meh, really. Kris Kristofferson (81) charming, but frail. The aforesaid National? Very Good Indeed. Beyond all possible descriptions? Father John Misty and London Grammar - both of them made time. stand. still.  loads of good comedy, politics, amusing high wire acts & lessons. and a very very chill mood (helped by fairly fine weather almost the entire time!)

unfairness in automated decision making in society.

reading this book about mis-use of maths/stats recently, i think we can go further in condemning the inappropriate approach taken in some justice systems to decide whether a guilty person receives a custodial sentence or not.

The purpose of locking someone up (and other stronger sentences) is complex - it can be to act as a disincentive to others; it can be to protect the public from that person re-offending; it could be a form of societal revenge; and it might (rarely) be an opportunity to re-habilitate the offender.

So we have a Bayesian belief system in action, and we have a feedback loop.  But we better be really careful about i) the sample of inputs to the system and ii) the sample of outputs....and not forget these are humans, and capable of relatively complex and highly adaptive behaviours.

So what could be wrong with the input? (sigh, where to start) -
people who commit crimes are drawn from a subset of society, but people who are caught are drawn from a biased subset - firstly, they're probably less well educated, or dumber, or both, because they get caught. secondly, they're probably from a socially disadvantaged group (racial minority).
people who are found guilty are also the subject of selection bias (and people who get away with it, are party to survivor bias too) - juries have re-enforced the bias in the chance they are caught.

people who are sentenced acquire new criminal skills - this may make them less likely to get caught if they are just poor, but more likely if they are dumb.

So in there' I count at least 4 ways that a decision system that looked at re-offending rates, and properties of the person found guilty, would be building in positive feedback that will lead to more and more people being incarcerated, with less and less justification.

occasionally, external changes (accidental natural experiments) perturb the system and make this more obvious - in the film documentary, the House I live in , the absurd war on drugs is shown to be massively counter-effective - near the end, the huge bias that this has set against african americans starts to wane, simply because of the move in the poor white working class of america into making and consumption of crystal meth (so brilliantly portrayed in Breaking Bad - suddenly, the odds stacked against on group, multiplied by re-enforced prejudice 3 or 4 times over (indeed, one more time for the 3 strikes rule), hit lots of "trailer trash"....

An interesting research task would be to run a model inference tool on the data and see how many latent causes of bias we can find - maybe my 3,4 or 5 is not enough.

truly the world is broken, when it comes to evidence based decision making!

of the internet, for the internet, by the internet

what have we wrought?

i don't think it is about the echo chamber, bubble, or
faddish claims about fake news and alternative facts.

nor do i accept that  the internet offers a zero-cost channel - the internet switched the value-propositions around by reducing cost for sender, but for some kind of content, it simply moves the cost somewhere else

1/  to the receiver (spam/advert/recommend, whatever you call them) -
2/ to the content creator (for music, film.games etc)
3/ to regulator (to ensure neutrality, control monopolistic tendencies etc)
4/ to the service provider as real competition drives profits to truly marginal
5/ somewhere we havn't thought of yet

so what we didn't think about was how to design robust games to allow people to design and choose appropriate system architectures for sustainable worlds, whether journalism (that doesn't let the vocal extreme minority control the agenda) or creative industries (so original work is rewarded), or peer-economic structures like uber, airbnb, etc that treat the means of production/labour force fairly...

hard times

[yes, i know this is sort of a version of jaron lanier's stuff, but it is becoming more and more evident that the complaint is right, but we need an actual fix, and that that is the hard problem, not identifying the cause, but designing the solution]