Why do we have to name everything?

Ahhhh humans. Always so quick to label things. Once we noticed a change in internet habits and the phrase Web 2.0 began to be muttered in motivational seminars across the world, we couldn’t help but stretch the metaphor. Now we’re looking for Web 3.0, 4.0 and even 5.0.

Web 1.0 and web 2.0 are fairly easy to understand as they’ve been discussed ad infinitum online. It’s mostly described as the difference between the early days of the internet, where content was pushed at you to consume, and how it developed into a two-way communication tool, where everyday people began to create and share content of their own in personal weblogs etc. Now we could get bogged down in semantics here but I write too much anyway so lets keep it that brief. Speaking of semantics…

The ‘Semantic Web’ is the term that comes up a lot when discussing what ‘Web 3.0’ might be. It gets bogged down in debate about specific coding languages pretty damn fast. XML. URI. RDF. Unicode. Oh god. It gets worse – there’s a diagram…

W3C - The Semantic Web stack
W3C – The Semantic Web stack

WAHH! What does all this mean?! The best description I’ve seen so far is this:

The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation.Berners-Lee et. al.

‘Computers AND people. That’s what’s missing from the stack. Yes – I’m back on the socio-technical bandwagon again. But this time, the ‘elders of the internet‘ W3C are on my side. (Check out their article “The Semantic Web Made Easy” ). W3C adds a ‘P’ axis to this stack, turning it into a 3D concept – the P stands for people and perception. What sway do people and their very humanness have over the technology? What do they want to use it for beyond the three c’s? Let’s break down this statement a little further.

“… enabling computers and people to work in cooperation.”

Imagine fridges that always have ice on hand for an after work drink if a fitbit reported larger than average stress in the day, or a persons better-than-average resting heart rate was reported to an insurer so premiums were kept low? The promise of the Internet of Things and Wearables – the vanguard of tools making use of Web 3.0 tech – is compelling. But few people care what makes it work – just that it does. We want our tech to work with each other to deliver services and tools to assist us in our daily lives and we don’t want to think about the messy tech that drives it. Life is hard enough!

Alas. Sigh. Woe is me and all manner of other disappointments. Why are we always looking for the new toy to play with rather than tidying away the mess we’ve only just made. On the grand evolutionary scale, humans are the equivalent of three year olds. We make something, get bored with it and want that new toy over there whilst simultaneously blocking our eyes and ears and singing ‘la-la-la-la’ in the hopes that some adult will come and fix the looming mess behind us. We don’t want to tidy our room!

Tidy your room meme
Tidy your room meme – Source: ‘The Internet’ (imgflip.com)

So what is this mess I speak of? It’s everything I have written about in my recent previous posts (see here, here, and here). Web 2.0 opened up massive opportunities for people to find their place in the world but the truly hideous aspects of our nature came as part of the package. Very few people designed their wonderful new web 2.0 tools with regulatory issues in mind. And now, we are struggling to cope. Twitter recently initiated new algorithms to deal with hate speech, abuse and doxing online. This is taking out anonymous egg accounts used by abusers and is (arguably) helping to corral the most virulent of abuser’s tactics. But it’s also taking out harmless twitter bots created to amuse or assist (e.g. – feel train) and may lead to the restriction of the development of the technology and the creative output of the medium.

But, toddlers need rules, and humans need regulations. We are struggling to catch-up and invent methods of self-regulation beyond the rallying cry of the unimaginative ‘we need to create a law for that’ (as if there is a secret cabal of adults ‘adulting’ all over the place to make us always safe and never uncomfortable.)

If we can’t solve these sorts of issues for how we behave on Twitter or in chat rooms – what in the hell are we going to do when businesses cannot avoid being in the business of collecting information about you in order to make their products work? What are the rules about what they can and cannot do with that information? How can we set those rules in such a way that allows for the maximum benefit of Web 3.0 technologies? How long will it be before your grocery rewards card is hacked and purchasing habits are published online for ‘the public’ to decide if you deserve your benefit this week?

Can you see why not treating behaviour online as seriously as what goes on offline might be a problem in a world when anything and everything can be known. But not only that it can be known, but that what that information actually means can be decided arbitrarily?

“…information is given well-defined meaning…”

Let’s go back to the Semantic web for a minute – computers working collaboratively with less and less human interaction, using algorithms to decide on the worth of information and making decisions for us to make our lives easier. So appealing to take human nature out of difficult things, (like deciding who is and who is not eligible for benefits) isn’t it? What’s the problem here?

Here are some examples, the first two of which are from Sacha Judd’s amazing Webstock talk (also presented here at the Beyond Tellerand conference in 2016)

  1. Algorithms designed to automatically analyse the suitableness of passport photos – ostensibly to standardise the process – were not programmed to recognised Asian faces. (Read more here)

    Passport algorithm example
    Passport algorithm – Source: Reuters
  2. Pokemon Go launched to great fanfare, but a hidden aspect of the story was that, in the US, the game was more easily played in affluent white neighbourhoods than in ones identified as predominantly black and impoverished. “Why? Because Pokemon Go’s dataset came from the earlier game Ingress. Ingress players tended to be younger, white, English-speaking men – tech early-adopters, and because Ingress’s portal criteria biased business districts and tourist areas, portals ended up in white-majority neighbourhoods. But in launching Pokemon Go off this dataset, no one noticed, or cared enough to address the bias” – (Judd, 2016)(Read more here)
  3. Even the mighty Google has algorithms that can be gamed:

(Read more here, and here)

The computer can only present data as it is programmed by the algorithm. ALL ALGORITHMS ARE PROGRAMMED BY PEOPLE. No matter how fancy your algorithm, ultimately, data are interpreted by people. And people are not free of their inherent and unconscious bias’.

Considering the prevalence of fake news and the unprecedented success of political campaigns built on fake facts, calling out and fixing mistakes like these becomes a political football. It’s utterly reliant on everyday people noticing when the algorithm is wrong and asking the progenitors of the algorithm to manually intervene to fix it, i.e. –  humans and computers working together. But it’s hardly AI. (Speaking of AI – why would we want to program computers to think like us? What a disaster!)

So, although Web 3.0, the Semantic web, or whatever the hell label you want to attach to it is driving the next evolution of social media and internet usage, we are still not dealing with the sorts of regulatory issues and mess created by the emergence of Web 2.0. This is going to create difficult compounding problems for us as we strive to identify the ‘next-big-thing’ to improve our lives. We need to address the top level of the socio-technical stack before it implodes and crushes all our lovely wearables with its sheer mass. As Marvin the paranoid android once said, “I have a million ideas. They all point to certain death.” – (The Hitchhiker’s Guide to the Galaxy – 2005)

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