In this digital age many feel they are saturated with data; and it’s not always good data. We have ever increasing sources it’s true and 5G will grow that volume even more. We have so-called fake news, real news, fake facts, real facts, my evidence and your evidence. There’s a certain doubt over what is authentic, given a growing politicisation of scientific research: creating a new form of ‘prience’; an unhelpful fusion of politics and science. Where does this leave what we call knowledge in the middle of all that?
Data has become for some a pejorative thing; a burden, where they are overwhelmed. Francis Bacon is often attributed to the quote “Knowledge is power”, from his Meditationes Sacrae (1597) – and we will explore the relationship with power on several levels – but does it mean for now we’ve got too much knowledge and we just can’t cope with it. Have we got too much of a good thing?
There are all sorts of descriptions and labels we give around types of knowledge. Policing tends to talk about information, intelligence and evidence; a kind of filtering hierarchy of trustability and relevance of data. It’s a form of currency identification that seeks to separate the highly significant from the volume bulk. This notion of gradiated usefulness means searching for knowledge is almost like a Klondike pan handler sifting for a golden nugget.
It takes a lot of time and you’ve got to be able to spot the gold when you see it. Before the Old West trend for gold sifting became established, someone was the first to find such gold, in a place they weren’t expecting it, when they might not have even been looking for it. But they found it nevertheless and then set a trend of the thing to look for, and how to look, for quite a while. This process moves from a very inductive position – having an open mind and spotting something – to a very deductive position – I know exactly what I want and how to do it. Morris (2020) defines the search as looking for something specific, and re-search as finding out about about a new concept. Think of it maybe also as either fishing for something very targeted, with a hook, or sifting in a broader more general style with a big net. See our blog here for more about inductive and deductive thinking:- https://www.empac.org.uk/the-deductive-paradox-finding-what-you-look-for/
Searching inductively is a bit of a chicken and egg dilemma. You might not know the next great thing you are going to come across, because you don’t know it’s there. We might resort to desperate measures. The streetlight effect, or drunkard’s search principle, is that you search where the light is for something, whether it’s actually there or not. How do you search to look up a word when you don’t know how to spell it? OK, you probably use a wild card approach and take a stab at it. You might then come across a better word using a thesaurus.
If you set off with the wrong, or limited, search parameters, you end up with a restricted result in your finding. You may come back with fool’s gold: but who is to say just what is real gold in the circumstances? We need to just pause and consider the language and presumptions around ‘knowledge’, otherwise we just end up being on the receiving end of yesterday’s rules and conventions. This takes us a little into the sociology of science, in that we need to unpack some underlying presumptions about who judges what ‘knowledge’ is. Within that sociology of science is really a form of power distribution; a ranking of ‘what counts more’ and you need to be aware of that background if you seek the democratisation of knowledge.
In summary, there has been discourse around ‘modes’ or types of knowledge. What is referred to as Mode 1 knowledge (Gibbons, Nowotny, Schwartzman, Scott, & Trow, 1994) describes ‘official’ or pure knowledge, maybe scientific, and maybe anchored within particular academic disciplines. Mode 2 knowledge is more ‘real world’ and applied, often which has been pulled together in a transdisciplinary way. Mode 3 (Caravannis and Campbell, 2012) opens up more meso (‘middle’) forms to include active knowledge creators in action, and the interfacers between industry, academia and state in approaches such as the Quintuple Helix Innovation Model. It’s very much a space of knowledge agile development in action; a creative milieu.
The point here is not to be unwittingly restricted to Mode 1 ‘official’ knowledge, as it’s not the only form out there. Whilst you need to be a discerning explorer, you wouldn’t want to restrict what you might find by only searching one form of what’s possible.
Having a more intelligent radar out there to proactively find all concepts from wherever and whoever that may be of use to your purpose is something of a dream; but it’s not impossible and maybe it’s nearer than you think.
All of this would be quite revolutionary because it would help democratise knowledge. There have been waves of change before. In the UK, like many places, history shows us once a domination of the Church; of authorised versions of the bible; of monks hand writing books (initially in Latin) and a general (purposeful) disconnect between the few who could access knowledge and the masses who could not (where there also often an illiteracy issue). Along came Caxton, when in 1476 he introduced Gutenberg’s printing press, and so started a wave of the democratisation of knowledge. But to enable the changes, there’s had to be a shift of language, a rise in literacy, an accessible reduction in the cost of books, and of course the invention of what we know as the library.
As well as the technical enablement of printing, there were also waves of change in democratization concerning the content of knowledge. The poet John Milton argued for the liberty of unlicensed printing in 1644 in Areopagitica; which in many ways formed the bedrock of the freedom of the press and academic freedom today. This also enshrines the notion of speaking ‘truth to power’, where we can all (in principle) discover and speak the truth; if we don’t hold the power to change things we can at least say it the way it could, or should, be.
The big game changer was the World Wide Web. This was a new Guternberg and Caxton for the modern age; the enablement of a new age of enlightenment. Whilst the initial concept was about communication networks, the initial focus on packet switching networks (NPL, ARPANET, Merit Network, CYCLADES) evolved to the combining of networks through research in the late 1980s by Sir Tim Berners-Lee, enabling a World Wide Web, interconnecting any node on the network. The concept has then enabled the world’s digital library with storage on the cloud, bigger than anything we could handle in a building.
Milton would have been so excited. Anyone can publish what they want for everyone to read and we can all read everything that’s out there – it’s the true arrival of the democratisation of knowledge, right? Yes, but.
Some of the old dilemmas remain. Firstly, there is an ongoing battle still over ‘open access’ because of some commodification of knowledge. In academic circles there has been a powerful business model that restricts access to knowledge (for example in academic journals). This means you can access whatever you want, but in some cases only if you can afford it. Ford (1994) calls for more knowledge sharing rather than knowledge hoarding. In the internet of things that inconnectedness is the way things are indeed going, but we’re not fully there just yet.
Speaking of interconnectedness, in a naturally joined-up world, humanity seems to have a nasty habit of creating silos, through ‘specialisms’ that so often do not talk to each other. It’s like 21st century tribalism. We inflict this disconnection on the various technologies we use, often buying numerous systems that have been almost purposefully deployed to reinforce silos.
Ensor (1988) coined the term vertical silo syndrome, meaning that many organisational structures are top down, on a vertical axis, creating real weakness in horizontal communication, interface and inter co-operation. As the opposite of ‘oneness’, Vakola and Bouradas (2005), identify that the silo culture and structure can foster blame, dysfunction and the non-recognition of a vital strategic overview – in short it’s like a disease.
We can perhaps understand the original relevance of the early twentieth century Fordist separation in the factory production function; to maximise efficiency via simple repetitive function. Yet this all breaks down if we can’t see the wood for the trees in our complex world. Fordist production and structure even ended up influencing Huxley’s Brave New World (1932), a place where everyone did indeed know their place. This approach of ‘seperatedness’ is not proving useful for us in the 21st century; where one of the great needs is to re-connect to a new more joined-up simplicity and focus beyond artificially constructed complexity. An overly complex approach does not improve insight, it leads to myopia. Ironically, despite originating as an efficiency enabler, the segregation of function and knowledge has become inefficient and hugely expensive.
If we think about the growth of the World Wide Web as the progressive realisation of interconnectedness, the vertical structure silo is the total opposite, and in that sense we should see vertical silos as regressive. Unfortunately, in many organisations very few, if any, can see the overall picture: silos put the organisation’s progress and goals at risk, by creating internal, artificial and costly barriers. Many organisations end up being incredibly ‘busy’ trying to understand themselves because of the silos they’ve put in place! To counter this, a joined-up ,’one-stop shop’ architecture is needed to bring (dis) connected concepts together in a horizontal fashion, cutting across vertical silos. Now that would be more efficient, more agile and cost effective – and it would help despecialise, and democratise, integrated knowledge.
Also, the chicken and egg of the search paradox stubbornly lingers on. Now, you’ve got an even bigger haystack to find your needle in. On the one hand a person today can reach a greater breadth and depth of knowledge and faster than at any time in the history of humanity. Yet, the more choice, means the more bewildering it can all be. So these may be exciting times and we may be very lucky but we also seem to have a severe headache about how to fully enable the opportunities that are all around us.
Linked to that search paradox (we’ve waited for so long for it, now we’ve got too much of it and can’t find it) also remains the need to be ‘knowledge savvy’. Out there in the paradise, or jungle, of the Internet is all sorts of data and knowledge. We’re still left with Klondike sifting trying to sort the gold from the dust and mud; and we’re still left with having to deductively search for the thing we want, reliant on the prior knowledge of what we were after in the first place. How do we proactively and inductively draw on the wealth of data and knowledge that’s out there? How do we discover the things that might be of use to us when we didn’t know they were out there?
Could we get the knowledge to come to us?
So here’s another wave in the democratisation of knowledge. Enter Joe Jaroch, with a background in cyber security, developing artificial intelligence capability in Chicago, who is now working on a new prototype of a proactive concept hunter with Mel Morris, CBE, based in the East Midlands region of the UK. This active form of AI brings you relevant interconnectedness without you having to ask for it (remember it’s that ‘you didn’t know you even wanted it until you saw it’), in super fast real-time, crunching masses of bulk down into punchy salient information. This is not so much of a machine resource but a form of AI colleague offering a joined-up architecture, leaving you, in this fresh wave of the democratisation of knowledge, to spend your new free time thinking about innovative ways of using the new knowledge you have. It’s called Netgraph and can change the knowledge out there from being a pejorative burden to an agile opportunity.
So a dream? Yes. Impossible? No, more an imperative; watch this space.