28th Feb 2013
The recent story about the new Seesaw crowdsourcing app got me thinking about the impact of digital on decision-making, collaboration and creativity. This is what Seesaw says about itself: “The purpose of Seesaw is pretty simple: you can instantly create a poll by taking a picture, and have friends (and strangers) vote on it. You can then send out a request for decision-making help through social networks or text message –
“It might seem a little silly for simple decisions you make throughout the day, but since all it requires is a photo you can use it for all types of different decisions, from home makeovers to vacation plans.”
My initial response to this concept, was the empirical point – that just because technology enables you to do something – that doesn’t necessarily make it a good idea. Does it really make sense for us to outsource all our decisions – to rely upon ‘the kindness of others’ – just because technology makes it quick and simple? What about the more established, but less fashionable approach of providing one’s own perspective or sourcing opinions and information from a select group of experts?
So – when is it a good idea to ‘crowdsource’ and when is it better to look to oneself or to a select group, for guidance? This question is particularly prescient in the digital age, where there are concerns about the effect that the web is having on the integrity and veracity of information available to us.
From my perspective, the debate about the pro’s and cons of crowdsourcing first came up at dinner in the house of friends – precipitated by a conversation regarding the advantages and disadvantages of Wikipedia.
One of my friends and I were in favour; our supporting arguments were – that it is democratic in style and structure, it covers a huge range of topics and is regularly updated .The two other dinner guests were not fans. They were much more in favour of the Encyclopedia Britannica model – content created by a small group of ‘experts’ – covering a smaller range of subjects and less regularly updated; but not affected by web ‘Trolls’ and differences of opinion that can affect the quality of online content.
A parallel to these different approaches of ‘esoteric vs. exoteric’ information gathering and application – is provided by the world of politics. Specifically the system of democracy – from our Greek – δῆμος (dêmos) “people” and κράτος (kratos) “power”
Democracy is traditionally an inefficient organisational model. It’s first apparition in the Athenian city-state around 550 BC wasn’t democracy, as we now understand it, at all. It only included people of a certain social rank and excluded women. Other ‘ocracies’ such as autocracies, theocracies or gerontocracies, are much more efficient systems of government. A good example of our perspective in this area, is how we are often derisory about any decision making process, when carried out by a committee.
The concept of using crowdsourcing (a.k.a. a democratic system of informational inputs) is an established and successful approach that has been around a long time before the web.
These examples of crowdsourcing in France and Britain go back to the early 19th Century:
The French government proposed several crowdsourced competitions, often rewarded with Montyon Prizes, created for poor Frenchmen who had done virtuous acts. These included the Leblanc process, or the Alkali Prize, where a reward was provided for separating the salt from the alkali, and the Fourneyron’s Turbine, when the first hydraulic commercial turbine was developed. In response to a challenge from the French government, Nicholas Appert won a prize for inventing a new way of food preservation that involved sealing food in air-tight jars. The British government provided a similar reward to find an easy way to determine a ship’s longitude in the The Longitude Prize. (Do have a look at this wonderful book on this subject) .
In the digital era there are plenty of different types of crowdsourcing – for example crowdvoting, crowd funding, micro work, prize contests and implicit crowdsourcing-. Here is wikipedia’s summary of the concept.
“Crowdsourcing is the practice of obtaining needed services, ideas, or content by soliciting contributions from a large group of people, and especially from an online community, rather than from traditional employees or suppliers”.
A varied and impressive list of successful crowdsourcing examples includes – Google, Amazon Mechanical Turk ( mturk.com), Kickstarter and Crowdrise.com.
When sourcing information it makes sense to balance an expert / detailed perspective alongside broader, democratic inputs. This has long been apparent in other worlds, such as that of research, where one often combines qualitative (eg. focus groups) and quantitative (increasingly web based) methodologies.
The logical culmination of the journey, from individual or select expertise passing through the ‘plurality of crowdsourcing’ and on towards a process of more quantitative and systemic information gathering – is the semantic web, the web of big data – or Web 3.0.
Tim Berners Lee defined the semantic web as a ”a web of data that can be processed directly and indirectly by machines.”
From Wikipedia again – ‘The main purpose of the Semantic Web is driving the evolution of the current Web by enabling users to find, share, and combine information more easily. Humans are capable of using the Web to carry out tasks such as finding the Estonian translation for “twelve months”, reserving a library book, and searching for the lowest price for a DVD. However, machines cannot accomplish all of these tasks without human direction, because web pages are designed to be read by people, not machines. The semantic web is a vision of information that can be readily interpreted by machines, so machines can perform more of the tedious work involved in finding, combining, and acting upon information on the web’
Crowdsourcing is merely a step on the path towards a more structured, quantitative mode of information attainment. It is an interim moment, between the reliance on individual inspiration that arrived with the Age of Enlightenment …and the logical conclusion – our reliance on machines and big data.
However much we may dislike the random democracy of some crowdsourcing systems, at least they have the unique charm of human fallibility and serendipity – something that will be glaringly lacking from the mechanized systems of the future.