Currencies of Meaning
New trusted currencies of exchange and meaning emerge to better facilitate transactions, trade, authentication and validation. Money is complemented by new systems to which we attach greater significance.
In the past things were relatively more straightforward. People were known in a local community. If they moved to a new location, state issued papers or passports would verify their identity. The provenance of goods or an object was known and if it was falsified, the identification of the perpetrator was simple. Truth and trust was easy.
Globalisation and digitization has changed this. People move and interact with each other more. Supply chains and webs are longer or more complex. As we move further into the Fourth Industrial Revolution, “characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres”, issues of truth and trust will become ever more important. As the World Economic Forum states, “the breadth and depth of these changes herald the transformation of entire systems of production, management, and governance”. Moreoever, “the possibilities of billions of people connected by mobile devices, with unprecedented processing power, storage capacity, and access to knowledge, are unlimited. And these possibilities will be multiplied by emerging technology breakthroughs in fields such as artificial intelligence, robotics, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing”.
In this new world, the breadth, frequency and volume of reputation data will grow exponentially. For every action we take, every movement we make, every trade we make, every like or comment we leave or friend we tag, we leave a reputation trail of “how well we can, and can’t, be trusted … how well we behave, or misbehave”. The reputation, of people, organisations and objects will become the dominant currency of meaning.
Today, we are already familiar with a number of reputation mechanisms that have developed in the last decade. Think of the trusted reviews of hotels and restaurants available on TripAdvisor or of rooms and hosts on Airbnb. Or the seller rating’s available on eBay or Amazon. This information allows people to make more informed choices and transact with confidence.
It has also made things easier. We inherently trust HTTPS secure websites to transact securely. Facebook Connect, allows us to port one login credential and data exchanges into a new organization. More disruptively, digital trails have enabled new trust mechanisms to be developed. For example, the decentralized ledger, or Blockchain, which underpins the crypto-currency Bitcoin, uses crowd-sourced computational power to authenticate and validate both transactions and ownership. Indeed, such is the influence of the rising data swirl that “truth” may well become what the online crowds agree, a world where ‘crowd truth verification’ is prioritised over search and media. The debates over individual Wikipedia entries veracity illustrate this well.
Organisations too have also been enabled to make better choices and keep their brands, products and users safe. Think of the credit performance data available to banks and businesses from credit bureaux (e.g. Experian) or the increased confidence in identification and secure authentication available using biometrics in passports of payment tokens such as Apple Pay. It is no surprise then that many of the world’s leading organisations now employ a Chief Reputation Officer.
Beyond consumption, individuals are starting to value and protect their data and its interpretation and meaning. From skills and endorsements on LinkedIn or Stack Overflow for the developer community, reputation matters; individuals, their peers, organisations, and society recognize that “the reputation they generate in one place has value beyond the environments from which it was built.” (e.g. Super Rabbits on TaskRabbit becoming more confident, more in control of their economic activity and more employable elsewhere). This recognition is leading to the emergence of online personal reputation start-ups who are figuring out how individuals can aggregate, monitor, protect and use their online reputation (e.g. Digit.me, TrustCloud or Legit – now part of Facebook). As Sir Tim Berners-Lee, the father of the Internet, put it: “The data we create about ourselves should be owned by each of us, not by the large companies that harvest it.”
The dark side of the emergence of new currencies of meaning may be further discrimination between the haves and the have-nots. For example, certain data indicators (sociological, biological, economic) may predict, restrict or grant access (e.g. medical care denied because your DNA is not in a national database; lack of data participation limits financial access or access to education, economic participation, employment). Not only are data inequalities a concern but also the means to act on the data could create even greater disparities in health, wealth and quality of life. This may therefore require governments to regulate in order to preserve and promote both access and opportunity.
More generally, and as revealed in Edelman’s 2016 Global Trust Barometer, inequality of trust and the flipping of traditional trust hierarchies have significant implications for both business and government. Moving forward it seems that digital trust networks, and the reputational capital they generate, have the potential to reinvent the way we think about wealth, markets, power and personal identity. This may shift who has power trust and influence.
The new currencies of meaning will have value and as such data marketplaces will likely develop, to price and manage the flow of data. Multi-layered ecosystems for those trading data will emerge consisting of buyers, sellers, creators, analysts, aggregators, governments and policy makers. New exchange and distribution models, sensitive to individual and cultural differences, will likely emerge, often local in nature. This will see an expansion in the potential for more relevant and target offers and solutions and a reduction in waste.
Increasingly it will be the combination and intelligent application of data and its’ meaning from different sources that is creating new sources of value. For example, we can already see the use of mobile location, traffic and accident data to assist town planners in the location of new cycle routes. Or the use of Apple’s health appdata to determine anticipatory actions to improve an individual’s wellbeing.
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