Radical change is generally met with a strange mixture of excitement, uncertainty and fear. It ravages structures, leaving only the most robust intact and it is followed by a long process of learning how to re-inhabit a landscape turned unfamiliar to a bygone age.
Featuring Cartwright’s power loom, Edison’s electric lightning, Benz’s horseless carriage and an abundance of other inventions, two Industrial Revolutions have already taken the world by storm, swept away economic systems, and have left new worlds in their wake.
Now, we find ourselves in the midst of a digital revolution. With a ubiquitous web, Artificial Intelligence (AI) and advanced robotics pressing forward, we are entering yet another world unknown with driverless cars, pilotless drones, machines capable of instant multi-lingual translation and mobile technologies dissolving distance.
The evolution of the revolution
The digital revolution is unfolding through a series of overlapping phases.
Phase 1: The birth of the internet
The first phase, between 1985 until 2000 saw the birth of commercialised internet: from a niche concept it quickly became the ubiquitous technology as we know it today.
During this phase, vast amounts of information suddenly came within reach in terms of cost and speed. It pushed companies to new frontiers of competition and forced them to make difficult choices about which parts of their business to discard and which to protect.
Recall those days when Microsoft started giving away Encarta CDs to drive sales of PCs, unwittingly destroying Britannica Encyclopaedia’s business model.
Phase 2: Rapid expansion
The second phase, which took off in the 1990s stretching into the present involved the creation of search engines, social media and mobile apps.
In this phase large corporations began to experience the forces of disruption more intensely as small web-based enterprises and self-organising communities started outperforming them by their ability to grow and collaborate without geographic constraint.
In this context, think of Wikipedia’s sharing economy of information, IBMs Open Source which challenged Microsoft’s hold on server software, Apple and Google embracing a role of curator for dispersed app developers, or Facebook disrupting the marketing industry by turning billions of ‘friends’ into advertisers, merchandisers and customers.
Phase 3: Mass-integration
The first two phases revolved around the internet as an industry in and of itself, revolutionising the way we gather information, consume media and communicate.
The next phase, however, is set to dramatically extend beyond the web, reach deep into traditional industries and blur the lines between the physical and virtual.
With the total stock of data doubling every two years and IP-enabled devices projected to exceed 50 billion by 2020, we have already reached a point where more than half of the world’s data technically constitutes a single document from which insights can be derived which were invisible before.
Dataists speak about releasing more data for machines to analyse and act upon in hopeful terms. They see it as a way to unlock innovation and material progress the likes of which we have never seen before in human history.
For others the increased centrality of data is a reason for great concern as it leaves us vulnerable to manipulation and instead of enabling us as a species, it could make us irrelevant.
Although we may not know exactly what the final outcome of such increased connectivity and analytical ability will look like, we are nevertheless able to catch a glimpse of some of its basic characteristics:
Hyper-scale & hyper-personal
Our physical and digital life-worlds are at the point of blending, blurring the lines further in the ways we communicate, socialise, pay, cook, learn, shop, travel, navigate, work or date.
On the one hand, we see the physical integrating into the digital with the Internet of Things (IoT). This refers to the network of devices, vehicles, home appliances and other items connected through sensors, electronics, actuators and software enabling them to connect, collect and exchange data.
Think of cars equipped with sensors to improve safety on the road, doctors who can monitor and diagnose patients from a distance in real time, or cameras able to detect what groceries we put in our cart and charge us automatically.
On the other hand, as data storage is becoming increasingly cheap, deliberately wasting storage has allowed for the creation of something completely new which enables the digital to take on physical properties: the blockchain.
As a distributed ledger, the blockchain secures information by periodically storing blocks of data in multiple computers that are anonymous to one another. It is therefore capable of imbuing data with incorruptibility, uniqueness and continuity.
Take Bitcoin for instance, while mainstream acceptance is still a long way off, it is nonetheless significant in that it is mined as a unique asset, recorded in a way that it cannot be duplicated and that despite its volatility it is imbued with real-world value.
While such integrative and interconnecting processes are widening our life-world to the point of encompassing everything, at the same time AI is growing in its capability to decipher and act on data with ever greater speed.
This process is effectively splitting that hyper-scaled life-world into billions of pieces in order for it to be presented to each individual in a personalised manner.
In simple form, we already see AI at work on Netflix, Google and Facebook where user history, location and other behavioural specifics generate a personalised feed.
The time is at hand when every single person and object of interest is connected to every other. The digital and physical will overlap at a scale of 1:1, turning the world into a self-describing and self-interpreting entity: a hyper-scaled life-world that is simultaneously hyper-personal.
Towards a stacked architecture
In the land of business, due to the prominence of software-based organisations, we are moving from pyramidic structures of vertical competition, where businesses compete for dominance at the top, towards a stacked architecture marked by horizontal friction.
In a way this stacked architecture is more like a natural ecosystem, where lower layers enable the layers above them, which in turn empower the layers above them, and so forth.
At the base, we find deep infrastructure developers, providing open access. Their value lies in efficiency, scalability and capability.
Seen in the context of blockchain technology, for example, we can see infrastructural organisations such as Ethereum, EOS, and Graphene.
Built on top of these base-line infrastructures we find curatorial platforms who set exchange rules and provide limited infrastructures of their own.
These platforms form a hybrid connection point between the stacks below and stacks above: they derive their capabilities from the infrastructures upon which they are built and their legitimacy and value are derived from the communities they host.
Built on top of Ethereum, for instance, are platforms such as Akasha, a decentralised social media network similar to Medium, and Civil which caters to a community of newsrooms, journalists and readers.
On top of Graphene, we find companies such as Steemit, which is similar to Akasha, and Spark, a remittance platform that enables communities of Money Transfer Operators, agencies and migrants to transfer cash-in cash-out remittances at high speed for low fees.
At the very top, enabled by the platforms that host them, we can find communities of professionals, entrepreneurs and users centring their interactions around particular needs and constantly evolving their niche in order to expand and retain their numbers.
Parallel to this stacked structure, we find traditional businesses rubbing shoulders as they vie for oligopolistic dominance. They draw power from the trust and customer loyalty they have accumulated over time, especially during times of public uncertainty. These businesses place big bets on emergent technologies to make incremental improvements.
In this regard think of traditional banks experimenting with technology to optimise financial services or even diamond companies as old as De Beers piloting blockchain technology to improve diamond certification by enhancing traceability.
Apart from the latter, base-line infrastructures, hybrid platforms and communities generally have no interest in competing with one another, but instead vie for market share with their peers within their respective stacks.
Sketching the aftermath
Although we see can see faint glimpses of the hyper-scaled, hyper-personalised world made up of near-infinite stacks ahead of us, there is no telling what life will be like after mass-integration.
Nevertheless, we like to imagine a scenario where complete interoperability enables our smart fridge to inform us that we are running out of almond milk. Although inclined to suggest we purchase a new batch, it is corrected by our health-monitoring watch that we are in dire need of iron and that we best spend our limited resources on ordering a lab-grown steak instead.
With our calendar reminding us of an upcoming video-conference and our weather app discouraging us from going to the store, our phone - subscribed to a local community lab - cleverly suggests we have our steak delivered by drone, which we obviously pay for on the blockchain.
What becomes of our free will in such a world that outsmarts us at every turn, is a question for another day.