A look at the nature of disruption, the characteristics of the innovation that underpins it, how disruption happens, and which industries are next in line. In short, are the machines coming for our jobs?
Disruption, often imagined as a lurking threat ready to destroy established businesses and business models, are on everyone’s minds of late. Disruption’s danger lies in its ability to transform expensive and complicated technologies and services, previously accessible only to people with financial means and skill, to be affordable and accessible by many. Think of the mobile phone, digital camera or solar panels as examples. Disruption also describes the speed with which this process can happen.
Disruptions don’t necessarily occur as once-off technological breakthroughs, but through cost and efficiency replaces its predecessor.
The big question of course is what and who will most likely be disrupted next?
The Singularity University (SU) Summit that recently took place in Johannesburg, South Africa, convened technologists, businesses and futurists to discuss these among other topics. The technology think-tank, funded by several Silicon Valley companies including Google, works from the assumption of the exponential nature of technology and its relationship to price and access.
David Roberts, a member of the Innovation and Disruption faculty at the think-tank, described the characteristics of industries ripe for disruption as industries where trust is broken, where the experiences are complex, that fundamentally serve as intermediaries, and where access is limited.
And the disruptors? Usually entrepreneurs who are not experts in the domains that they disrupt, as Deloitte’s Larry Keely, an innovation consultant said.
Disruptions usually comes in a digital format. Roberts explained that anything that becomes an information science is likely to be disrupted, since it then becomes underpinned “exponential technology”. An exponential technology doesn’t just double in performance every year, but its price-to-performance ratio doubles – which means technology doesn’t have to become better to be disruptive.
The concept of exponential technologies is not unchallenged, and critics point out that Moore’s Law (which predicts that computing processing power doubles approximately biennially) has been slowing down in recent years as physical limitations have come to determine the number of conductors that can be fit in close proximity. Other critics question the scientific foundation of exponential technology.
Yet, disruption coinciding with exponential technologies remains a compelling argument, with developments in distributed and quantum computing seemingly taking the slack of Moore’s Law as it still unlocks new processing power and other efficiencies.
The mechanics of innovation
Disrupting technologies don’t merely describe tangible products such as mobile phones, but complete new ways of thinking instead, such as the services like Uber that run on mobile phones.
Larry Keely dissected innovation into ten types, separated into three groups:
Keely believes modern innovation is not breakthroughs, but like Lego blocks, iterative and built on existing tech stacks that are combined in a meaningful way. His approach echoes the notion that you don’t need to understand the underlying principles of technologies, so much as understand its capabilities. He also said that in most instances innovation is no longer built on proprietary technologies.
To be innovative requires breaking down social problems into simplest forms, and solving them by combining the above ten aspects of innovation. Keely also stressed that innovation is decentralised, and best situated on the fringe of business interest where it is allowed to develop and help pull the business in new direction. An example of this is that developments in Uber are driven at the city level.
Companies also regularly underestimate innovation and its value in the company, since by its nature it sets out to question and change routine business operations, and includes failure as part of its process.
His advice to companies: trust talent. Create incentives at the top and bottom levels in a company; at the bottom level to allow innovative ideas to rise up, and at the top level, to avoid good ideas from being shut down.
Which leaves the question: who’s next?
Ripe for disruption
Various industries have been identified as ready to be disrupted. These include the energy sector, the banking sector, transport and mobility, and the health sector – all of which fulfil the above criteria outlined by Roberts.
Some industries, such as the energy sector, are already undergoing disruption. The dropping price of renewable energy is threatening to disrupt utilities such as Eskom, undermining its revenue model, to the point where Eskom has refused to sign further REIPPP Programme power purchase agreements. However, as Ramez Naam, an energy expert at the think-tank pointed out, customer demand for their own solar power and the introduction of battery technologies render the disruption inevitable.
Along with dropping energy prices, developments in material science have helped decrease the amount of energy required to filter and desalinate water for example.
Transportation too has been a stagnating industry which has recently become digital information driven and is now being disrupted on several fronts: first with the arrival of electric vehicles, and lately by the advent of autonomous vehicles. Freight transport can also do with efficiency improvements, especially with optimising empty load trips.
Each disruption raises serious concerns and debates – and this is where expert opinion diverges. How will society deal with those excluded by disruptions, such as those on the wrong side of the digital divide? What does the prospect of abundance (be it of energy or information access or any other equivalent) mean for businesses and profitability, and how are products and services monetised? How effective are existing social safety nets? What could new social safety nets look like? Will it be in the form of a universal basic income? And who is to pay for or implement it?
One of the most hotly debated topics are around the future of work, particularly what automation and artificial intelligence mean for employers and the workforce. It also considers the rate of this change.
There are legitimate concerns about the changing nature of work, and what that means for a workforce, companies and governments in developed and developing countries. The impact of automation and artificial intelligence have been particularly divisive topics, with proponents envisioning a more skilled workforce and higher quality work, and critics fearing mass unemployment resulting in inequality and social instability.
In South Africa the mining and manufacturing sectors are already witnessing the transformation, led by greater needs for efficiency and productivity in order to remain profitable.
On a practical level a changing workforce begs the questions of what will happen to employees, and where will demand for product come from when there’s no income to go around?
Utopianists look forward to a future where machines are included into the economy and have the ability to earn and spend money like humans – something already made possible by public ledger technology such as the blockchain which automates peer-to-peer transactions. You’re asked to imagine a world in which your autonomous vehicle can navigate to and pay for itself at an automated car wash, then go about earning money as a shared Uber-like service, and still be ready should you like to use it.
In this futuristic worldview humans are freed from the shackles of labour to write poetry all day – an overtly rosy scenario very reminiscent of Ambrose Bierce’s satirical description of the future as “That period of time in which our affairs prosper, our friends are true and our happiness is assured.”
For most, blue collar and increasingly white-collar workers, the prospect of unemployment and boring oversight work are more realistic, and frankly, daunting.
Already the nature of work has transformed, with new sectors now including what’s called the sharing economy and the gig-economy; both of which rely on a temporary, freelance workforce for scalability purposes. Many of these workers don’t have company benefit such as health care, and instead manage their workload, at least in theory.
The general consensus across ideological divides and even among experts who disagree fervently about the full impact of automation and artificial intelligence, is that education is key to the transition, especially due to the rate of change and changing skills demands.
Institutional learning is touted as the antidote for scarce and unevenly distributed skills, with the general expectation that the workforce will have to be reskilled on a regular basis, or be educated in a process that will require them enter and existing the workforce for periods at a time. This will also change how people learn, away from long durations of learning to more day-to-day and short bursts of learning.
The voice of government institutions was noticeably missing from discussions at the summit, and duly so. Governments globally are seen as slow to adapt, often incapable of dealing with institutional change, and particularly slow to respond to technologies and processes that their electorate adopt without hesitation. While there is certainly a role and need for all sectors of society to formulate a response to societal change, don’t expect the lead in the transition to come from government.
Deloitte’s head of digital and innovation, Valter Adao articulated it well: change is easier when you drive it, than being on the receiving end of it.
In the short term, this should serve as good reason for any business to reassess its role and place in the market in relation to potential disruption, reconsider its attitude towards innovation and institutional change, and articulate the role of its workforce in a changing landscape.
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Source: EE plublishers