I love it. It’s about the rate of change in modern society. Friedman notes human history as a tapestry of steady cultural, technological and economic step-changes. But what we’re not used to, he asserts, is anincreasing rateof change. Since the year 2007 – notable for, among other things, the launch of iPhones, widespread adoption of Facebook, and the first major distributed computing services – the milestones of technological change have been reached in ever-shorter time periods.
Justin Trudeau, Prime Minister of Canada, speaking in February 2018 described the idea neatly: “The pace of change has never been this fast, yet it will never be this slow again.”
Friedman’s book has stuck with me because of its reflections on the human experience of this acceleration. Acceleration feels disorientating, destabilising and difficult to navigate. It takes effort learn how to recognise and adapt to a nonlinear environment.
The ‘Very New’ Cutting-Edge Is A Different Beast
Recently, sparked by several interesting conferences and conversations, I’ve come to notice a particularly weird example of acceleration: the cutting-edge technologies of the last three-to-six months seem to be on a different trajectory to those of the last two-to-three years.
The ‘Very New’ things, those products and capabilities which have only emerged in the last few months, are being treated differently. They are moving quicker.
It’s all still cutting-edge, almost by definition. It’s all brand new technology that is still maturing and being adopted, but the ‘Very New’ things have a few defining characteristics.
Firstly, they arrive on the scene with little warning. What was previously science fiction is suddenly announced as a viable, market-ready technology. (It’s worth noting, to paraphrase Jenn Hirsch, the existence of a sci-fi precedent is itself an important feature).
Secondly, they are expected to reach global-scale adoption at a much faster pace. The market is starting to appreciate what pace the modern ecosystem can perform at. New technologies can get to market at unprecedented speed, thanks in part to new manufacturing techniques, interoperability standards and agile software deployment.
Finally, the latest innovations are set to leapfrog standards which themselves have barely emerged.
Take, as one example, high-tech user interfaces for personal devices. Last week I saw Thomas Reardon, CEO of CTRL-Labs, demonstrating a new wristband capable of decoding neural signals from the brain and translating them into machine-readable instructions. Right now it can handle movements, not abstract thoughts. The field is emerging but expected to be fast-paced, given how it’s tracking closely advances in deep learning for neuroscience applications and is receiving not-insignificant investment; the crowded field in neuro-controllers includes – among others – Facebook and Elon Musk’s Neuralink.
Now let’s compare that to the other cutting-edge. Can we identify another set of user interfaces that have been maturing over the last few years? I’d say gesture-recognition systems have had momentum during this time, while still going through the process of widespread adoption. For example, radar-based gesture control is only just poised to come to the next generation of smartphones, and the functionality is also likely to be supported in Apple’s hotly anticipated but long-awaited smart glasses.
How will the rapid arrival of wearables capable of responding to discreet thoughts and tiny movements affect the market? Considering the value for near-future users of personal devices – with smart glasses as a stand-out example – neuro-controllers may well immediately leapfrog gesture controllers, setting a new standard before the old one even had a chance to take root.
As technology change accelerates, the cutting edge is at risk of being outpaced by the very-new cutting edge.
How can we properly assess the impact and externalities of new technologies if they are coming to market faster and faster? In an accelerating environment, the task of academic, regulatory and media institutions quickly becomes overwhelming.
In regulated sectors, such as healthcare, the risk is of unnecessarily slowing down the adoption of valuable (indeed, lifesaving) innovations. Leaders in AI healthcare note that the scientific peer-review process alone now takes longer than their ability to go-to-market, not to mention the timescales for subsequent processes such as clinical appraisals, procurement and change management.
Suppliers also feel the pressure of acceleration. When products are being shipped so quickly, developers are afforded less time to consider the nature of their work. A doteveryone survey from last month found that nearly two-thirds (63%) of UK tech workers would like more opportunity to think about the impacts of their products.
Enterprise Adoption At The Cutting-Edge
If today’s cutting edge is at risk of immediate obsolescence, how can enterprise buyers make sure their technology investments are up-to-date and fit for the future? To address this challenge BJSS works closely with clients to develop a fit-for-purpose technology strategy. Some of the themes we tackle:
- Buy flexible solutions, work with technology-agnostic partners.Avoiding tightly coupled solutions or vendor lock-in becomes a strategic imperative, rather than a nice-to-have.
- Innovate with Velocity. Through our Innovation Labs, we facilitate short exercises to deliver rapid, incremental value using AI and Advanced Technologies.
- Cut through the noise. Hype and confusion around advanced technologies create a good environment for those who practise deceptive marketing. Understanding the market and remaining vigilant to snake oil (or ‘vapourware’) vendors is crucial.
- Invest in engineering quality.It’s not unusual to meet practitioners struggling to keep on top of day-to-day progress in their field. BJSS protects the engineering quality of our advanced technology solutions by researching the whole market of available solutions, as well as investing in training about how to deploy them properly.