The rise of the smart machines may have a Terminator-esque ring to it but the definition of smart machines is rather wider than that image might lead one to believe. Smart machines or self-learning machines are fundamentally machines which deal with highly complex data and uncertainty but still manage to form and test hypotheses, drawing probabilistic conclusions. They are cited as representing the next generation of computing and some say will affect society to the same extent as the industrial revolution.
What might they look like?
Importantly, smart machines, as machines which effectively self-learn, represent a far more important proposition than simply the eye-catching projects of Google’s driverless cars or Amazon’s deliveries by drone (or even robots like the fictional Terminator cyborg). Businesses must prepare to acknowledge and implement machines and computers which will affect not just the easily mechanised logistics and manufacturing sectors but the knowledge work of lawyers, doctors, managers and consultants.
Smart machines are already established in some industries where the efficiencies they bring are more obvious. Rio Tinto, for example, utilises self-driving trucks, albeit on private property. Indeed, virtual customer assistants are becoming more commonplace online and some question and answer programs can be classified as ‘smart’ insofar as they are capable of learning from the answers human customer service assistants give in order to refine their own answers.
However, the same principles are at work in the competing voice operated systems of the American tech giants. As consumer expectations change, and as a new generation of children grow up in the midst of this technological upheaval, the voice operated programmes of Google’s Google now, Apple’s Siri, and Microsoft’s Cortana will increasingly represent a standard way of computing or searching the internet. Crucially, smart machines will be facilitating this new way in which we input data into computers.
Where are we up to now?
Already evident are the increasing amounts of automation present in the professions, which have freed up workers to undertake less repetitive tasks such as exercising judgment and intuition whilst the machine performs generic or administrative tasks. Perhaps the greatest effect such technology is predicted to have is that of its impact on that very human of tasks of exercising judgement and intuition. In this respect, smart machines have been cited as being able to help make human experts smarter by examining the user or expert’s actions, their tendencies and habits. The smart machine or assistant will be able to proffer advice to the expert to help her do her job more efficiently.
Competitive businesses are already building their own smart machines and computerised advisers. The benefits of having such machines, which are continually on the lookout for efficiencies or better plans and investment strategies, will be appreciated by any business, including those in the traditional knowledge sectors.