The Age of the Machine

Robot slaves performing menial tasks.

Is this all we’ve got to look forward to as machines take over the world, capitalising on their ability to learn and create faster, more accurate decisions? Could it be that advanced algorithms are becoming the biggest threat to business and our way of life now machine intelligence is proving superior to our own?

The digital revolution amazed us with products and services tracking our every move, placing location and context at our fingertips. Machines began to tell us where we could go and how long it would take to get there bearing in mind the weather, roadworks, driving conditions, etc. Today, machines are not only capable of identifying possible routes, they’re predicting (with a high degree of accuracy) which path we’re likely to pick.

In almost every field, machines are outperforming humans. Not surprisingly, the automation of machine learning is opening businesses up to a new reality where they become self-optimising, real-time decision-making engines that enable new business models and maximise revenue streams.

So, should we be worried about machines making humans redundant? The reality is that machines can operate businesses more efficiently and effectively, allowing us to devote our time to innovation, transformation, and creativity.

Machines powered by big data

Gartner’s last ‘Hype Cycle Report Of Emerging Technologies’ showed machine learning taking the most prominent place on the curve, replacing big data altogether. Whereas, in previous years, the focus might have been on big data potential, today, we understand that business success is achieved through the development of sophisticated algorithms.

Machine learning may be the new black, but it’s not new. It has been used extensively throughout the academic community where specially designed experiments create large volumes of data that require complex analytics. And now businesses have moved beyond big data, they need new techniques to handle the massive amounts of streaming data.

Data is capturing more knowledge, experience, and learning, than we can comprehend and process. Algorithm intelligence is directly related to the data we provide; the bigger the better. As I’m sure you’re aware, the machine-learning algorithms we use today would be dumb without data. And just as humans improve with experience, algorithms improve their accuracy in step with the increasing amounts of data they work with.

Moreover, studies have shown that when it comes to predicting events, machines outperform humans in most cases. The human mind is constrained by the volume of information it can process, what it can hold in memory at any given time, and the difficulty of identifying complex, hidden patterns. These skills are essential in big data world where the volumes are enormous in scope and complexity.

Mind over machine

Traditional businesses are run by management and executive-committee members trained to make decisions that impact the daily business. Executives who base organisational decisions on intuition, gut-feel, and experience, are now up against a data-driven, machine-learning approach that benefits from the massive amounts of data collected.

As a business, we encourage management teams to develop bonus-maximising behaviours which result in suboptimal decision making. They focus on the data that supports personal theories and preconceived opinions, discarding contradictory information. This bias is compounded by the fact that they’re under pressure to deliver ever-greater results, quickly.

Reliance on a series of mental shortcuts rather than the assessment of evidence impairs our judgement. Consequently, it makes sense to hand over our future decision making to machines, an act which will change business, society, and the economy, for good.

This embedding of machines is forging new relationships between people and machines. It’s putting science at the centre of business life and opening up new ways of doing business through fresh technological capabilities and new corporate cultures.