Slowly but surely, artificial intelligence (AI) is finding its way into our factories. It promises to profoundly transform our entire industrial sector, one of AI’s primary application areas. But while its benefits in that area are already quite clear and real, there are still several barriers to its use and democratisation. Not the least of which is a lack of training and education on the subject of AI.
Offering assistance in decision-making: such is the primary role of AI in today’s industry. So far, we can distinguish tree different levels of assistance, respectively known as descriptive, predictive and prescriptive AI.
Descriptive AI uses big data analytics to simplify information and present it on a KPI dashboard. This significantly saves time, as analyses performed using AI techniques are quicker, cheaper and far more reliable.
By providing probability-based projections, predictive AI takes things to the next level. It effectively allows factory employees to anticipate situations more easily. And it makes for better predictions on manufacturing failures, for example, or on risks around the supply chain.
Finally, with prescriptive AI, the assistance provided is no longer limited to just presenting the necessary information for decision-making. Artificial intelligence now also guides the employees, offering recommendations known as the ‘next best action’. In some cases, AI can even be used to relieve humans altogether of low-risk or non-strategic tasks. Warehouses, to give but one example, are increasingly entrusting sections of their logistics to driverless vehicles.
‘Augmented’ employees and cobots
This naturally brings us to an area of technology that in recent years has been completely transformed by the huge and rapid progress made in the field of AI and, more particularly, that of machine learning: industrial robotics. Not only have industrial robots become more autonomous, to the extent that they can move entirely on their own now to the location where they are to be deployed. But at the same time, by improving their capacity for (self-)learning, they are also able to cooperate far better with humans - thereby giving rise to the term ‘cobots’, short for ‘collaborative robots’.
And then there is the whole area of eXtended Reality technologies (XR), ranging from Virtual Reality (VR) and Augmented Reality (AR) to Mixed Reality (MR). Apart from providing operational assistance, these new AI tools are also helping factory employees gain a better understanding of their environment. This in turn allows them to move away from repetitive, monotonous and time-consuming jobs and focus instead on meaningful jobs with high added value.
In the end, as is usually the case with new technologies, the key to unlocking the potential of artificial intelligence lies in our willingness and readiness as humans to adopt it. This is where the true challenge of democratising AI resides. In industry, as in any other sector, this requires employees to be adequately trained. Luckily, progress made in the field of Human-Machine Communication (HMC), as exemplified by AR-headsets and voice-based tools, is likely to simplify this long and arduous task in the coming years. Which basically and ironically comes down to AI breaking down the barriers to its own democratisation.
Next to this human barrier, technical (e.g. data quality) and legislative (e.g. GDPR) challenges are also limiting the use of artificial intelligence. More about these challenges can be learned from a corporate blog post written by some of my colleagues, which inspired this blog post. You can read it in full here