It has been a while since we, the human species, have been involved in a revolution that has the potential to affect every single person on the planet, says Marta Portugal Senior Data Scientist at Merkle Aquila
Revolutions happen when there’s a need for change and evolution. One can argue that a main incentive for the industrial revolution in the eighteenth and nineteenth centuries was the realisation that we were reaching the limits of our physical abilities, and that we needed to evolve if we wanted to reach optimal efficiency.
The industrial revolution changed the world, and almost every aspect of our day-to-day lives is impacted by the residual effects of it, simply because it made our lives easier.
So, what exactly constitutes a revolution? According to the Cambridge dictionary, a revolution is “a very important change in the way people do things.”
Can we say that AI is fundamentally changing the way we do things?
A large proportion of the population use some sort of intelligent (AI powered) navigation system when wanting to go from A to B; it is used to stabilise the cameras in our phones helping us taking better pictures; AI programmatically determines which content is displayed to us when browsing through our news feed; itis used to reduce global hunger by assisting with crop monitoring and water irrigation; or used as a secondary medical diagnostic technique. Yet despite all of these examples, we consistently reject the idea of seeing AI as a necessity, more often than not downplaying the role that these useful co-bots play in our everyday lives.
So why is there resistance to this revolution?
As history has proven time and time again, no revolution is ever welcomed by everyone in the same way. Although there are several challenges that AI still needs to overcome, such as problems with job security and ethics and accountability, none is more important than widespread societal acceptance and adoption.
Reservations around digital transformation and the adoption of AI could not be truer than for the Oil and Gas industry. As a field that has deep-seated concerns regarding accountability, safety, and job security – whereby there is much more on the line when things go wrong – the industry treads very carefully when it comes to change.
However, these same solutions which are transforming processes – safely and reliably – in other industries have undeniable relevance to Oil and Gas. The ball has certainly started rolling but I think it is time to acknowledge AI as a viable solution to some of the industry’s main pain points. If facial recognition is a stable technology for accessing mobiles, then it can help monitor critical machinery on installations; if AI can be used as a medical diagnostic tool, then it can help identify single points of failure in operations; if AI can assist in human health and safety through AI monitoring systems, then the same will be true of increased remote management of unmanned installations.
Just as with the industrial revolution, where there was a clear need for evolution, the AI revolution relies on the fact that we are reaching the limits of our mental abilities and we should leverage all available resources to overcome these barrier to avoid stagnating.
What’s the solution, then?
As data science professionals and aficionados, we have a responsibility to lead the discussion on the usefulness and potential applications of AI. Educating society on the importance of leveraging AI goes well beyond the usage of mantras such as “Data is the new oil” or “AI is the new electricity”. So, how can we lead?
As media tends to predominantly cover instances whereby AI has failed, there has been widespread distrust. However, considering we are immersed in this revolution, it is a data scientists’ responsibility to highlight some alternatives to not using AI – crop failure and global warming being examples. Digitisation has started transforming the Oil and Gas landscape – from unmanned operations to predictive maintenance – and the best in AI and digital is yet to come. Right now, we can see AI being used to automate inspection; however, in the future you will see the robots and drones will be doing the interventions themselves – such that staff can focus on additional matters onshore. Competency assessments will be digitised, optimising time and energy for the workforce in training processes. Some of us even fantasise about industry professionals each having their own VR robot (think Jarvis from Avengers) which could monitor manual activity and check for quality assurance. AI can and will be used to optimise productivity, costs and safety in the workplace and, truth be told, those who close themselves off to these changes will lose their competitive edge.
So, our challenge as data scientists will be ensuring that we bring ethics and transparency to the table, first. This means delivering the black box in language consumers can understand – translation requires effort, so we as a community must work on this, put as much effort into improving our communication as we do in our coding.
With time, patience and a lot of debate, and as AI becomes more and more ingrained in our lives, the value that AI can bring when allied with human intuition and context will be the next step in our evolution. At least until the next big revolution comes knocking…