By Martin Pienaar, COO of Mindworx
Should you be worried about being replaced by a robot at work? No… at least not yet.
It’s too soon for most of us to worry about our jobs being obliterated by robots but already there is hardly an industry that is not impacted by exponential technologies like robotics, artificial intelligence (AI) and machine learning, smart algorithms, the internet of things, and even blockchain. As they increasingly become part of the mainstream, they will disrupt every aspect of our lives – not just work.
But asking whether you can be replaced by a robot is the wrong question. You should be asking two other questions instead:
- Which aspects of my job would be difficult for a machine to replicate? Once you have this answer you can focus on how to perform really well in those areas.
- How can I co-exist with new technologies? Right now, you should be able to automate about 30% of the mundane and routine admin processes your job requires, liberating you to focus on the more meaningful aspects of your professional life while preparing you for increased automation.
Instead of looking at the future negatively, I see lots of hassle being off-loaded, freeing up time for higher level thinking, deeper engagement and more thorough research. All of which should make us more productive.
Only a handful of occupations are completely automatable using today’s technology. Examples include:
- Sorting agricultural products
- Sewing machine operators
We also need to think about all the products and services that will be enabled by disruptive technologies but which haven’t been envisaged yet. The Boeing Dreamliner 787 generates a terabyte of data every hour it’s in the air and there are hundreds of them in flight around the world at any given time. But such a volume of data was useless until recently when machine learning gave it value. Today, General Electric, which manufactures Boeing engines, is able to spot trends in hardware failure, fuel economy, and weather issues. They can use the data to optimise safety and altitude selection, and can even order a plane down quickly if something catastrophic becomes evident.
There are lots of other datasets like this that will become useful and valuable with the advent of artificial intelligence. Google is using datasets to optimise its data centres, resulting in them using 40% less electricity. In Australia, mining company Rio Tinto has become 20-30% more efficient by using robotic diggers. And every major motor manufacturer is experimenting with self-driving cars; they have to if they want to stay in business. A decade ago, who would have thought that the leader in self-driving cars would be a search engine? Tesla recently sent a software update to customers who were geographically located in the path of hurricane Irma to increase the distance they could travel, in order to allow them to evacuate.
From diagnosing disease and teaching, to optimising supply chains and making deliveries by drone, there is not an industry that is not going to be impacted by exponential technologies.
Algorithms and big data have been around for decades, so what has changed that’s suddenly made all of this possible? Lots of things, including:
- We’re now layering technologies on top of each other
- Computer chips are faster and have much greater processing power
- The chips inside video games have become exponentially faster and are being used for other applications, like crunching algorithms
- We’re writing better algorithms
- Much larger datasets flowing through algorithms is allowing them to learn faster
- Faster network speeds
At the moment there are jobs that are difficult to replicate with machines and algorithms. Business analysis is one of them because it calls for judgement and collaboration. Business analysts should be at the forefront of re-imagining business processes and systems to keep our companies and industries competitive. Banks and retailers have led in this space for some time, but will they lead or lag as the world shifts gears?
Think about this…
In South Africa our banking sector employs about 120 000 staff. Less than 50% of bank processes are digitised end-to-end. People intervening in processes increases cost and often results in errors. Automating these processes could improve costs by up to 80% and service levels by more than 50%. It’s no wonder that there are so many areas of banking being attacked by lean, digital competitors, and fintech startups. 120 000 staff happens to be close to the number of employees Kodak had in the late 90s when it dominated photography in North America with a 90% market share. Kodak invented digital camera technology but didn’t understand the exponential path that the technology was on and failed to invest heavily in it. Kodak filed for bankruptcy in 2012. The banking industry will have to invest boldly and wisely in this exponential world to ensure that it does not suffer a similar fate.
But this is not the end of work for humans. While many tasks in our jobs will become automated, there are very few jobs that will be completely automated away. Also, as companies digitise, many new jobs are being created too. Just a small selection of jobs that didn’t exist a decade ago are:
- Cloud computing specialist
- Driverless car engineer
- Blockchain developer
- Uber driver
- Social media sentiment analyst
- Mobile app developer
- Drone pilot
- YouTube content creator
- AI trainers, explainers and sustainers
Since the education systems around the world are not keeping up with the changes that technology is enabling in the workforce, it is the responsibility of parents and corporations to ensure that they are preparing the workforce of the future. Our Mindworx Academy is an example of an organisation preparing young graduates for this new world. Hiring for potential and not based on past results. Since we don’t know what work these new entrants to the workforce will be doing, they will need to solve problems we have not yet encountered, be creative, show resilience, be adaptable and have excellent written and verbal communication skills. Analytical ability is a requirement in more and more roles, employees can backfill these skills using online courses. It’s not just entry level employees that will need to be assessed for potential, as machines replace tasks, employees at all levels will need to learn new skills.
We also see more and more employees leaving formal employment to join the “on demand” or “gig” economy. Research has shown that employees who choose self-employment are more satisfied in their work. They are forced to continually invest in their skills to stay competitive. Companies benefit from these skills and are able to scale up and down quickly depending on a project’s skill requirements.
So while not all gloom and doom, we all have to stay abreast of changes in technology, and learn and unlearn as we go. We need to invest in ourselves and our businesses to remain relevant and be nimble to avoid being taken over by a robot.