Rise of the Machines
We’ve all heard — a robot is likely coming for your job very soon.
A PwC report in March 2017 estimates that more than 10 million people in the UK will lose their job or find their field of expertise obsolete within the next 15 years through the rise of automation and robotics in the workplace. The Telegraph ran an article in September 2017 based on research by the Oxford University in 2013 which identified the percentage likelihood a job was at risk of automation — good news for those in social care, bad news for telemarketers and librarians.
The majority of the press rhetoric seems to centre around humankind being doomed, especially if your job is repetitive or falls into a low income category, although interestingly, the PwC report indicates that men are more susceptible to automation than women. Jeremy Corbyn even mentioned the need to ‘urgently face the challenge of automation….a threat in the hands of the greedy’ at the 2017 Labour Annual Conference.
Well guys, I don’t agree, as I think there is a lot more to it than meets the eye.
For me, I believe there are two key reasons why robotics and A.I can actually be good for us mere humans…….
Hear me out on this one. It is inevitable that businesses will look to automation to save costs, but if this is the only driver, then simply, you are doing it for the wrong reasons. The boardroom may be won over by those falling pound signs, but your business is only as good as the customers you serve. Which is why I think you need to consider the following when making decisions to automate:
Simply, automation in the right context, where the customer expectation is to have a quick, simple experience and where human interaction adds zero or little value will make the customer experience better.
Take checking into a hotel as an example.
Research has shown that receptionists have a 96% chance of being automated, but we need to consider the context. If you, for example, are staying a night or two in a reasonably priced, no frills hotel (I’m talking Premier Inn and Travelodge ball park), automation could play a part here as you generally just want to check in and get your key. A machine can do this for you and you would have likely made any reservations following suggestions when booking, probably via a Chatbot. Flip side, if you are staying in a 5* luxury hotel, part of that luxury feel is the human interaction and service you get upon checking in, so frankly, a robot or machine in this context is not going to cut it. Opening doors, pleasantries, recommendations for dinner or taking the time to ask questions to make your stay even more memorable could probably be automated, but the human touch has such added value to the experience, it would be detrimental for the hotel to move away from this.
This thinking isn’t just limited to services. As an employee, you want to have work that is stimulating, enjoyable and safe and leaders want to make sure their teams are working at peak productivity. Automating repetitive tasks means less boredom for you (sorry, data entry can be incredibly boring) and more time focusing on tasks that are more complicated and interesting, but also have a human social element. If these repetitive tasks are manual in their nature (i.e. picking orders in a warehouse — Amazon have deployed this to great success, with a fleet of robot pickers overseen by human ‘handlers’), it reduces your risk of sustaining a strain injury or much worse. Bonus for you and your organisation.
Within the housing context, there are plenty of opportunities to deploy robotics, A.I or machine learning to complement and enhance existing service offerings. People are generally afraid of letting go of their work as they fear they will become obsolete, usually stemming from a lack of confidence in their own ability. In this day and age, transactions as simple as a customer making a payment, asking for a refund or setting up a Direct Debit online should be automated as much as possible, with minimal, if any human interaction, but elaborate, manual processes still exist in some housing associations. Organisations should take this opportunity to gain inspiration from other sectors, looking at their processes and show colleagues how focusing on tasks that require their more specialist skills works in the interest of everyone. Which brings me nicely onto the second point…..
Socrates makes an excellent point here. Mankind built these technologies as a response to change and challenging what was possible. Advances in robotics and A.I may have put some jobs on the path to extinction, but by the same token it has created a whole host of new ones at the same time. Leaders and individuals should embrace these movements and use it as an opportunity to grow not just skill sets, but service opportunities. This isn’t just about teaching yourself to code or become a tech whizz either (although it is really fun and surprisingly useful! Mimo, General Assembly and Codeacademy are all good places to start). In the Amazon example above, many of the human handlers were previously employed as pickers, but instead of making them redundant, the new technology actually created a new role for them. One that didn’t require an ability to be able to program machinery. Look at the jobs social media have created too — content managers, influencers, brand architects, none of which require anything more than being human and a real skill at the various social media channels.
Going back to housing, one of the biggest opportunities for them lies in the advances in machine learning, particularly in data analysis. We collect so much data from our customers and day to day activities and until recently, as a sector, we’ve just sat on it! There is so much power to be gained from analysing data and using this to make service decisions — this is paramount here in the Lab and made hugely easier thanks to our talented Insight colleagues. I’m really excited to think about the endless possibilities available to apply machine learning in identifying data patterns, build prediction models and improve data visualisation but the best thing is, you only have to have a basic grasp of code (Python is highly recommended) to get started. If you’ve ever read Freakeconomics by Steven Levitt, he has been doing something similar for years, but machine learning makes this possible on a whole different scale and accessible to those without an economics degree.
So, in true Jerry Springer fashion, my final thought is this. Humans have much to gain from these advances, but only if we use our human social skills to make the right decisions. That’s something that even the most amazing developer will find hard to replicate.
We only have to worry if a company called Skynet appear — in that case, I recommend watching all the Terminator movies and hoping for the best.
Hasta la vista baby.