Talk about artificial intelligence and, as day follows night, someone will bring up AI leading to mass unemployment. There’s a likelihood there’ll be some mention of robots rising up, potentially an allusion to Terminator 2 and Skynet. It all gets very dramatic. The narrative is very much one of man versus machine – that it’s only a matter of time before we’re battling robots with supreme AI for our existence.
Architects of our own doom
There’s two problems with this. Firstly, if that is the case, we are architects of our own doom. Who built the machines in the first place? Who prioritised convenience, speed and low prices? We did. Look at retail – across the globe bricks and mortar shops are struggling to stay afloat. Why? Because of the popularity of online retailers who aren’t weighed down by expensive physical sites, who use algorithims and automation to serve millions of people simultaneously, who are augmenting their customer service teams with chatbots as a first layer of response, who are even where they do have a tangible presence. Online retailers didn’t make themselves popular. We did. We reap what we sow.
Are we automating the right roles?
The second issue on the case of man versus machine is that it ignores what we gain from the automation of our lives, and how that can be harnessed to deliver better lives for us all. Often when we talk about the the benefits of automation, the counter argument is that it shuts out the lowest paid workers, causing an increase in unemployment in demographics with the lowest levels of education and the least opportunity to change careers or find alternative work. It’s true that machines have been used in some instances to reduce the number of staff required – think car production lines, self-service check-outs, the introductory bit when you call a contact centre. Yet to apply those examples, which are, at best, examples of automation, rather than artificial intelligence, misses the point. Artifical Intelligence can make decisions faster than any human could hope to. Where it’s applying a series of variables and selecting the optimum outcome, isn’t it a bit of a waste to be applying it only to low-skilled jobs? For all the investment needed, wouldn’t it make more sense to apply it to roles where the ability to make decisions quickly, based on evolving inputs, would be more useful?
Think about all the time organisations spend on the process of decision-making. executivers spend 23 hours a week in meetings of all sorts. That’s a significant amount of time spent talking about creating value, but not actually spent doing so. Don’t believe it will have an impact? A separate study that companies with dysfunctional meeting behaviours (such as going off topic or being negative) were also associated with lower levels of market share, innovation, and employment stability.
Now take that away. Suddenly there’s more time to be active. It might be time to talk to clients, solve problems, build new products, training; whatever it is, it’s an opportunity to create more value.
AI isn’t going to remove all meetings, and it shouldn’t even be deployed for that reason. What it can do is remove the need to make mundane decisions, for instance assigning tasks to team members. Rather than waiting for a team meeting to decide who does what, the team are automatically notified by the AI and they can go off and do their jobs. That drives value to their employer.
But what if your job is to make decisions? Will AI make that role redundant? Well if deployed correctly, yes. And that’s a good thing. Why? Because it means you’ll have more time to focus on bringing the emotion back to business.
Why does that matter? At the heart of every use of computers or machinery, stretching right back to the industrial revolution, was the desire to do things faster. To go beyond what humans, that need sleep and food and toilet breaks, can physically manage, whether that’s weaving, building cars or deciding where to direct your call. One of the side effects has been the removal of the personal touch, the human connection. We complain about faceless corporations, of the tyranny of the contact form over the direct dial. In our desire for speed and convenience, we’ve sacrificed the ability of businesses to be empathetic. It’s the removal of the bank manager knowing his customers, the butcher or pub landlord knowing what the regulars will have.
AI gives organisations the ability to bring that back. Being able to act fast and decisively, but with emotion, with empathy, for a more immersive experience. To consolidate, review and analyse, make a decision and then leave the human to convey that decision is the most appropriate way. That might be a call centre worker empowered, by AI, to make adjustments to a customer’s account then and there; it might be a doctor using AI to formulate a diagnosis and focus on the care and bedside manner the patient receives.
AI across the organisation
That part is just the customer facing element, of course. There’s a whole raft of opportunities in the backend which already embed AI. As organisations strive to seize the opportunities offered by the massive volumes of data being generated, whether it’s in traditional data centres or sat outside it on on sensors and remote devices and mini-datacentres, they also wrestle with the complexities of managing these environments. Wouldn’t an AI that can tell the organisation what’s working and what’s not, what needs fixing and how it’s going to fix it be a significant help? It could be solar panel arrays in the Middle East, wind farms in the North Sea or a platform supporting autonomous vehicles – by deploying AI, organisations truly benefit from harvesting data from all sources while remaining agile without sacrificing accuracy.
It’s not just in industries reliant on large scale machinery, either. Data has long been of huge value to the media industry, where companies like Dentsu Aegis can see the value of the intersection of AI and machine learning with big data and analytics. In the public sector, governments such as the Dubai Municipality are turning to AI, IoT and Big Data to meet the demands of heightened citizen expectation, which means having to know what they want and deliver it before it is asked for.
That means more time for employees to focus on the value creation, less time on the mundane, keeping-the-lights-on work. What that means for their employers very much depends – it might be the potential creation of more opportunities for the organisation to exploit. It might be the chance to provide a greater level of customer experience by combining the pace of AI with the emotion of humans.
Man with machine, not man versus machine
As the world becomes increasingly digital, humans are coming to the limit of our capacity to manage the amount of data that’s being produced. You can see it in the criticisms of social networks not doing more to monitor harmful content, or in a statistic that between 60 to 73% of data collected is never successfully used for any strategic purpose. We need something to help us, to take away what we’re not as good at, and allow us to focus on what we are good at. We’re good at feeling, at emotion, at empathising with one another; in short, at delivering a more immersive level of service. AI is good at processing information and making decisions. Why would we want to compete with something that could take every peer-reviewed article ever published on a medical condition and use it to come up with a diagnosis? We can’t, so we shouldn’t. What we should do is use that ability to augment our basic humanity to create value. That value might be reassuring a patient, it might be fixing a phone contract issue, it might be coming up with a new app. Whatever it is, with AI, we’ll be able to do it more effectively and more efficiently.