The Good And Bad Of Automation

The opinions on Automation are not quite the same always. Automation is super simple, in theory. The basic premise of automation is to allow machines to follow a set procedure –wait for it — automatically, to save on human capital and reduce human errors. So far so good. The complexity of what can be automated, however, is still up to humans and is limited only by the imagination.

Well, your imagination and your ability and standardize the formatting of your inputs, integrate them into various systems, and create rules.

A good majority of the automated warehousing systems that are found in today’s plants, warehouses and factories are built to cater to an e-commerce supply chain. Amazon, Apple, and IKEA are just a few of the big-name companies that have altered their warehouses with the help of a battery-powered workforce.

There are three types of Automation:

Fixed Automation — Where a machine could do something as simple as repeatedly banging a nail into some wood over and over again to create furniture. It is the simplest form of Automation.

Programmable Automation — This is where a machine is programmed to do a specific task, usually. Still, with this form of automation, simple product changes can be taken into account as the program behind the machine can be changed.

Flexible Automation — This is developing further from Programmable Automation. Flexible Automation has the power to allow machines to manufacture and work with a multitude of parts, allowing the machine to do lots more than a basic program.

With the rise of machine learning and artificial intelligence, quite a few jobs that humans used to do are being taken over. This could include, for example, building a car, where various car parts are assembled into the final car itself. That’s a legitimate fear sometimes, but it’s not new. It is just another step in a process that started long ago. But not to forget the amount of efficiency these automated machines add to their work.

Indeed, automation is eliminating many jobs, but it’s also making the workforce significantly more productive, which means new jobs will be created to complement these automated systems. The modern economy was built on automation, so it’s natural to assume that the future will be defined by automation as well.

The bigger question is whether job automation is good. If we want the economy to grow, math is pretty easy. It’s a two-factor equation: The number of available workers, multiplied by the value of goods and services the average worker produces. Increase one or both of those and presto, GDP will rise. Automation helps raise the second one. But then it gets complicated.

This “average” worker is rare. Almost everyone is somewhere above or below average. Much depends on who produces how much. Talking about change as ‘automation’ focuses on digital or robotic systems replacing human actions. The advantage of this perspective is that it highlights how change affects people.

The downside is that it may not take into account new possibilities for human agency that radical new technological developments create.

‘ The Rise of the Robots, Technology and the Threat of Mass Unemployment ‘ explores how automation could threaten generalised employment and, as a result, social prosperity, as broad-based consumer purchasing power begins to evaporate. Author Martin Ford rehearses how manufacturing employment can decline even as industry booms, for example, China lost 15 per cent of its manufacturing jobs between 1995 and 2002.

Ford raises the spectre of automation affecting high-skill, high-wage jobs too, as machine learning algorithms are applied to tasks ranging from project management to basic journalism. Other narratives envisage broadly beneficial effects on society and the world of work from rapid technological change.

The McKinsey Global Institute anticipates disruption but also, in the long run, benefits — for example, an estimated increase in productivity growth of 0.8 to 1.4 per cent annually through to 2060.

So what kind of jobs are threatened by automation? There is a general agreement about the jobs that are likely to vanish. They all have certain qualities. One is that they are routine and repetitive, involving the repeated performance of standardized tasks.

This includes both simple manual jobs and process-driven desk jobs. Another is that the job or role can be captured in a decision-making tree or flow diagram so that the range of decisions that have to be made is finite — this means an algorithm can do it.

The argument that automation will increase the advantage of capital over labour is simple and intuitive. Owners of robots will benefit more than the workers they replace. This argument has a stronghold as the result is to boost returns to capital further ahead of returns to labour at the level of a whole national economy.

In most industrialised countries, labour’s share of national income has been falling since the 1970s. And the process is also visible in some middle-income countries, with a particularly steep drop in China.

But a strong version of this thesis is scarcely plausible. It implies that the total labour requirement per unit of output is higher in the automated process than in the manual one; if that were the case, it would be hard to see the economic incentive for adopting automation.

A weaker but likelier version concedes that labour per unit of output declines under automation, but total output increases enough t compensate. Even for this weaker prediction, however, there is no guarantee of such a rosy outcome.

Misuse of automation, for lack of a better word, is bad. Automating something doesn’t create a process, and if automation doesn’t fit the context of what you’re working on, it can actually be a detriment. With no process to sum up with Automation, the result could never be efficient.

To put it more elaborately, Automation can’t create a process for you, and if you engage in automation before you’re ready, you’ll waste a lot of time and resources.

The implications of increasing automation and the digital economy for education systems and skills development are profound. An important dimension of the changing context is that AI applications can perform many tasks in today’s labour market up to now performed by professional or white-collar workers — for example, AI programmes are now as good at diagnosing skin cancer as the best human specialists.

Workers throughout the labour market, therefore, may need to upgrade their skills regularly throughout their lifetimes to adapt to changing requirements. At the same time as the requirements of education systems change, the delivery of education will be transformed — with complex implications.

The evidence, however, suggests that automation will, in time, erode the engine of ‘convergence’ between poorer and richer countries. Higher productivity is positive because it lets everyone get more value for their money.

We can buy our stuff at lower prices when producing it costs less. But it’s a problem when productivity gains are concentrated among relatively few workers. Employers naturally place a higher value on them and a lower value on everyone else.

So a question that might come to your mind is — “Why can’t a man and machine work together?” Well, the answer is, We don’t know. The reason for this simply is, the technology hasn’t touched enough industries yet to broadly answer this question.

Sure, bits of work in the car manufacturing industry have been taken over, and the human presence in making the car is still there. But other people have completely lost their jobs due to the presence of Flexible Automation so at this point, it’s hard to say.

Robots certainly provide some advantages over humans. For one, they’re quicker and more precise, compromising a high likelihood of human error in traditional work. Companies strive for consistent, quality service in the age of customer experience and on-demand services, so there’s certainly something to be said about automating some facets of a workplace.

But humans still have the upper hand when it comes to empathy and creativity which will help keep certain jobs safe. In the end, the use of automation can be restricted but not avoided.

It has its pros and cons. But the thing that separates these automated machines from us humans is a term called MORALITY. It is in this work ethic that humans tend to surpass machines by a larger margin.

It all depends on a balance. The key term here is ‘ BALANCE ‘. And probably, in this case, the thing to be adjusted is the fulcrum.