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AI / Big Data

Automation is coming! Are you ready for it?

Like it or not automation is coming 

In the past decade, robots have made drastic improvements in terms of the tasks they can perform. From military grade and industrial robots to household ones, there is no doubt that many of our daily tasks will eventually be performed by them.

Although Tesla had to pull back on some of its automation efforts and Amazon has also struggled to fully automate its warehouses, manufacturing centres and warehouses will eventually become fully automated.  In China, a restaurant has opened in Guangdong Province that is fully automated, using robots to manage everything from taking orders to preparing and serving the food.

Robots are not only replacing manual labour. Technologies like Robotic Process Automation are automating repetitive rules based back office processes such as inputting data, processing transactions, triggering responses, and communicating with other digital systems.

Every role will be impacted in some way by automation. Some roles will be completely eliminated and new ones will be created. In the roles that survive, some skills will become redundant and new ones required. As a result, it is important to keep an eye on the changes happening in the automation space because technology is changing faster than ever. Ignoring, silently observing, or trying to oppose new technology is akin to swimming against the tide. It is more fruitful to identify the changes, understand their implications, actively embrace the direction of change, and adapt by investing in yourself to build the skills that will allow you to excel.

How do you prepare for the future? 

Whether it be disruptions from technology, political instability, economic downturns, or social unrest, it is difficult to prepare for the future because it is difficult to predict.  The current COVID crisis is a good example of an unexpected disruption that has destroyed many jobs globally. Organizations looking to cut costs are also exploring ways of automating their work, which will cause further layoffs.

Having a simple framework to determine what kind of work is easy to automate and what kind of work is difficult to automate can really help in understanding the kind of skills that will put you in good stead for the future.

We can think of work as consisting of two main parameters: tasks to be done and decisions to be made. The more structured the task, the easier it is to learn, the greater the supply of potential employees, and the lesser the pay.

Your level of performance at work will also depend on the context that you are operating in, which we might classify into 4 quadrants:

  1. Simple
  2. Complicated
  3. Complex, and
  4. Chaotic

Figure: Cynefin framework developed by David J. Snowden

Simple contexts are characterized by stability, clear cause-and-effect relationships, a defined chain of command, and structured tasks that can be easily quantified and monitored. Disagreement about what needs to be done is rare.

Simple environments are a domain in which automation, adherence to rules, and best practices tend to work well. Robots should be able to perform these kinds of tasks efficiently at scale with few mistakes. Cashiers, waiters, and data entry technicians operate in this context, and this kind of work is already being automated through self-checkout counters, automatic vending machines, and RPA Bots.

Complicated contexts may contain multiple right answers. There is usually a clear relationship between cause and effect, but it’s difficult to quickly understand the nuances of the various decisions that need to be made. Although an answer exists, it may lie buried. It requires an expert to help identify the problem and propose a solution. Complicated environments are where management consultants thrive. Lawyers, accountants, and investment advisors also operate in this context.

Machine learning and natural language processing (NLP) are beginning to disrupt work in complicated environments. For example, there are mobile apps that can recommend investments taking into account the user’s risk profile and preferences. There are also apps that use machine learning and NLP to skim through legal contracts and identify the most important clauses for the user to focus on. Even though the consultant role has not been completely eliminated, a lot of prediction, data crunching and judgement is now done by algorithms.

Complex contexts are ambiguous, poorly defined, and characterized by emergence. They are hard to predict due to constant flux and dynamic shifting relationships. Complex environments are best thought of as probabilistic, which means they cannot be solved. Answers don’t exist. The best one can hope for in a complex situation is to understand some of the dynamics, monitor the situation closely, and adjust course as new information surfaces. This is the domain of anything that is highly interactive with feedback loops. CEOs, governments, top economists, reserve bank leaders, and chief healthcare officers operate in this context.

Even though machine learning, and data analytics-based models can provide insights, people in complex environments require high level critical thinking skills to look beyond the obvious, openness to new ideas, and strong decision making ability to select a course of action after considering the pros and cons. Since human beings are somewhat unpredictable and exhibit a wide range of behaviours and emotions, managing them also requires a high EQ. Based on the current level of artificial intelligence, these skills will be difficult to replace, and so they will be higher in demand even in the era of automation.

In chaotic contexts, searching for right answers is futile. Relationships between cause and effect are shifting constantly, with no identifiable patterns, thereby making rigorous analysis useless. Snowden and Boone suggest these environments are rare, usually temporary, and can be effectively approached by trying to establish order and regain stability however possible—even if only in certain subdomains. Entrepreneurs starting a new company, and national leaders during a crisis like a war or pandemic operate in this context.

There is no level of artificial intelligence that can operate in chaotic environments. The ability to navigate through uncertainty and make good decisions based on very little or no data are skills that are irreplaceable. There are few individuals in the world that can operate effectively in this context. Hence, they are famous world leaders, sportsmen, and renowned entrepreneurs.

Applying the four quadrant framework

Look at the context you operate in. Your role may not fit perfectly within any one of the four quadrants. However, if you find that most of your work can be described as ‘simple’, then you have reason to worry. Gaining new skills will help you complement the automation technology, and transition to roles that require more critical thinking, judgement-based decision making, and emotional intelligence.

For those of you who operate in a complicated context, leveraging automation can actually help you focus on more important tasks like relationship building, making more informed decisions, and focusing on more complex parts of the task. It is important not to blindly follow the recommendations made by the automation tools. Common sense has to be applied at all times.

People who work mostly in complex and chaotic contexts are at the least risk of being replaced by automation. Also, since these skills are hard to learn and typically in short supply, people working in these contexts are normally paid well.

When assessing the likelihood of your work being replaced by automation, it is important to step back and look at the work of your entire team. If you are managing a team of people who perform repetitive tasks, you are still in trouble. There are situations when an entire function may be laid off as it becomes irrelevant to the organization. If bots bring down the headcount from 100 to 5, then the need for a hierarchical structure of managers and VPs may become irrelevant as well.

Final thoughts

Creativity, critical thinking, the ability to make judgment-based decisions, emotional intelligence, and the ability to navigate uncertainty are likely to be the skills of the future.

Mudassar Shaikh is an engineer at heart, management consultant by profession, entrepreneur by spirit, and student by essence. He is passionate about enabling organizations to develop new technologies and make them accessible to the masses, positively impacting the life of many and pushing the human race forward.

Images: Pixabay, Canada School of Public Service

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