Automation and Job Displacement: Myths and Realities
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Welcome!
Let’s start off with a poll, who here has heard anything about widespread job loss as a consequence of AI, or humanity will become lazy as AI is able to automate daily tasks?
Well, it’s not really true, and in this post we will be debunking some common myths about job displacement as a result of AI, and be unveiling some realities.
Introduction:
Picture this: You’re sitting at the breakfast table on a Saturday, sipping your morning coffee, and scrolling through the latest headlines. Suddenly, you come across an article about how AI and automation are going to take over millions of jobs. You feel a little uneasy as you wonder, “Will my job be next?” This scenario is all too familiar in today’s rapidly evolving technological landscape. While the fear of job displacement due to automation is widespread, it’s important to separate fact from fiction and understand the true impact of AI on the workforce.
Understanding Automation and Job Displacement:
Automation:
the use of technology to perform tasks that were previously done by humans, without any human intervention
Automation can range from simple, repetitive tasks such as doing the laundry or the dishes, to more complex processes. AI, a “subset” of automation, involves machines learning from data to make decisions or predictions. While it’s true that automation can replace certain jobs, and AI models have far greater capabilities than our day to day machines, the reality is much more nuanced.
Myth: Automation Will Lead to Mass Unemployment
One of the most common myths is that automation will result in widespread job losses and mass unemployment, amongst other things. While it would be wrong to say that n o jobs will be affected, if anything, history has taught us that technological advancements often create new opportunities. For example, during the First Industrial Revolution where the introduction of machines replaced many factory jobs, there was a need for people to manage those machines and oversee the production process. Another example: the emergence of computers and the internet led to the creation of entirely new industries and job roles that didn’t exist before; typists and switchboard operators saw their roles diminish, but in their place, we saw the emergence of software developers, IT support specialists, web designers, and digital marketers. Entirely new industries, like e-commerce and social media, sprang up, offering roles that were unimaginable in the pre-digital era.
Reality: Job Transformation, Not Elimination
Rather than eliminating jobs, it’s more probable the automation will transform them. Tasks within jobs may change, with machines taking over repetitive or mundane tasks, such as entering data into spreadsheets or responding to emails, allowing a human to focus on more complex and creative aspects of their work. For instance, in manufacturing, robots can handle repetitive assembly line tasks, while workers can oversee quality control and complex problem-solving. And for anyone wondering: “What about complex robots that can act as humans?” - It’s a valid question, but right now I think it’s just to early to tell, but one thing I know for sure, is that it will be a while before any robot can replicate a human’s thought process.
Reality: The Impact on Different Sectors
We’ve talked a lot about automation, and how it will transform jobs, but it’s unfortunately all smiley and cheery. While it is unlikely for AI, in the near future, to replace most STEM, creative, business, and legal professions. AI will most likely possess the capabilities to automate some manual labor jobs. And we’ve talked about the transformation of those jobs, but it’s not all that simple. A lot of the jobs that AI is capable of executing are “low-skill” jobs, in which the worker usually does not have the kind of education you’d see in a software engineer. The transformation of these manual labor jobs, will inevitably require a higher level of education.
Manufacturing: Automation has been prevalent in manufacturing for decades, leading to increased efficiency and productivity. While some jobs have been displaced, new roles in programming, maintenance, and oversight have emerged.
Retail: In retail, automation is being, and will be, used for inventory management, checkout processes, and customer service. This has led to a shift in the types of jobs available, with a growing need for skills in technology and customer relationship management.
Healthcare: AI and automation in healthcare are enhancing diagnostic accuracy, streamlining administrative tasks, and improving patient care. While some administrative roles may be reduced, there is a growing demand for healthcare professionals who can work alongside AI systems. It’s also important to note, let’s say AI can diagnose 99/100 cases accurately, with: a description of symptoms, imaging, and medical history, there has to be doctor’s to corroborate an AIs findings, because even in that 1 case that an AI misdiagnoses, is someone’s life. In short, an AI can only work (currently) well if all the data is present, which is a lot of the time, not the case.
Finance: In the finance sector, AI is used for fraud detection, risk assessment, and customer service. Now, finance professionals need to be comfortable using and managing AI tools.
Analysis: Cutting Costs?
To start, we have to understand why companies want to use AI in manual labor jobs. It’s simple, it’s cheaper, more efficient, makes less mistakes (most cases). But we also have to understand that historically when companies try cutting costs, often times quality drops. This is seen now with produce, many foods grown in labs, or completely by machines, are perceived to be worse for you, albeit not always the case. The point is, people put a price tag on goods that are “organic” or “hand-made.” And AI won’t necessarily change that in every sector.
Preparing for the Future
Before, I wrap this post up, I wanted to offer some suggestions for the future:
Soft Skills: While technical skills are important, soft skills: critical thinking, creativity, and emotional intelligence are becoming increasingly valuable. These skills are less likely to be replicated by machines and are crucial for roles that involve complex problem-solving and human interaction.
Corporate Training Programs: Companies should invest in training programs to help employees adapt to new technologies. This can include workshops, on-the-job training, and partnerships with educational institutions.
Policy Support: Governments and policymakers should support initiatives that promote education and training in emerging fields. This can include funding for vocational training, tax incentives for companies that invest in employee development, and policies that encourage innovation. Moreover, schools should not feel hesitant to adapt their curriculums to make students better suited for the real world. The introduction of computer programming courses has been an addition to most school’s curriculums in recent years.
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