For the last several years, workers around the country and around the globe have been uniting behind the same rallying cry: “the robots are taking our jobs!” Others argue that implementing new and more “intelligent” technology into the workplace will allow businesses to scale in new ways, providing new jobs to human workers.
These ideas hint at the two main views that have emerged about the role new technology will play in the development of the workplace: replacement versus augmentation. So what are the main concerns surrounding both ideas? How can businesses adapt to these new technologies? And what does the future of automation and augmentation look like in 2022 and beyond?
Common Automation Concerns
Many workers’ primary concern is that they will lose their jobs in favor of robots and automated programs that do their jobs in less time with less error, and all without a weekly paycheck and employee benefits. These fears are not wholly unwarranted. Automated technology is replacing some jobs. In fact, one study predicts that by 2030, 1 in every 3 Americans will cede their job or tasks to robots or AI. Jobs in the transportation, food service, storage, and manufacturing/construction industries are at the highest risk because they are repetitive and can be easily automated.
But there is a bright spot amidst what appears to be a gloomy outlook. One is that the transition to automation is still moving fairly slowly. This gives workers time to reskill to meet the new needs of the changing workplace. But more on that later. First, let’s talk about automation and AI.
Types of Automation
Before we can really dive into this topic and address workers’ concerns, we have to understand the different kinds of automation and AI that currently exist:
- Robotic Process Automation – This automates repetitive, rule-based processes. Such technology cannot learn, adapt, or make decisions; it simply makes mundane tasks more efficient. This could look like a robot constructing cars on an assembly line.
- Machine Learning – A computer uses large volumes of data to understand and predict a course of action, subsequently improving its ability to predict over time. The chatbots used by financial institutions, for instance, are an excellent example of this.
- Cognitive Augmentation – This is the closest technology we have to true artificial intelligence. IBM’s Watson computer is an apt example. It takes unstructured data and provides answers to complex questions. One practical application is the Memorial Sloan Kettering Cancer Center in New York using Watson’s software system for utilization management decisions in lung cancer patients.
We mustn’t view these categories as levels that automation will progress through. Instead, each one serves a unique purpose and can complete different tasks. Robotics automation removes the burden of repetitive tasks, while machine learning can solve certain low-level questions and continue learning so that humans can spend time solving more complex problems. And cognitive augmentation can synthesize and analyze data efficiently to provide solutions to problems more quickly.
How to Work Together with Technology
Even though the thought of robots and AI taking over some human workers’ tasks can be scary, there is also a lot of growth potential. And this is where the idea of augmentation comes in. To augment simply means to make something better—enhanced or more efficient—by adding to it. So, in this case, the use of technology can augment, or enhance, our work.
When we augment human and technological resources, jobs aren’t necessarily disappearing; they’re just changing. Indeed, for a job to be completely automated and to entirely eliminate the human component, the machine would have to do the work just as well (i.e., drastically reduced errors, etc.), or more likely better than the humans. And it must do this all at a lower cost.
But technology like this is still few and far between. For example, many large-scale businesses, like financial institutions or insurance companies, have implemented chatbots or automated customer service lines. And I don’t know about you, but when I’m on a customer service line, I usually just want to speak to another human being. This type of technology can be beneficial for assisting with basic issues. It can help guide customers to the right department, but it is not sophisticated enough to handle more thorny problems.
By removing the burden of repetitive or low-level problem-solving tasks, AI and automated technologies free up workers to contribute to value-adding tasks. So when a worker performs in tandem with automated technology, their job is augmented so that they can accomplish even more work in less time with fewer mistakes. Deloitte calls this worker plus automated technology a “superjob.”
The next step in augmentation then is to extend the work of humans and machines together to the group. We call this a “superteam.”
Deloitte was the first to coin the term “superteam.” It encompasses the integration of AI into human work teams.
Work teams have become the standard unit of a successfully functioning organization. These businesses are group-centric and network-based. AI then simply augments the team. The human team and AI working together actually increases the business’s overall work and thus creates value. So superjobs are augmented, but superteams are a collaborative extension of the superjob.
But still, according to Deloitte, superteams are not yet a workplace standard. Why not? Well, they say, “this may be because many organizations still tend to view technology as a tool and enabler, rather than as a team member and collaborator.”
Businesses can use augmented teams and their machine elements to complete the same tasks, but perhaps a more effective approach is to allow these superteams to reimagine the nature of work and the workplace, rather than merely doing the same work in the same way as before.
A Reimagined Workplace
Of course, reimagining the workplace is no small feat. Deloitte offers some ideas on what this might take. There are steps that everyone, individual employees and leaders alike, can take. But from a company-wide perspective, here are three ways you can start to prepare for new technology:
- Create a long-term integration plan. Instead of utilizing automation and AI for quick fixes to immediate problems, consider the use of technology over the long run. How will the machines and technology you implement today benefit you five and ten years down the road?
- Help employees to transition. Likely, you will still need many of your employees to complete the work of the business. Being transparent about the change and how your employees will be vital to a successful transition helps set them up for success.
- Invest in your workers. Since many of your employees’ jobs will be changing, they will either need to reskill, upskill, or do both. Businesses that provide on-the-job training communicate to employees their value to the company.
- Use AI to reimagine, not just as an enabler. Sometimes, implementing AI into existing processes—or using it to enable current practices—isn’t enough. Building new processes based on new technology may be the best long-term growth strategy.
The Future of Artificial Intelligence
Humans have not yet created machines that can imitate human-level intelligence. Current AI tech simply cannot operate autonomously at an intense level of decision-making like the human brain. But some scientists and futurologists don’t think that artificial general intelligence (AGI) is too far away. In fact, according to DeepMind lead researcher Dr. Nando De Freitas, artificial general intelligence at this point is more a matter of scaling than anything else.
Scientists have differing opinions on what it would take to achieve AGI. Notably, scientist, author, and founder and CEO of Robust.AI, Marcus Gary, staunchly disagrees with de Freitas. But we’ll cover AI more in-depth in our next blog, so stay tuned!
Suffice to say, the use of automation and augmentation is critical today and will be critical tomorrow. Businesses who want to be successful must get on board the AI train and learn how to augment their workforces with new technology.
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