While humans may be the most intellectual creations and sit atop the “food chain,” artificial intelligence (AI) is a branch of computer science that can simulate human intelligence in many cases. AI is implemented via machine learning (ML) and performs tasks traditionally executed by humans.
Like it or not, AI and ML technologies are here to stay and can help humans in many ways. The numbers show investments in this technology will continue to grow over the coming few decades. Fortune Business Insights pegged the global 2021 market value for AI at more than $328 billion, with another $50 billion forecasted for growth in 2022 and $1.3 trillion by 2029.
Adopting AI and ML enables people to focus on more complex tasks, since no matter how “smart” machines become by analyzing and copying routines, they cannot think for themselves. AI employs special algorithms (machine learning and deep learning) that can detect patterns and devise a process to make decisions. These algorithms allow machines to learn from the data. This means when humans cannot easily program or perform those labor-intensive tasks, machines use data gathered by AI to learn how to execute those tasks.
The expanding use of AI and ML will create opportunities for the displaced labor force in industries where routine tasks can be supplanted by AI and ML. After all, someone needs to make or learn how to program all those robots or to create algorithms. Embracing these technologies can lead to greater efficiencies, new employment opportunities, and a more competitive position for organizations. In this context, AI and ML are not to be feared.
The Case for AI and ML
Employing AI and ML for rote, routine tasks will enable humans to focus on other more intuitive tasks where “thinking” is required and cannot easily be replicated digitally. The data loaded for AI drives the tasks where ML is used. Electric car manufacturer Tesla is an adopter of AI technology that enhances the driving experience and creature comforts. For example, after a few trips the car can recognize that the Tesla owner is always going to the same place every morning at 8:00 a.m., directing the onboard computer to load that map automatically. Remember though, AI systems cannot think on their own or consider human emotion factors in decision-making: They rely on data that can easily be broken down and interpreted.
In addition, social media platforms employ AI to recognize patterns and glean data from user searches, before offering other similar online opportunities via the click of a mouse. AI can work in any industry that is data-driven and where there is a high degree of predictability. Netflix uses AI to suggest series or movies based on other programs the viewer accessed, using customer information retrieved from the cloud, where that large volume of data is stored.
AI and Its Impact on the Workforce
AI can lead to more productivity as well, like reading aloud e-mails during a morning commute, so employees don’t have to spend time at the office on that same task. Instead, they arrive more prepared with priorities already forming based on hearing those e-mails. So, will AI and ML eliminate jobs, or simply move people from one field to others where the human ability to think is still highly valued? Some have lost or will lose their jobs as automated technology becomes more prevalent, with the current shortage of workers in many industries fueling that growth. Even restaurants are experimenting with robot servers. Of course, someone will have to build and program these data-driven machines, which create a new and different opportunity for employment and positions, calling for enhanced training and a commensurate higher pay scale. Any system that employs AI and ML must also have scalability – the ability to automatically ramp up as the traffic increases.
Misconceptions About AI
- It’s too technical. AI is applicable for the “common folks,” and in fact analyticsinsight.net states that AI processes can be created with just a few lines of code. AI is found in business sectors including smart cars, social media, virtual assistants (Siri, Alexa), financial industries, and customer service, employed for common and repetitive tasks. AI was even employed to sift through data obtained by the Kepler telescope to identify a distant solar system.
- AI works just like the human brain. AI does not understand or comprehend its surroundings or learn from its environment in the same way humans do but depends in large part on the quality of data transmitted to it. AI “can’t think outside the box and their code,” reports Synder, which works with some of the biggest e-commerce companies in the world, and while human beings can build those important business relationships, “AI will never be able to do it.”
- AI and ML are made only for more common and repetitive tasks, like those found in manufacturing and routine software applications. In fact, AI and ML can be used in a wide swath of industries, for day-to-day activities. Statista.com reports that in 2020 private investments in AI in the United States totaled almost $24 billion, more than double – surprise – what China spent on the technology in the same year.
- AI will take jobs away. Short-term job loss in certain industries due to the use of AI and ML can lead to other higher-skilled opportunities. Many of those will require more complex problem-solving skills, critical thinking, and creativity. Where implemented, AI can improve how people and businesses perform their jobs.
- AI and ML are too costly. In the long term, using AI and ML can be more cost-effective, because productivity improves, enabling businesses to make better decisions and save on operating costs.
No Reason to Fear the Future
The potential of AI offers many benefits. It can be used to simplify and speed up security procedures at airports, such as scanning a passport that automatically links to other personal data to clear travelers quickly. In addition, technical and teaching job opportunities will be created due to the increased use of AI and ML. Comprehensive training will be needed for valuable employees so they can take the next steps in their careers. Schools and colleges will need new academic tracks to prepare the next generation for the expansion of AI and ML.
At this point, the implementation of AI and ML may have reached only about 20% of its potential, which means there are ample opportunities for growth. Making sure the data used in AI and ML applications are “clean,” and can be scaled automatically based on demand, and that all applications meet security requirements will ensure future growth as competitive tools for companies to employ with confidence.
The forecast for AI and ML looks strong, with the bulk of manual manufacturing jobs expected to be performed by robots at some point in the not-so-distant future. Forbes cited a report last year that shows the use of AI in many business sectors had grown by almost 300% over a four-year period. AI is emerging across nearly every industry. As builtin.com puts it, AI “is already the main driver of emerging technologies like big data, robotics and IoT [Internet of Things], and it will continue to act as a technological innovator for the foreseeable future.” Indeed, AI should be looked at as a friend – not a foe to mankind – as the technology is more widely adopted and reimagines what workplaces of the future will look like.