Remember in 2017, Elon Musk
"People should not underestimate the power of the computer,'' Musk
AI is really good at many "human" tasks — diagnosing diseases, translating languages, and serving customers. But as the application of AI expands, more and more people are
Engineers and scientists have already done a lot of work to teach technologies to mimic the human mind's processes and have made significant progress along the way. AI has already surpassed human intelligence in some tasks, from games to problem-solving. Here are some examples of how AI has outperformed us in our inventions.
The Deep Blue Computer has Been a Better Chess Player Since 1997
The most famous battle between Deep Blue and the world chess champion Garry Kasparov occurred in 1997, although some experts believe the computer had an unfair advantage. And while the computer system used to defeat Kasparov is not technically "smart," we cannot deny that it has surpassed the human ability to analyze chess moves and choose the right one.
Data drives much of what we do, from analyzing election results to developing healthcare solutions. Reportedly, people who build models that explain and predict patterns in the ocean of "big data" are in short supply. But that may not matter due to the development of computer software that proves to be better than humans. MIT's data science machine can automatically generate predictive data models from raw datasets in as little as 2-12 hours. It can take several months for a team of data scientists to complete the same task.
Visual recognition is used in applications as diverse as facial recognition in photo storage applications and the analysis of shared social media images to improve marketing. Any object recognition task is likely to be completed faster and more efficiently by a robot than by a human.
Robots are undeniably better at repetitive tasks than humans. Amazon was the first major logistics retailer to adopt robotics and now owns 30,000 so-called Amazon robots, which it uses in its US warehouses. And all this happens because:
Humans make mistakes, but not computers. They receive instructions and execute them exactly as written in the code. It is extremely important for such tasks as data entry, where a typo can lead to chaos.
Therefore, AI can perfectly perform work that requires copying, pasting, transcribing, and typing.
Lack of rest, boredom from repetitive tasks, even "hanging out" are purely human problems. For example, staying up all night or being stressed affects your performance the next day.
On the contrary, computers never need to sleep, rest, or have fun. No matter what, their operational capabilities are the same (unless we turn the power off). This is what the machines were made for.
Jobs such as mining, factory work, and machine assembly expose workers to danger. Whether it's extreme temperatures at work, hazardous fumes, or falling objects, there will always be circumstances and situations in which people can be seriously injured or killed.
People can use AI in manufacturing to improve the efficiency of processes and protect people from industrial harm. Opportunities for using AI and machine learning in manufacturing include logistics optimization, product development, predictive maintenance, and, of course, robotics.
While machines can also be injured or crushed while performing hazardous work, they are not as fragile and are built to withstand enormous pressure, heat, airborne toxins, and other threats.
While the initial costs of building and training an AI machine are high, the total operating price is much lower than paying a human for the same job.
Only electricity and periodic maintenance are required to use the machine. Recruiting a person for a job requires resources to find and train them, not to mention paying an annual salary and benefits.
Former Google CEO Eric Schmidt believes we’re in “the golden age of investing in AI.” In the third quarter of
Logistics, packaging, and materials ($31 billion);
AI analytics ($70 billion);
Autonomous cars ($87 billion);
Robo advisor ($255 billion).
This capital influx is a sign that investors believe in the potential of AI, and they bet that it will eventually automate many jobs instead of creating value with machines. If you don't use AI, you are at a disadvantage.
To date, AI can be divided into three categories. More routine tasks are already being delegated to weak AI, also known as narrow AI. It is trained and focused solely on a specific task. For example, a weak AI is suitable for playing chess, but it cannot transfer this intelligence to another domain.
General AI is a hypothetical form of AI. A machine would have an intelligence equal to that of a human; it would have a self-aware mind capable of learning, solving problems, and planning for the future. Super AI is predicted to surpass human abilities, becoming smarter than humans in several areas.
Super AI is still a completely theoretical concept with no practical use cases. But if
Introducing AI and advanced technologies suggest that, in the long term, machines will become even more refined and processes even smarter. Therefore, experts agree that AI will fully automate many professions in 5-10 years. However, the problem is that this can lead to a reduction in the number of jobs.
This is already happening: technology is replacing humans in the workplace in manufacturing, service delivery, recruitment, and the financial industry, causing human workers to move into low-wage jobs or become unemployed.
According to the World Economic Forum report, AI will replace 85 million jobs globally by
The fact that AI automates jobs in every industry is no longer news - technology has been replacing humans in the workplace for many years now. So, what jobs are affected by AI?
Computer-controlled assembly and industrial robots can assemble automobiles and other products and have been in use since the late 1950s. Today, almost all large manufacturing plants use robots to produce millions of different products efficiently and inexpensively.
We have all experienced getting automatic phone calls. As voice recognition and speech synthesis become more progressive, it's becoming easier for companies to implement these systems, and it's getting harder for people to know if they're talking to a real person.
Today, there are self-service checkouts in most grocery stores. Although one person still supervises these computers, this person does work that previously required several people.
In the past, banks used to have many employees. Today, a part of the staff has been replaced by ATMs that allow you to deposit and withdraw money from the bank without actually talking to a live employee.
Financial institutions will soon become even more automated as more people switch to digital currencies like bitcoin and conduct their financial transactions using their smartphones.
Law firms are replacing paralegals and other staff with e-discovery lawyers and research robots. These robots can browse through millions of documents and find relevant facts, phone numbers, email addresses, and additional information based on keywords.
For example, medical imaging startup
The creation of hypotheses has long been a purely human domain. However, now scientists use machine learning to get original ideas.
For example, a neural network has determined that the density of the structure of the mammary glands contributes to cancer recurrence. While it couldn't explain why, it helped Case Western Reserve University biomedical engineering professor
Customer service executives do not demand a high level of social or emotional intelligence. Therefore, many companies now rely on AI to answer frequently asked questions and customer support questions. According to the World Intelligence Congress, by
This sector is probably the biggest area where people fear AI will take over jobs. As soon as the manufacturing process for most goods produced today gets mechanized, the operational aspect will also be handled by AI. Robots can work alongside scientists, even in pharmaceutical labs, providing a safer environment. Scientists will no longer put their lives at risk.
By the way,
These are not all the industries in which AI is replacing jobs; many more are. And all these "smart" systems in communities, vehicles, buildings, utilities, farms, and business processes offer important benefits that we cannot underestimate. They save time, money, and lives and give people the opportunity to focus on more interesting and important tasks.
Despite all these incredible possibilities, artificial intelligence is still at its early stage of development. Everything we see today is only a harbinger of a much smarter and more intelligent version that is yet to come. And that is why we can be sure that today's AI will still not be able to replace humans in many areas.
Although machines can mimic human behavior to some extent, their knowledge of rational decision-making, like ours, may not be sufficient. Machines with artificial intelligence make decisions based on events and their connection. However, they lack common sense, free will, opinion, and creativity, so they can only produce results for their programmed purpose. AI systems are clueless about understanding "cause" and "effect." Meanwhile, real-world scenarios require a holistic human approach.
Therefore, many professions will require unique human qualities called "soft skills" — empathy, communication, strategic thinking, questions, creativity, imagination, vision, and dreams. These soft skills will always be the hard currency in the labor market, so many professions will not disappear even after AI replaces jobs.
We are talking about those that require creation, conceptualization, integrated management of strategic planning, precise hand-eye coordination, working with "unknown and unstructured spaces," and feeling or interacting "with empathy and compassion." And until artificial intelligence has evolved to the stage of developing machines that can engage, interact, think, adapt, and respond the same way as people, such intelligent machines cannot completely replace human resources.
While AI has already taken on many labor-intensive tasks, it cannot reproduce human emotions and behaviors that are so important in certain industries and fields. Therefore, some professions will be in demand even after the widespread introduction of automation.
This area will grow by 9% by
The tasks of marketing managers include interpreting data, tracking trends, monitoring campaigns, and creating content. They must also quickly adapt and respond to changes and feedback from the rest of the company and customers, which even the most advanced AI is not capable of yet.
When OpenAI taught the GPT-3 AI to answer questions using Bing search, the resulting answers turned out to be better quality than those of humans.
Also, with the help of machine learning, AI has mastered one of the most unusual tasks — the restoration of speech from a video. Engineers trained the neural network on over 2,400 hours of various speeches in different languages, and as a result, a model was developed that
However, writers must conceive and create original written materials "for people." And while AI does a pretty good job of creating content for automated social media posts, still books, movies, and plays are likely to be written by humans for the foreseeable future.
One promising AI idea has already turned into a business:
But those AIs designed to help developers are still making mistakes and do not fully understand the code, so everything will remain the same in the major field of creating software. However, with the help of AI, highly skilled developers can get rid of routine work and focus on more creative processes. And novice or low-skilled developers can use AI programs, particularly
Due to AI, people have discovered new ways to interact with drawings, videos, and photos. For example, AI is great at manipulating and editing images based on users' thumbnails.
And Meta AI rolled out a cool demo that can revive and animate children's drawing — from a straw man to incomprehensible mojibake.
However, this is not enough to completely entrust this task to AI, and in design, it can only be assistive technology.
Since planners must coordinate and negotiate with vendors, contractors, and freelancers to achieve alignment, these organizational and HR skills will make this another almost impossible task to automate.
While automated proofreading technologies such as
Don't forget that AI is an invention of the human mind. Full automation of various tasks today is possible due to the human imagination. And we can be sure that AI systems have not yet reached the technical maturity to take over humanity at the moment. So put aside the fears that AI will take over jobs and harness the full potential of this ambitious and promising technology.