For a long time, it was thought that artificial intelligence (AI) was a myth, a product of science fiction that would never come true. The idea was that machines could never have characteristics resembling intelligence, a uniquely human quality. It was understood as two distinct things: the human brain – analytical, creative, and emotional and the equipment developed by it. The first industrial revolutions created equipment that replaced manual labor, performing with greater efficiency and lower cost of the work of many men.
Today, a lot has changed and it is already known that the potential of machines is much greater. So much so that there are arguments in favor of artificial intelligence.
In several cases, it is already being employed in tasks once seen as “intellectual.”
Does this mean that these devices have an intellect? Not exactly, because, although the comparison is valid, the “intelligence” of machines is quite different from ours. Be that as it may, the important thing is that nowadays everyone already recognizes that artificial intelligence is a reality.
What must be done is to broaden the understanding of its mechanisms and the understanding of the possibilities it provides. It is a challenge, especially for entrepreneurs and managers, who are always in search of greater productivity in all sectors.
In this article, we will talk about the concept explain how it works, and present the advantages and disadvantages of artificial intelligence.
You will also know examples and know ways and models to make it an opportunity.
Follow the reading to understand the concept and check out examples of artificial intelligence in everyday life!
What Is Artificial Intelligence?
Artificial intelligence emulates human thinking on devices, Artificial intelligence is the ability of electronic devices to function in a way that resembles human thought. This entails noticing variables, making decisions, and solving problems.
In short, operate in a logic that refers to reasoning. “Artificial,” according to the Michaelis dictionary, is something that was “produced by man’s art or industry and not by natural causes.” Intelligence is the “faculty of understanding, thinking, reasoning, and interpreting.” Or the “set of mental functions that facilitate the understanding of things and facts.”
In the same dictionary, there are two Psychology definitions for the word “intelligence”:
- Ability to harness the effectiveness of a situation and use it in the practice of another activity
- Ability to solve new situations quickly and successfully, adapting to them through the knowledge acquired.
Even these last two definitions make sense when we talk about artificial intelligence, with the strand called machine learning.
Finally, AI is developed so that man-made devices can perform certain functions without human interference.
And what are those functions?
With each passing day, the answer to that question is greater.
We will try to answer later by giving examples of applications of artificial intelligence.
How Does Artificial Intelligence Work?
- You may have heard many times about hardware and software, right?
- But do you know what those terms mean?
- While hardware is the physical part of a machine, software is the logical part—or the “brain.”
- Where would you say, therefore, that artificial intelligence is?
In software, of course.
So if you want to know how a car can ride alone, for example, forget about the hardware, because the secret is in the program that guides its movements. Therefore, it is not possible to explain how artificial intelligence works without talking about computer science. This science studies techniques and methods of data processing, and the development of algorithms is a central issue in it.
Algorithms are a sequence of instructions that guide the operation of a piece of software – which, in turn, can result in the movements of a piece of hardware and artificial intelligence, Where does it come into that?
In its origin, the algorithm is very simple, as in a cake recipe. Today, the logic of algorithms is used to create extremely complex rules, so they can solve problems on their own, even when there are two or more paths to follow in a task.
For this, it is necessary to combine algorithms with data.
Going back to the cake example, a person removes it from the oven when he observes that it is ready or after doing the fork test. A cake-making machine with artificial intelligence could have some kind of sensor that identifies the texture of the cake.
The algorithm would work with two hypotheses and an answer for each:
- If the texture is still not ideal, the cake follows in the oven
- When the cake is ready, it is removed and the oven turned off.
Of course, this is a very primary example in the face of all possibilities.
There are machines that perform tasks that are often more complex, solving problems with thousands of variables instead of just one.
But they will always work this way: from previous programming, a code that considers these variables processes the data and determines what to do in each situation.
What Is The Goal Of Artificial Intelligence?
Since AI is a type of technology that enables machines and electronic devices to emulate human thought, the question remains: Where do we want to go with this?
One of the possible clues to finding this answer is in an Accenture article on Artificial Intelligence. He brings us an interesting and revealing definition of what we can expect: “The definition of artificial intelligence that everyone does is different perhaps because AI is not just one thing.”
That is, to point out a single goal would be to reduce its size and role too much. Another perspective that suggests the myriad purposes of AI is given by researcher John McCarthy of Stanford’s Computer Science department. According to him, “artificial intelligence is related to the use of computers to understand human intelligence, not limited to biologically observable methods.”
Therefore, there is not only one goal in developing AI but a sum of purposes that led humans to emulate their own intelligence in computers. This helps us understand the importance of artificial intelligence, which we will talk about later when addressing the technology involved.
The History Of Artificial Intelligence In The World
In the 20th century, Alan Turing conducted experiments that revolutionized the world. During World War II, in 1940, the British mathematician developed a machine that allowed the breaking of secret Nazi codes, generated by another machine, patented by Arthur Scherbius and known as Enigma.
Ten years later, he introduced the world to the Turing Test, also known as the Imitation Game, created to verify that the computer is capable of imitating human thought. His great work was the Turing Machine, which stored information on a tape, according to a series of rules – the first algorithms.
For these and others, Turing is considered the father of computing From there, the development of AI went on to advance along with the evolution of computers. During the 1950s and 1960s, researchers began developing computer programs that aimed to mimic human thought, with approaches such as symbolic logic. After a few years of stagnation, known as “the winter of AI”, artificial intelligence regained momentum from the 1980s, with the emergence of new algorithms and approaches. It was around this time, for example, that the field of AI known as “deep learning” emerged.
In the 1990s, the internet and increased computational processing power further drove the growth of AI. The systems began to be used in various practical applications such as speech recognition, machine translation, and medical diagnosis.
Over the past decade, we’ve seen notable advances in a number of areas, such as autonomous vehicles, facial recognition, object detection in images, content recommendation, and more.
Different Types Of Technologies And Approaches To Artificial Intelligence
Each researcher has their own way of understanding the challenges and opportunities of the area.
Generally, they fall into two distinct approaches: symbolic AI and connectionist AI. In symbolic artificial intelligence, mechanisms effect transformations using symbols, letters, numbers, or words. They simulate, therefore, the logical reasoning behind the languages with which human beings communicate with each other.
The connectionist AI approach is inspired by the functioning of our neurons, thus simulating the mechanisms of the human brain. An example of technology from the connectionist approach is deep learning, the ability of a machine to acquire deep learning by mimicking the brain’s neural network.
Some even talk about a third approach, evolutionary AI, which uses algorithms inspired by natural evolution. That is the simulation of concepts such as environment, phenotype, genotype, perpetuation, selection and death in artificial environments.
What Is A Neural Network?
Starting from the premise that the functioning of artificial intelligence is similar to our own reasoning, the concept of neural networks emerged. It is a computational model inspired by the functioning of the human brain, capable of processing information through an interconnected set of processing units called “artificial neurons” or “nodes.”
These neurons are organized in layers, and each neuron is connected to other neurons in subsequent layers through so-called weighted connections. Each connection between neurons has an associated weight, which determines the strength of the influence that one neuron exerts on the other.
These weights are adjusted during neural network training, where it learns to map a set of inputs to a set of desired outputs. Processing in a neural network occurs through the propagation of the input signals through the network, from layer to layer, until the signals reach the output layer.
As the signals propagate, they are weighted by the weights of the connections and undergo activation functions of the neurons, which determine whether the neuron should be activated or not. A neural network’s ability to learn and adapt from data is known as “machine learning” or “neural network learning.” During training, the weights of the connections are adjusted based on optimization algorithms, which seek to minimize the difference between the outputs produced by the network and the desired outputs.
With the advancement of technology and the increase in computational power, neural networks have proven to be extremely effective in various applications, boosting the field of artificial intelligence and the development of innovative solutions in various areas.
Types Of Artificial Intelligence
As the concept of artificial intelligence became more widespread, new scholars began to dwell on it.
Thus, different perspectives have also emerged.
One of these contributions was the differentiation between two types of AI, the strong and the weak, which we detail below:
- Strong Artificial Intelligence
Also known as self-aware, Strong Artificial Intelligence is one that emulates human reasoning with such perfection that it is able to solve situations faster and more assertively than a person.
No wonder, it is a very controversial topic, because many understand that it is a technology that comes to be an alternative to the more qualified workforce of companies.
Other ethical dilemmas surround this subject, reminiscent of fictional films such as “I, Robot.”
Examples of Strong Artificial Intelligence are those that use machine learning and deep learning techniques.
- Weak Artificial Intelligence
Weak Artificial Intelligence, as the name suggests, does not have such great power to cognitively mimic human reasoning.
In practice, it can collaborate in the processing of a large volume of information and even create reports, but without the self-awareness of the previous type. The big issue is that a weak AI can develop and reach the strong stage, even though most of the advances are in the first classification.
Within the field of Weak Artificial Intelligence is Natural Language Processing.
In this case, the machines use software and algorithms created for specific purposes, such as simulating a human conversation. Currently, much of the advances considered relevant to the area have been made in the field of Weak Artificial Intelligence, with little progress happening in Strong AI.
Examples Of Application Of Artificial Intelligence
Artificial intelligence is no longer a thing of the future, it is already applied in various segments of the economy.
Here are some practical applications of AI:
Industry
Automation has been an industry buzzword for many decades.
And machines keep getting smarter.
With AI, there is equipment that manufactures and checks the products without needing the operation of a human.
This is just the beginning, as machines are being developed that also create and execute new projects on their own, that is, they do creative work and have no limitations to their use.
GPS
The routes suggested by the Waze app may even lead to passing through dangerous places, but people keep using it because it actually indicates the fastest way.
This is because the program uses artificial intelligence to interpret data automatically provided by other users about traffic on the roads.
Self-Driving Cars
Uber, Google and Tesla are some of the companies developing self-driving cars, which don’t need a driver to drive them.
The innovation is made possible by a combination of various technologies and sensors that provide data for algorithms to guide the movement of automobiles.
User Service
Chatbots and systems with natural language processing are getting smarter and smarter to replace human attendants and be available to users with questions 24 hours a day.
Online Retail
Online store algorithms recognize users’ shopping patterns to present them with offers according to their preferences.
In this format, Amazon created Amazon Go, a retail store that does not have stockists and checkouts, for example.
Journalism
With access to several databases, there are programs capable of writing informative journalistic stories in a way that makes it difficult for the reader to distinguish them from texts written by humans.
Banks
Financial institutions use algorithms to analyze market data, manage finances, and relate to their customers.
Right
Law firms and legal departments will rely on robots to accomplish much of what a lawyer does faster, more accurately, more directly, and more affordable.
Health
Healthcare is one of the areas that benefit the most from technological advancement In healthcare, we have a very recent example, which is the use of smart machines to help combat the Covid-19 pandemic.
The AI collaborated with the identification of foci of contamination and infection, in helping the authorities to manage calls and to solve doubts of the population, in addition to the fight against fake news.
Previously, technology was already cooperating with the early diagnosis of diseases such as Alzheimer’s and Parkinson’s disease.
It also helped in reading exams, and identifying changes in CT scans, for example.
Therefore, some of the main arguments in favor of artificial intelligence come from health.
Social Networks And Applications
Photo recognition, identification of objects and situations, thematic playback of videos, simultaneous translation, and automatic removal of inappropriate content are some of the contributions of AI to social networks and other applications.
Other than that, the algorithms can customize the feed of posts and news, suggest friendships according to the network of contacts, present augmented reality features, and synchronize content instantly.
Entertainment
Entertainment is one of the areas that has benefited the most from AI.
One of the most everyday examples is the personalized recommendation system on streaming services, ensuring a better experience on the platform.
However, we didn’t stop there.
Games and eSports are increasingly immersive.
Virtual reality accessories offer a perception that the person is, in fact, performing the actions of the screen character.
Predictive Maintenance
Anticipating problems is a beautiful way to avoid headaches in the future.
And that’s exactly what AI has been doing by collaborating with predictive maintenance.
Evaluating preliminary information on machinery and products, it prevents unnecessary repairs from being made and any errors from stopping an entire company.
What Is Big Data?
Big Data is the term used to refer to our current technological reality, in which an immense amount of data is produced and stored daily. From this abundance of information, there are systems created to organize, analyze, and interpret (i.e. process) the data, which is generated by multiple sources. Remember when we said that artificial intelligence algorithms needed certain information for decision-making?
Because this information is available in the age of big data.
For example, when you access the page of a product in an online store, the data about your access (how long you stayed on the page, where you accessed it, what was your next action, etc.) are stored. This information can motivate an algorithm to guide the display of product offers best suited to your query and related to the one you viewed.
Big Data And Artificial Intelligence
The article “Artificial Intelligence: A powerful paradigm for scientific research” highlights the data-driven character of all AI.
Therefore, the authors emphasize the need to develop machine learning, so that machines have a continuous learning capacity and do not rely only on stored data to present answers. This is where Big Data and artificial intelligence are intrinsically connected, as this is a key relationship to drive breakthroughs in both areas.
Big Data provides large amounts and varieties of data, coming from various sources such as social networks, sensors, and online transactions. This data is essential for training and feeding AI models, allowing them to learn complex patterns and make predictions.
The combination of Big Data and AI makes it possible to analyze large data sets, as well as extract relevant information and generate insights. In this way, it is fair to say that without Big Data, there would be no AI, and without AI, the technology of storing and processing mass data would not develop as fast.
What Is Predictive Analytics?
Predictive analytics is the ability to identify the likelihood of future outcomes based on data, statistical algorithms, and machine learning techniques.
From big data, therefore, there are programs capable of doing this type of analysis, identifying trends, predicting behaviors and helping to better understand the current and future needs of customers.
And, of course, qualify decision-making in machines, equipment and various software, taking artificial intelligence to a new level.
Predictive Analytics And Artificial Intelligence
As a discipline, predictive analytics uses statistical and mathematical techniques to extract patterns and trends from historical data sets in order to make predictions.
Therefore, it is related to AI, since both play key roles in the processing and interpretation of data.
In a way, predictive analytics can be considered a branch of artificial intelligence as it relies on algorithms and machine learning techniques to build predictive models from historical data.
This is a two-way street, in which the evolution of one area is reflected in the other.
By applying artificial intelligence techniques such as machine learning, neural networks, and optimization algorithms, predictive analytics can be enhanced and automated.
AI models are trained with historical data to learn complex patterns and relationships between variables.
From this, predictive analytics benefits from artificial intelligence by utilizing its algorithms and learning capabilities to improve the accuracy of predictions.
In contrast, AI benefits from predictive analytics by providing a practical application for its models and techniques.
What Is The Internet Of Things?
It wasn’t so long ago that the only way we had to experience the magic of computer science algorithms and the internet was by operating a computer.
Not today.
There are a number of hardware that work connected to the internet, such as the smart TV that allows you to watch content in streaming, the smartwatch that measures the heartbeat during an exercise and sends the data to an app, etc.
This is the Internet of Things (IoT): the connection between physical devices and the World Wide Web.
Most of these devices use, even on a small scale, artificial intelligence
Netflix, for example, suggests movies and series to the user based on what they have previously watched.
Internet Of Things And Artificial Intelligence
As research published in the IEEE Xplore journal on the Internet of Things (IoT) and artificial intelligence highlights, “autonomous management intelligent services are critical to the integration between IoT services.”
After all, IoT generates large volumes of data in real-time from connected devices, and AI provides the tools and techniques to analyze and interpret it.
In addition, the combination of IoT and AI makes it possible for connected devices to make autonomous decisions based on the data collected and analyzed.
This would happen, for example, with sensors in a factory detecting equipment failures, automatically triggering maintenance.
AI also allows IoT devices to learn from the data collected, improving their performance over time.
It would be the case of a smart thermostat capable of learning a user’s preferred temperature patterns, adjusting the environment for greater comfort and energy efficiency.
Myths And Truths About Artificial Intelligence
The examples of artificial intelligence in everyday life are already so many that sometimes it is even difficult to distinguish reality from fiction.
One of the most propagated myths in this regard is that AI will develop to such an extent that the day will come when it will rebel against humanity.
There are researchers who point to a future in which machines will be able to take control over their own programming, in the best “Terminator” style.
In this sense, it is worth mentioning a presentation to the British Science and Technology Select Committee in which Michael Osborne, professor of machine learning at the University of Oxford, receives several questions.
He points out, for example, that the development of AI has been encompassed by the arms race, in which global powers compete for the last word on the matter.
On the other hand, there are those who say that it works better than the human brain, when in fact this is far from happening.
Another myth, this one with a more solid foundation, is that AI will wipe out jobs.
On the other hand, the same article highlights that AI should cause new jobs to emerge, counterbalancing in a way the losses it should cause.
What Are The Challenges Of Using Artificial Intelligence?
That artificial intelligence is gaining ground within productive routines is beyond doubt.
That doesn’t mean there aren’t challenges in its implementation.
We’ve listed some of the key obstacles to a more massive use of AI in companies:
Lack Of Skilled Labor
Lack of training is still a problem in many companies and regions.
Gradually, however, this reality is changing, with the entry of professionals with the technical skills necessary to master the technology and use AI in the best way.
Loss-Making Investment
A company will only invest in something if it has the confidence that it is an asset that can bring benefits in a safe and proven way.
However, the absence of studies customized to the reality of the business ends up driving AI away from many organizations.
Not to mention the previous topic: why finance artificial intelligence technologies, if there is no human capital capable of doing this management?
Difficulties In Process Integration
Including AI in the routine of a company requires a digital transformation, which, in turn, goes through the integration of different processes. Often, organizations are not prepared for this disruptive change or do not have the ideal structure to move forward.
Ethical And Legal Uncertainties
Debates about the legal and ethical limits of AI are yet another challenge for the implementation of these technologies.
Advantages And Disadvantages Of Artificial Intelligence
After everything we’ve seen so far, let’s break down more about the advantages and disadvantages of artificial intelligence in strategic segments.
Advantages Of Artificial Intelligence
- Automation: Automation frees up humans to focus on more complex and creative activities
- Efficiency: By performing tasks with speed and accuracy superior to humans, AI can lead to improvements in efficiency and productivity
- Improved decision-making: AI algorithms can analyze large volumes of data and identify patterns that can help with decision-making.
Disadvantages Of Artificial Intelligence
- Bias and discrimination: Some AI algorithms may reflect biases and discriminations present in the data used to train them
- Privacy and security: The collection and processing of large amounts of data for AI can raise concerns about privacy and digital security
- Data dependence: Lack of adequate data or biased data can affect the accuracy and reliability of AI systems.
What Is The Importance Of Artificial Intelligence?
One of the examples of artificial intelligence in everyday life is tools like Alexa and Siri, which use voice commands to give answers.
Outside of conversational AIs such as Chat GPT and Bard.
These are just a few of the many examples that illustrate the importance of artificial intelligence and point to a future in which we will no longer live without it.
It will be like the telephone, the TV, and the internet, which after its massification, have never ceased to evolve and be part of our daily lives.
Artificial Intelligence In Companies
Of course, there will always be niche markets with consumers who make a point of acquiring handmade products and services, made with all the affection that only a human can offer.
Even so, it’s safe to say that AI is here to stay and will take over more and more processes in companies across all industries.
Those who are successful in using this technology will be able to produce more and lower their costs, gaining an immense competitive advantage.
Every manager needs to be aware of these technological innovations and plan the future of his company.
Acquire or develop technology?
How to get human resources capable of dealing with AI?
These are just some of the challenges that present themselves.
There are 76 hours of intense learning about these concepts, which makes the decision-making of any professional much more qualified.
What Is The Application Of AI In The Routine Of Organizations?
It is wrong to think that the use of AI is restricted to certain sectors.
We now list four areas that can be positively impacted by the application of artificial intelligence in your productive routines:
Financial
The first aspect to benefit from AI is financial.
After all, thanks to the data processed by artificial intelligence, it is possible to have a greater basis when making choices and setting budget priorities, for example.
Automated calculations also help you estimate the best Return On Investment (ROI).
There are also all the advantages aimed at reducing bureaucracy, such as the possibility of carrying out large-scale economic operations outside business hours.
Human Resources (HR)
Speaking of reducing bureaucracy, human resources managers no longer need to calculate overtime, vacations, and other labor rights, much less worry about inspecting time cards.
After all, with AI, all of this can be done automatically.
Selection processes also tend to be more efficient, as recruiters can turn to databases and use filters to choose candidates who fit job profiles.
With a more assertive management of information, the internal professional relocation itself is favored.
After all, artificial intelligence can take over mechanical functions, while employees focus on more creative tasks.
Marketing
Of all the business areas, marketing is perhaps the one that has had the most advantages with the massification of AI.
The sector has made gains at all ends.
Starting with the mapping and anticipation of trends and opportunities, through the analysis of behavior and customer service tools, to the segmentation of profiles and the recommendation of products based on the habits and histories of customers.
These benefits are practical and the numbers prove it.
According to a Salesforce survey, the impact of artificial intelligence on Customer Relationship Management (CRM) tasks could boost companies’ profits by as much as $1.1 trillion. Operations or production
An integral part of the so-called Industry 4.0, along with the Internet of Things (IoT) and other technologies, artificial intelligence arrives to make operational and productive routines more practical and dynamic.
In addition to the example brought earlier about predictive maintenance, which makes it possible to analyze data from any system, whether virtual or physical, AI can be useful in improving simulations and monitoring of robots.
What Is The Impact Of Artificial Intelligence On The Job Market?
Yes, it’s true that artificial intelligence is expected to reap jobs in the coming years, as we saw earlier.
On the other hand, it must also create new functions, for which those who prepare before will come out on top.
So, the best thing to do is to accept the new reality, adjusting to act in an increasingly dynamic market dominated by digital and quantum technology.
And especially, keep an eye on the professions of the future.
Why Has AI Become So Strategic And What Are Its Risks?
Throughout this article, we emphasize that artificial intelligence can bring numerous benefits to organizations, but also that it is a transformation that requires preparation.
It is not overnight that a company will begin to dry up its team of professionals and replace its human capital with computers.
Even because those who operate these machines are people.
That is, a simple change is not the best way.
The way out here is to invest in intellectual training and talent retention to build a healthy relationship between the parties.
Perhaps, the key word is adaptability.
It is necessary to adapt to the new in order to enjoy all the advantages it has to offer.
In the case of AI, there are gains such as production optimization, cost reduction and process integration.
Many companies have already realized the need to keep up with digital transformation and have begun to invest heavily in artificial intelligence.
According to a PWC study, 54% of managers revealed that they have made major investments in AI in recent years, believing that the initiative will bear fruit soon after.
How To Define A Utilization Strategy For Artificial Intelligence?
Since setting the stage for the implementation of AI is so important, we have put together a step-by-step that can be very useful for you to succeed in your company’s digital transformation process.
Check:
Set Goals And Carry Out Good Planning
It all starts with setting goals and questioning how AI can help your business achieve those goals.
Try to ask very practical questions, such as:
- If the goal is to increase productivity, how can AI be useful?
- In the absence of support and interaction with customers, what benefits can the implementation of AI bring?
- Is the idea to use AI to correct operational defects or develop new products?
There is always the chance that you will have the idea of using artificial intelligence for multiple focuses, which is not prohibited, but can delay its implementation.
Collect A Large Volume Of Data
Data is the main guarantee of successful implementation of AI in your company.
After all, they are the ones that will allow the platform to integrate securely and reliably with other business software and workflows.
There are several ways to collect a large volume of information – all of which require time and determination, but they are a must.
You can opt for internal use tools such as ERP and CRM or invest in Big Data Analytics and the IoT itself.
Whatever your choice, care has to be in compatibility.
The solution needs to be AI-compliant for there to be a correct capture of the data.
Adopt An Efficient AI Solution
There are several types of AI solutions on the market.
Certainly, one of them is indicated for your goal.
The pursuit of efficiency should be your main obsession here.
In addition, look for experienced suppliers, who already have a certain name in the market, to take this first step in search of automated routines and organized workflows.
How To Use Artificial Intelligence In Your Company?
The list of possible uses of artificial intelligence in business is extensive.
To stay only in the most relevant, we highlight 10 possibilities:
- Data analytics for business insights
- Process automation and repetitive task execution
- Customization of products and services
- Automated customer service
- Supply Chain Optimization
- Demand and inventory forecasting
- Fraud detection and cybersecurity
- Analysis of feelings and feedback from customers
- Talent recruitment and selection
- Virtual assistant for internal and external support.
The Future Of Artificial Intelligence
Artificial intelligence is already a reality, and the trend is that in the future it will become even more present in our routines.
The coming years point to a significant increase in task automation, with advances in service personalization and progress in areas such as healthcare, transportation, and sustainability.
However, ethical issues, privacy and proper regulation will be crucial challenges to be faced to ensure a responsible use of AI.
By the way, these are topics that we have already debated here, in a content about the Legal Framework of Artificial Intelligence.
Conclusion
Now that you know the universe of artificial intelligence better, do you see this technology as a threat or an opportunity? If you see a threat, you are already at a disadvantage compared to other managers who are already looking to apply the intelligence of algorithms to their advantage.
The smartest thing is to accept that technology is advancing toward the creation of even smarter machines.
With the time that will be saved in activities that will no longer require human work, the way is open for more strategic actions by professionals in any area. So, in addition to understanding the basic precepts of technology, prepare to think and act differently, in a way that no machine can imitate.