Artificial Intuition is the Next Phase of Artificial Intelligence
The goal is to minimize human intervention and allow machines to operate independently.
To date, AI has gone through three phases of its development. Descriptive analysis to answer what happened, diagnostic analytics to answer why it happened and predictive analytics to answer what might happen next. The analytical and forecasting power of AI has increased tremendously, but it won't stop there.
The problem with the current generation of AI is it needs to receive data from humans. This reduces the problem-solving power of artificial intelligence in dealing with new events. There is no denying that AI has made it easier for humans to predict the future. But, dealing with future events, like another pandemic, needs a more powerful AI.
We need machines that are self-contained, can make their own decisions and predict future events without the need to receive data from humans. The goal is to minimize human intervention and allow machines to operate independently.
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The good news is artificial intelligence has started its fourth phase, and it is mature enough to make human-like decisions. The fourth phase is called Artificial Intuition.
What is Artificial Intuition and how it works
Artificial Intuition is the next step for AI and it can revolutionize the machine learning process. Since the time that our ancestors discovered fire, and until today when traveling to other planets isn't out of reach, human intuition evolved dramatically with a capacity to grow over its limitations. But can AI mimic human intuition? The answer is yes.
Intuition is a state of mind that grows the capacity to perceive, interpret and operationalize information from an ordinary-level to in-depth analysis of inputs. This is what we know as logical thinking and enables high-level function for the brain. For years, imitating human intuition has seemed impossible. It was believed that the highest level for AI is predictive analysis to forecast the future based on input data.
Artificial Intuition has a similar function to human intuition. Traditional AI requires human involvement to tell what must be done. The decisions that have to be made are taught to machines by humans. Artificial Intuition, on the other hand, operates independently without any specific instruction.
The advanced algorithms in the heart of the machine can interpret the data and identify correlations to make the final decision. Artificial Intuition uses a qualitative model, a contextual language and a set of mathematical equations to see the end of the process from the beginning, which is a kind of high-level forecasting.
Artificial Intuition relies on advanced data analysis to detect what must be done, and also to predict future threats and opportunities. This function is quite similar to human instinct. What transformed us from cavemen and uncivilized humans to those who can build the most advanced machines was the development of our instincts.
With Artificial Intuition, the goal is to add human intuition to a machine and make it think like a human. This way, the machine is equipped with a computational instinct. Thanks to progressive perception and high-level analysis, the problem-solving ability of machines increases to an incredible level. MIT researchers have been working on this for years, and they improved problem-solving power by 10-15 percent. The researchers tried to teach the problem-solving methodology of smart people to the machine.
Of course, it's not an easy job to add intuition to a machine. Apart from discussing technical limitations, a machine needs to be equipped with a wide range of knowledge and technologies, including computer engineering, cognitive sciences, linguistics, neuroscience and more.
Artificial Intuition in different industries
Artificial Intuition still has a long road ahead to be operationalized and find its place in the market. Almost all industries can host it, although some have a better opportunity to exploit it. In the next ten years, Artificial Intuition will be at the core of any business operation in big companies. An AI-first approach will be mandatory for any company that wants to stay competitive.
Healthcare: Healthcare is among the industries that have adopted AI at a high level. AI in healthcare is currently being used for things like diagnosis processes, treatment protocol development, drug development and more. However, Artificial Intuition can be a revolutionary innovation in healthcare.
We all know the scope of damages that the Covid-19 pandemic caused to the world's health and businesses. Since one of the main usages of Artificial Intuition is active prediction of future events, it can be used for confronting future pandemics and health crises. Each pandemic usually shows symptoms before it occurs. Artificial intuition, with its advanced analysis of data, can play an active role in preventing any upcoming pandemics.
Cybersecurity: Cyber attacks against companies have increased, forcing them to invest heavily in cybersecurity. Some companies are currently using AI to detect vulnerabilities in their systems. But the current generation of AI used for cybersecurity has some flaws that may lead to things like alert fatigue. Thanks to more advanced analytics and resolution ability, Artificial Intuition can detect unwanted and unusual activities and repel attacks. Moreover, the risk of data breaches and infiltration of systems will be minimized.
Retail: Retail is currently more about the psychology of customers rather than merely selling. Artificial Intuition can help retailers present more personalized offers to customers through analyzing and understanding their behavior and shopping habits. AI can also help with product placements in physical stores and pricing strategy. For expanding to new markets and addressing the needs of future customers, retailers can use Artificial Intuition to identify possible opportunities and risks. Managing the supply chain and increasing the competitiveness of a business are other advantages of AI for the retail industry.
Financial Sector: Banks and financial institutions are currently using AI and machine learning to identify financial cybercrimes, scams, tax evasion, ATM hacking, monitoring account transactions and more. Artificial Intuition in the financial sector can help companies to identify breaches in their financial systems in the early stages. This can reduce the risk of financial cybercrime and asset theft. Also, suspicious transactions in the banking system and the source and destination of the transferred money can be closely monitored by Artificial Intuition.
The risks of adding human intuition to a machine
It's a fact that every new technology has two sides: A good side for facilitating human life and community service. And a dark side that allows criminals to continue to make illicit gains in new and innovative ways. AI is not an exception and some criminals are currently using it to exploit people. Violations of privacy through wider surveillance, the dissemination of deep fakes and misinformation, the loss of jobs and using AI for wars and weapons are among the concerns that exist around Artificial Intuition.
More importantly, Artificial Intuition consumes data and makes decisions based on that inputted data. Any malice in spreading false data to the machine can force it to make harmful and risky decisions. If you have seen movies like The Matrix and I, Robot, you are probably more aware about the dangers of AI.
Over the next few years, artificial intelligence will enter a new level of development. Governments will need to enact laws to monitor and control it. Any weakness in lawmaking can be catastrophic. Just imagine that you have a machine that has been poisoned by false data and is making dangerous decisions on its own without human intervention. That is a very troubling scenario.
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