Artificial Intelligence vs. Human Intelligence: Which is the Force Majeure?
Anthropomorphizing AI is easy to do. In the age of smart assistants like Google Home, Alexa, and Siri, we imagine that these technologies have our best interests at heart. While painting a mental picture of AI, we usually envision machines that think, learn, and come to conclusions as humans do.
For a general understanding of the phenomenon, artificial intelligence is described as the intelligence possessed and displayed by machines and technologies as opposed to the one exhibited by humans. For lack of a better term, AI is used as a blanket expression to represent machine learning, cognitive computing, image recognition, and more.
Human intelligence, on the other hand, is an innate ability of the mind exclusive to humans. It is a quality that equips and empowers individuals to utilize knowledge — whether acquired from daily experience, cognitive development, or comprehension of abstract concepts — to interact with their environment. What a machine can do that has warranted the suffix, “intelligence,” is mimic this quality, in an albeit watered down manner, to make human lives easier.
The advantages of AI over human intelligence
AI technologies are born from mathematical and computational processes. These processes harness computing power to design and develop models of operating systems through combining large data sets.
The advantages of AI are many but are most apparent within the business.
In a recent study conducted by Gartner, AI augmentation was predicted to drive business worth exceeding $2.9 trillion and save organizations implementing the technology an estimated 6.2 billion man-hours worldwide. Another survey by McKinsey revealed that AI analytics could increase global GDP by $13 trillion by 2030, a16% rise.
It’s been documented that the adoption of AI can improve business processes. As a significant data initiative, almost 61 percent of businesses claim machine learning (ML) and AI to be their organization’s leading light. This proliferation of AI has led to a 40 percent projected increase in labor productivity.
Machine learning supplements automation and drives the biggest gains when applied to cyclical operational decisions made thousands of times a day, eventually replacing the most repetitive aspects of routine work.
For instance, ML has been successful at automating repetitive finance tasks such as the matching of payments and invoices, increasing matching rates by 24 percent in a matter of a few weeks and leading to huge savings.
However, while AI can perform repetitive tasks with greater efficiency, better accuracy, and higher speed, human expertise is still the most crucial factor in designing AI technology in the first place. It is this intelligence that AI seeks to emulate and is what molds the adoption, development, and emergence of AI and related innovative solutions. Ultimately, it is human intelligence that thinks and questions, asking what and why through critical thinking.
AI as a subsistence tool and not a harbinger of unprecedented change
It’s already been established that AI is a huge boost to businesses around the globe — but its real potential lies in unbridling the power of human intelligence. Instead of usurping humans and treating them as secondary in the pursuit of organizational goals, AI can be used to leverage the unique human abilities of creativity, adaptability, and leadership.
It could also enhance human intelligence in ways unseen before. Sales teams can use AI to review catalogs of potential deals. It can be used to derive algorithms based on historical patterns to prioritize calls of prospects that are more likely to convert, as well as providing information on how likely they are to buy, how long the deal might take to close, and more. This data allows salespeople close deals faster, effectively increasing both productivity and profits.
AI-augmented analytics can be used to ensure businesses ask the right questions, unlocking key performance drivers like profit and revenue. Business owners are then freed up to spend their time on decisions that matter the most.
The rise of AI
The Industrial Revolution was so named because of the enormous impact it had on the basic fabric of life. Today, AI has brought about what people have termed as The Fourth Industrial Revolution, driven by data analysis resulting from AI augmentation.
It’s clear that AI has made waves across day to day life, and will one day change the world — but how and when it will do this are still open questions.
The progress of AI has always been a hot topic because of the boom in machine learning and developments in cognitive computing. Robots and machines learn from their environment thanks to the code that helps them make sense of their surroundings, and eventually equipping them with the ability to perform complex tasks in the real world.
In an Elsevier global analysis report, commercial and research work in AI and its funding has seen a massive boom almost everywhere across the globe. Although the development of AI is widespread, there is a concentration among the Asia-Pacific countries of South Korea, China, and Japan, with China even being recognized as the land of face recognition thanks to its masterful AI implementation.
Europe, on the other hand, is the most vocal about AI and how it is developing. In fact, it published the largest number of papers on the subject, releasing almost 28% of all AI-related print the previous year. China came a close second with 25%.
Drawbacks of AI
Most data scientists and researchers agree that AI is not likely to exhibit emotions, such as anger or love — qualities that are inherently human. There should be no fear of them turning on humans. When it comes to discussing the potential risks and drawbacks of AI, it’s more or less limited to functionality. Experts define these scenarios as:
1. No intuitive replication
Irrespective of the data acquired by a machine, it can never be as sophisticated as a human. While machines might be rational and driven by logic, they can’t perceive ethics, emotions, value, virtue, and ramifications. Because of this, they don’t possess the skills to make an accurate judgment. Despite what they learn, they still function on code. Any task that isn’t coded will cause the machine or program to break down.
2. Zero improvements with experience
Artificial intelligence isn’t self-improving and can’t evolve unless new data is made available to it. If machines are made to automate the same tasks again and again, it could lead to wear and tear by virtue of excessive storage of data.
AI also can’t keep up with the dynamic and ever-changing environment they are a part of and are consequently unable to modify their response to suit their environment.
3. Creativity isn’t key
No matter how smart you make AI, it is never going to be creative. It can only label things based on the data it receives. For example, a kid could look up to the clouds and say the cloud looked like a dog, while AI, on the other hand, will say that the cloud is a dog. They can only carry out what they are commanded to do. Whilst they can help in the design and development of something, they can never actually do it on their own.
Conclusion
In the end, AI’s evolution has focused on tasks that could previously only be carried out by humans, helping remove drudgery from workers’ lives and affording them time to pursue more valuable business activities. Ultimately, it is providing humans with the chance to be even more human.
