In this article, you will learn about AI vs Human Intelligence, Difference Between AI & Human Intelligence.
- Definition of AI & Human Intelligence
- Comparison of AI & Human Intelligence
- What AI cannot do without – The “human” factor
- Artificial Intelligence vs. Human Intelligence: What will the future hold?
Read more to know each in detail.
Artificial Intelligence has come a long way from being a component of science fiction to reality. Today, we have a host of intelligent machines like self-driving cars, smart virtual assistants, chatbots, and surgical robots, to name a few. Since AI became a mainstream technology in the present industry and a part of the common man’s daily life, it has sparked a debate – Artificial Intelligence vs. Human Intelligence.
While Artificial Intelligence seeks to design and create intelligent machines that can perform human-like tasks, one cannot help but think, “Is Artificial Intelligence sufficient in itself?”
Perhaps the biggest fear is that AI will “replace” humans and outsmart them in a few years. However, it is not entirely true. Although AI is highly advanced – now that machines can learn from experience and make smart decisions – AI cannot function optimally without relying on innately human attributes like human intuition.
Now, let’s dig deeper into the Artificial Intelligence vs. Human Intelligence debate to understand their peculiarities and relationship.
Artificial Intelligence vs. Human Intelligence: Definition
What is Artificial Intelligence?
Artificial Intelligence is a branch of Data Science that focuses on building smart machines capable of performing a wide range of tasks that usually require human intelligence and cognition. These intelligent machines are imbued with learning from experience and historical data, analyzing their surrounding environments, and performing befitting actions.
Vendors have now been scrambling to promote their commodities via AI. This helps them to accelerate their business intensively. There are several subsets like machine learning, R, Java, and other popular programming languages.
AI is an interdisciplinary science that leverages concepts and tools from multiple fields like computer science, cognitive science, linguistics, psychology, neuroscience, and mathematics.
What is Human Intelligence?
Human Intelligence refers to humans’ intellectual capability that allows us to think, learn from different experiences, understand complex concepts, apply logic and reason, solve mathematical problems, recognize patterns, make inferences and decisions, retain information, and communicate with fellow human beings.
What makes human intelligence unique is that it is backed by abstract emotions like self-awareness, passion, and motivation that enable humans to accomplish complex cognitive tasks. Human intelligence is not just constricted to a particular pattern but can be changed depending upon the problems that arise with it. It can change substantially with the crux of the situation.
Artificial Intelligence vs. Human Intelligence: A comparison
Here’s a head-to-head comparison between Artificial Intelligence and Human Intelligence:
While Human Intelligence aims to adapt to new environments by utilizing a combination of different cognitive processes, Artificial Intelligence aims to build machines that can mimic human behavior and perform human-like actions. The human brain is analogous, but machines are digital.
In Artificial Intelligence Human Intelligence, Artificial Intelligence aims to provide a style of work efficiency that will help to solve problems without any hassle. It can solve any kind of problem in the blink of an eye whereas, Human Intelligence takes a lot of time to accustom to the mechanisms with a considerable amount of time. So, to see to it, the main difference between natural and artificial intelligence is the process of functionality and the time taken by both of them.
Humans use the brain’s computing power, memory, and ability to think, whereas AI-powered machines rely on data and specific instructions fed into the system.
Besides, it takes a very long time for humans to process and understand the problems and gets accustomed to them. In the case of Artificial Intelligence proper inputs and study, it helps them to provide accurate result in the end.
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Human Intelligence is all about learning from various incidents and past experiences. It is about learning from mistakes made via a trial and error approach throughout one’s life. Intelligent thought and intelligent behavior lie at the core of Human Intelligence. However, Artificial Intelligence falls behind in this respect – machines cannot think. Hence, in this case of the difference between AI vs Human brain, Human Intelligence has a much more powerful thinking capacity than Artificial Intelligence and can have great problem-solving skills depending on the crux of the situation.
They can learn from data and through continuous training, but they can never achieve the thought process unique to humans. While AI-powered systems can perform specific tasks quite well, it can take years for them to learn a completely different set of functions for a new application area.
Artificial Intelligence, can learn from data and through continuous training, but it can never achieve the thought process unique to humans. While AI-powered systems can perform specific tasks quite well, it can take years for them to learn a completely different set of functions for a new application area.
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What AI cannot do without – The “human” factor
Artificial Intelligence vs. Human Intelligence debate isn’t a fair one. Granted that AI has helped develop intelligent machines that can outperform humans in some respects (case in point – AlphaGo and DeepBlue), they have yet to go a very long way to match the human brain’s potential. Although AI systems are designed and trained to mimic and simulate human behavior, they cannot make rational decisions like humans.
Besides, talking about the difference between human and Machine Intelligence, Human Intelligence is the main contributing factor that has given definition to the simulations that are created in Machine Intelligence. So, the main difference between natural and Artificial Intelligence is the data that has been fed to them with the limited problem-solving skills which are offered in this regard.
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The decision-making power of AI systems is primarily based on events, the data they’re trained on, and how they are related to a particular event. AI machines cannot understand the concept of “cause and effect” simply because they lack common sense. Nick Burns, an SQL Services Data Scientist, puts it quite well: “No matter how good your models are, they are only as good as your data…”
Humans possess the unique ability to learn and apply their acquired knowledge in combination with logic, reasoning, and understanding. Real-world scenarios require a holistic, logical, rational, and emotional approach that is specific to humans. Therefore, in some aspects of the difference between human and Machine Intelligence, human intelligence seems to be much more feasible than others.
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Artificial Intelligence vs. Human Intelligence: What will the future hold?
Right now, AI is still developing and advancing. The time required to train AI systems is considerably high, which isn’t possible without human intervention. Be it autonomous cars and robots, or sophisticated technologies like natural language processing and image processing, they all rely on human intelligence.
Human Intelligence is the one to create AI in the first place. Therefore, it totally depends upon the modifications made by human intelligence to introduce new features in AI. Therefore, to look into the age-long debate about which is better, human intelligence holds much more credibility for creating methods of Machine Learning.
Presently, automation is the leading AI application that’s penetrating the industry rapidly. In a 2018 report by the WEF, the Swiss Think Tank predicted that by 2022, AI would displace 75 million jobs globally while also creating 133 million new jobs. The new job profiles will demand Data Science specific skills like knowledge of Mathematics & Statistics and ML algorithms, proficiency in programming, data mining, data wrangling, software engineering, and data visualization.
In 2022, WEF has made several agendas of how Artificial Intelligence is the future and it will enormously help us in creating an environment with accurate data. The field has provided feasible job opportunities to people, which has helped them to turn their careers around. The field of Artificial Intelligence is now massive and has been supported immensely with the new branches to learn different components of Data Science. In comparison to Artificial Intelligence Human Intelligence is much more customisable and might not be feasible enough to solve a complicated problem as a whole.
Today, companies using Big Data and Data Science technologies are skilled experts like ML Engineers, Data Scientists, Data Engineers, etc., who know the nitty-gritty of AI/ML. It is the domain knowledge and versatile skillset of such experts that create value out of Big Data.
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AI is an invaluable tool shaping the industry, and automation, coupled with intelligent workflow, will be the norm across all sectors in the near future. And while AI has mastered intelligent behavior quite well, it cannot mimic a human’s thought process. So, in this case, AI has been lagging behind when competing as AI vs human brain, which can only solve problems according to the interfaces that are provided in this regard. The human brain is still the mastermind for creating different aspects of simulations and inputs that will be looked after in the AI and help in progressing the concept of Machine Learning.
Since scientists and researchers still don’t know the mystery behind the human thought process, it is highly unlikely that we’ll create machines that can “think” like humans anytime soon. To conclude, the future of AI will be governed mainly by human abilities. It will be complemented by human intelligence and cognizance.
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This will provide you feasible inputs depending upon the subject, and it, therefore, helps you to get in-depth knowledge about the different branches of Data Science paired with aspects of Machine Learning.