AI intelligence stands for artificial intelligence, is probably the most debatable and conversational technology. However, sometimes it works as a boon for the society then the other times it shows the dark face if misused. Thus it revolves around some myths.

Though there are several advantages of artificial intelligence, these myths have undoubtedly depicted the questionable future of human society if artificial intelligence can take over all human work and similar intelligence in the future. Remember the artificial intelligence movies The Terminator or Matrix! But are all the machine-related intelligence belongs to the same complexity? Or are they really achievable?

Well, you must have heard about three types of artificial intelligence –

Weak AI / Narrow AI – Weak AI works to reduce human effort. However, there is no intelligence associated with its functionality. For example, a speedometer measures the speed of a vehicle. This is something that eliminates the human effort of measuring the job. However, there is no intelligence in this activity. Moreover, it does not recommend the optimum speed based on road condition, etc.

Thus, we can say weak AI relates to and based on pure coding that directs some jobs. Additionally, we don't directly inject real intelligence in it. Furthermore, or doesn't have any cognitive approach. They are suitable for routine tasks. To explain more, Computer vision, natural language processing, speech and image recognition are still at the current stage of narrow AI.

Strong AI /Human-level AI– Strong AI associates with machine job that belongs to part of cognitive approach or thinking capability. Using strong AI, a machine can logically take actions based on an understanding on its own. Chatbots are an excellent example of it. Some chatbots have the capability to accept only positive information and reject negative questions. Microsoft TAY is one example of it. However, achieving strong AI in the real sense is still hard to achieve.

Super AI relates to human-level consciousness. Though this is still at the hypothesis level, researches are on. Furthermore, the biggest myth that comes around it is that super AI will destroy humanity. Whether that is true or not is still a question, but it is a matter of time, which will answer the question.

To explain more, if we consider artificial intelligence applications, then Weak AI performs small level tasks with the help of Machine learning, Natural language processing, etc. Also, we need to train them with massive data sets. On the other hand, Strong AI comes with a higher level of intelligence that is almost nearly human intelligence with emotional intelligence and other features. If we look into the common myths of AI, they associate with these two types of AI.

However, what are those myths and AI facts? Well, there are many. Here we will look into 5 such AI intelligence myths and truths about their reality.

Myth #1: AI intelligence technology will cut over human jobs

Truth: Artificial intelligence technology is about Machines to augment human effort.

This is probably the first concern that comes to mind when considering the negative side of AI intelligence. In fact, AI implementation targets a higher level of automation, which ultimately provides cost-effectiveness. Besides, it helps in reducing the human burden. This automation capability is indeed responsible for laying off a certain percentage of employees related to Weak AI-related activities like some repetitive jobs.

But not all such tasks can be replaced by machines or AI-driven robots because many tasks need human interactions and human sentience, which AI can't perform at this level. Most importantly, the power of artificial intelligence development is augmenting human factors. This will increase the volume and quality and decrease the future cost, which is an important business process.

To explain further, it is more of changing the professional aims rather than replacement by machines. Implementing Artificial intelligence indeed means the transition from repetitive to cognitive tasks. Artificial intelligence's future will, no doubt, change the profession. It will enforce more inclined to learn new technologies related to AI.

Myth #2: AI Intelligence will take over human intelligence

Truth: Highly unlikely for the coming future.

There have been grim predictions about AI intelligence that if some limited number of companies only use it, they will misuse it. Furthermore, prediction also comes like in such scenarios, risks of Artificial intelligence will increase towards the purpose in the future. In this context, if you follow Elon Musk, then risks of Artificial intelligence may turn into a threat to humanity if controlled by "a handful of major companies." This calls for proactive regulation “before it’s too late.” Similarly, Stephen Hawking has similar views, which see AI as a replacement for humans.

enormous data analysis task. However, while competing with the human brain and emotional intelligence, it is a far-off dream in machine learning.

Myth #3:Deep learning, Artificial intelligence and Machine learning are the same

Truth: Machine learning and Deep learning are the subsets of Artificial Intelligence

It is a misleading fact that machine learning and AI intelligence are the same technologies. Also, many believe that Artificial intelligence is the implementation of Machine learning.

In reality, Machine learning is a sub-component of Artificial Intelligence, which, with training data, can solve the purpose of AI. We can define Machine learning as the algorithms that can parse data sets and then learn from it to apply what we learn to make informed decisions. In the case of Machine learning, the computer program learns from experience by performing some tasks and sees how those tasks' performance improves with the experience.

Read more - Machine learning vs. Deep learning

machine learning algorithms focus on solving real-world issues by automated tasks across industries. These may range from on-demand music service to data security services. Hence, Machine learning without data will go nowhere in the applications of Artificial intelligence.

Myth #4: Algorithms come first than data in AI

Truth: Without data, Machine algorithms cannot work. Data quality and quantity is more important than the algorithm

a subset of Machine learning and popularly known as Deep Learning. It works on many layers of algorithms called Artificial Neural Network (ANN). These networks are identical to the way the biological neural networks of the brain are. Hence deep learning is the field creating ANN that learns and makes intelligent decisions by itself. Performance as per the scale of data is the main point of difference between deep and machine learning.

similar to the human brain. Additionally, the algorithms understand the detailed data correctly from a large scale of data. Thus, without a massive amount of data, it cannot perform well.

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Myth 5#: Artificial intelligence and Robotics are the same things

Truth: AI controls robots in some cases but not always

There is a general misconception that Robotics is a part of AI intelligence. However, the fact is AI and Robotics serve very different purposes. Technically, these two fields are entirely separate, but they overlap to serve specific purposes in some scenarios. To explain more, Robotics is a branch of technology that is a combination of electronics, mechanical, and computer engineering, whereas AI is purely based on computer science. A robot can perform automated tasks using the pre-programmed logic set by applying robotics. Now robots can be artificially intelligent, that is, AI robot, or they could merely for the monotonous job that is non-AI robots. In AI robots, AI is used to control robots, but that does not mean it involves complex AI algorithms always.

Hence, in a nutshell, Robotics involves building robots, whereas Artificial intelligence leverages programming intelligence.

Final words:

AI intelligence is not magic, and it has certain limitations. Anything that becomes hype associates itself with misconceptions and myths. The same applies to artificial intelligence. However, if we stay alert to the truths, it perpetuates the distorted picture of the technology. We must remember that AI is not going to take over the world, neither the limitations will not be overcome with time. Finally, we must consider AI from a less fictional and more scientific point of view.

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