7 Myths and Misconceptions About Artificial Intelligence

Table of Contents

• Myth #1: AI Will Eradicate Jobs and Replace Human Workers
• Myth #2: AI, Machine Learning and Deep Learning Are Interchangeable
• Myth #3: Super-Intelligent Computers Supersede Human Intelligence
• Myth #4: AI Threatens Privacy and Security of Users
• Myth #5: Only Companies With Big Investments Can Afford AI
• Myth #6: Training an Ai Requires Large Amount of Data
• Myth #7: AI and ML Models Are Biased
• Conclusion

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AI is the future that will bring about a change as profound as the World Wide Web did two decades ago. In the years to come Artificial Intelligence (AI) will become the cornerstone from which the world will plunge into technological revolution.

However, like any other transformational change, this too has paved the way for some distrust and misapprehension. Let’s have a look at some of the most common myths and misconceptions around AI.

Myth #1: AI Will Eradicate Jobs and Replace Human Workers

AI’s introduction to our lives and workplaces may indeed cause some disruption to employment. But it is only partially accurate to assume that this is the only impact it will have.

Artificial Intelligence is merely meant to work with humans and not instead of them. The industrial revolution is a testament to the fact that transformational changes like invention of machines create a consistent growth in the employment stance.

AI systems could replace certain jobs that were earlier the tasks of humans. But the possibility of entirely new jobs being a part of employment opportunities. From the point of view of business, employers are looking at AI as a solution to augment human workforces and enable them to work in smarter and more efficient ways.

Myth #2: AI, Machine Learning and Deep Learning Are Interchangeable

AI, Machine Learning and Deep Learning are often used interchangeably but should not be confused as synonyms.

AI refers to machines that perform tasks attributed to human intelligence. Machine Learning is a subset of AI which enhances intelligence by training algorithms using data. Similarly, Deep Learning is a subset of Machine Learning which uses neural networks to solve a problem or perform a task.

Essentially, AI has a broad spectrum of which Machine Learning and Deep Learning are two subsets.

Myth #3: Super-Intelligent Computers Supersede Human Intelligence

A lot of speculation dwells around the capability of computers powered by AI to surpass humans.

Artificial Superintelligence or ASI is a term that refers to a time in future when a computer’s potentiality will exceed that of human beings. Ideally, if that were to happen, it would mean that AI would need to develop strategic thinking and reasoning and work independently.

Experts believe that AI is still at an embryo stage of development and it will be long before we start tapping the complete potential of an AI system. Personal virtual assistants like Siri, Alexa, and Cortana are the simple applications of AI which can handle decent tasks. They come with the limitation that they only respond in certain ways.

Companies such as Tesla, Waymo, Addison Lee, Audi, and others are developing self-driven cars, which is another example. But even these aren’t totally independent and cannot operate entirely autonomously. While fear of uncertainty about the future of AI haunts many, studies such as the Turing Test have proven that computers cannot imitate, think or reason like humans. The debate about computers taking over humans in future is merely a vast assumption in theory with no proof to support such an argument.

Myth #4: AI Threatens Privacy and Security of Users

There has been a lot of hearsay regarding this notion and AI dystopians claim that AI-powered technologies are invading their privacy and security.

Most people’s inadequate acquaintance with measures to protect their privacy is one of the main reasons for such concern. An AI can inherently analyze huge amounts of data making it efficient in terms of speed as well as scale. AI systems require data collection and analysis, but laws and regulations ensure that they do not compromise privacy.

In fact, it is quite probable that the threat to privacy is greater in non-AI systems because they too amass a large amount of data. This is the reason why tech giants like Google, Facebook, Amazon, Netflix which primarily run on mass data collection from their customers are adapting Privacy-Centric AI into their programs. Experts believe that the advantage of using AI-enabled systems is that most of the analyzed information can be obtained without the risk of uncovering personally identifiable information.

Myth #5: Only Companies With Big Investments Can Afford AI

It’s not uncommon for small and medium enterprises to presume that the cost of employing an AI will be expensive beyond their means. The reason being that the working of the technology is quite complex and scientific. Most people would imagine actual robots, supercomputers, and drones when they think of AI systems.

AI implementation doesn’t require investing millions of dollars or employing experts for research. One of the best use cases of AI in small to medium businesses is through Robotic Process Automation (RPA) which has impacted a vast array of industries like healthcare, finance, banking, IT and HR. The RPA technology enables these SMB’s to have an efficient workflow and is extremely affordable.

Myth #6: Training an Ai Requires Large Amount of Data

It is indisputable that training an AI from scratch requires a large amount of data and computing power, but not all scenarios follow this rule.

Essentially, the function of the AI system employed will indicate how much training it has to undergo. Not only that, it depends on the field of application of the AI system. For instance, if the AI system has the training to perform the task of driving a car it would require merely a few terabytes of data.

Furthermore, the maintenance of an AI’s basic data framework typically involves replacing components as needed based on the assigned task.

Myth #7: AI and ML Models Are Biased

Human beings design and train AI and ML models, and these models may sometimes learn subtle biases from human practices.

An AI system cannot think consciously but it learns and replicates behavior from the data being fed to it during its training. But experts believe the sources of the AI’s vulnerability are identifiable and can be detected and corrected.

In fact, a unique AI tool called “Public Safety Assessment” is being used by judges in the US to obtain most relevant and effective information to be able to make fair decisions. Such exceptional implementations of AI technology can bring about a change in a backdrop that heavily relies on decision making and upholding values at the same time.

Also, with respect to the bias issue, researchers are amending AI vulnerabilities by building more transparent algorithms.

Conclusion

Artificial Intelligence has brought about a metamorphic change in the technology realm. The unique ability this technology possesses to learn and mimic human interactions has made our day-to-day activities simpler. Further advancement in AI-powered technologies shows great potential across various industries.

With technology as powerful as artificial intelligence, mistrust and doubt are inevitable. It is understandable that some may find it difficult to fully grasp the workings of such complex technology. It is important to know that AI is still in the developing stage and that its full potential is still under exploration.

As far as AI taking over humans goes, that is an assumption that simply has no basis whatsoever. AI has one primary goal, which is to be of assistance to humans and co-exist with them.

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