5 Myths of Artificial Intelligence - and the Realities Behind Them

5 Myths of Artificial Intelligence - and the Realities Behind Them

The growth of artificial intelligence, from self-driving cars to digital chatboxes, has been exponential. Though enthusiastic about artificial intelligence, some companies are still hesitant about the usage of this technology. They do not know how to implement a more robust data analytics infrastructure within such a rapidly changing environment. Some businesses are taking more measured steps towards artificial intelligence initiatives, due to the dangerous myths, adopting it one brand or region at a time, whereas competitors are rushing to implement projects that span entire countries.

This article debunks the industry’s biggest artificial intelligence myths, exposing the truth behind them.

Myth #1: Artificial Intelligence and Machine Learning Are the Same

Reality: Machine Learning Is More of a Subdivision of Artificial Intelligence

Artificial intelligence, in its simplest form, can be divided into two categories: strong AI and weak AI. Though the terms have evolved in recent years, they can be generally described as follows:

Strong artificial intelligence, otherwise known as “true AI”, is able to think independently. This type of artificial intelligence is constructed to function like the human brain. Strong AI makes decisions based on understanding context and nuance, rather than based on formulas. An AI system built on strong principles is designed to learn and adapt to new situations so that it will be able to make a better decision tomorrow than it made today. Examples of strong AI include behavioural recognition and cybersecurity.

Weak artificial intelligence, otherwise known as “ narrow AI”, on the other hand, is a collection of technologies that simulate intelligence by using algorithms and programmatic responses, usually focusing on a limited range of tasks. Examples of weak AI include Amazon’s suggested purchases and Apple’s Siri.

Then, what is machine learning? As an application of artificial intelligence, machine learning allows devices to have access to a store of historical data and to learn from it. With this said, not all applications of artificial intelligence are considered machine learning. For instance, when you ask your Google Home to turn on the lights, it is not learning anything. Instead, it is just waiting for the command to turn the lights off. Machine learning systems, on the other hand, will be given sets of data and asked to draw conclusions from them. This may include searching for trends, information or patterns in a set of data that may not be seen by an analyst. Machine learning may ultimately determine that a machine should be repaired or run at a slower speed because it is about to fail. With continued learning from this data, the machine learning algorithm becomes increasingly adept at generating additional insights over time, and these insights become more accurate.

Machine learning is just one example of artificial intelligence put into action. For instance, deep learning is another subsection of machine learning, where it mimics brain activity best by simulating software.

Myth #2: Artificial Intelligence Will Occupy Many of the Jobs of Humans and Leaves Them Jobless

Reality: Artificial Intelligence Is No Different From Other Technological Advances in That It Helps Humans Become More Effective and More Efficient

Losing jobs to machinery is a legitimate fear that many individuals have. This fear has made it difficult for individuals to be open to the idea of artificial intelligence.

“What will happen to people whose jobs are replaced by AI? They move on to other jobs. We’ve done that through all of human history. That’s nothing new,” said David McCall, vice president of innovation for data centre operator QTS.

Some industries may be impacted by the rise in artificial intelligence and some workers may be displaced, but this has happened several times before as technology has been threatening jobs throughout history. Consider when computers were first adopted in the 1980s. The introduction of this technology-supported work and several businesses. Early telephone calls could not be made without an operator, and AT&T had armies of them. The industrial revolution of the late 1800s caused mass displacement. Cars and other modes of transportation have even put the horse and buggy out of business.

Similar to this, artificial intelligence will not entirely destroy jobs, instead, it will aid humans in their work, making them more efficient and effective. The good news is the more artificial intelligence is adopted, the more likely new jobs will be created. Even though, these jobs may not look like anything we see today, the variety of them will help the different levels of skills, qualifications, and abilities to evolve.

Even more so, humans are the essence of any form of business. Jobs, such as doctors, teachers, and lawyers, will not be fully automated. Doctors and radiologists use this technology to recognize abnormalities, such as tumours or other diseases. Artificial intelligence has the ability to interpret scans and data faster and more thoroughly than humans. In the end, it will be up to a doctor or radiologist to determine a diagnosis. This occurs even for lower-wage jobs, similar to gardening, care work, and plumbing.

Myth #3: You Need Data Scientists and Huge Budgets to Use AI for the Business

Reality: Many Tools Are Increasingly Available to Business Users and Don’t Require Google-Sized Investments

Some artificial intelligence applications require Ph. D.s and computational linguists to handle the hard lifting; nevertheless, a rising number of artificial intelligence software solutions are becoming more accessible to commercial users. On one hand, the use of artificial intelligence requires a deep understanding of programming languages and sophisticated techniques. On the other, artificial intelligence is becoming increasingly accessible.

Hiring a data scientist is no longer necessary. Between salary and stock options, a “typical” artificial intelligence specialist makes between $300,000 and $500,000 a year, according to The New York Times. There are now a number of developer tools that are ready to use. A majority of AI-based solutions (such as Matlab and SAS) were over-qualified and extremely expensive in the past. Python now offers feature-rich packages — instead of paying a premium to access those features, you can get them for a fraction of the price.

Reality: Successful Usage of Artificial Intelligence Requires an Equal Amount of Humans and Machines

The use of this technology is rapidly changing, as it now has the ability to complete complex tasks. Despite this, humans must make the correct requests for artificial intelligence to work correctly and to the best of its ability. The development and usage of this technology are not so black and white — it is not 100% machines or 100% humans. Instead, the successful usage of artificial intelligence requires an equal amount of both humans and machinery.

In the case of an example, artificial intelligence has tremendous value to data analysis. This technology can analyze data 1000x faster than a team of analysts. However, in order for artificial intelligence to properly function, humans must enter the correct data and distinctively define the parameters, in which the data is being analyzed.

Reality: Artificial Intelligence Is as Smart as You Program It

“We project onto AI what we would do,” said McCall. “I think the smartest engine on earth is the human brain and we’re not going to build a smarter AI than the human brain. AI isn’t sentient, it isn’t conscious, and I don’t think it will get smarter than us.”

Artificial intelligence does not exist without humans as they are the ones that create the algorithms that make it up. In order to make certain decisions on our behalf, we build it, teach it, and give it the tools needed to do so. Hence, it is useless without humans’ awareness and understanding.

The best summary of artificial intelligence is that it is extremely useful and capable of solving complex problems that humans are not equipped to complete. Machines are faster at certain tasks when they are aided by artificial intelligence. Artificial intelligence can generate superior results in some circumstances when compared to human-made decision matrices. It does so by identifying complex patterns in a large amount of data. However, artificial intelligence does not have the capability to independently perform complex divergent thinking. As a result, it cannot outperform humans.

Due to the exponential growth in artificial intelligence, the progression of this technology is inevitable and will change the way humans employ tools and technology. Instead of believing these misleading myths, consider believing in artificial intelligence.

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