THE MOST COMMON MISCONCEPTIONS ABOUT AI TO AVOID IN 2021

Artificial intelligence (AI) has been one of the most debated subjects in recent years. While AI is gaining popularity as its applications and capabilities expand, there are still many confusions. Like what AI is and what it can do.

Since there are so many concepts and variants of AI in the news and media, business leaders and entrepreneurs are often perplexed about what AI can do for their company. With artificial intelligence (AI) finding its way into the workplace, it is critical to know where AI can add value to your company where it cannot.

Common Misconceptions about Artificial Intelligence

Machines are capable of self-learning.

That is how you get the impression. Machines are not yet at the point that they can make their own choices about what they can do with themselves. Moreover, the decisions they do make are the product of much human effort upstream.

Experts must still formulate the problem, prepare the models, select suitable training data sets, remove possible biases introduced by these data, etc. The programme must then be adjusted based on its efficiency. Countless human brain hours are still needed for AI models to work.

Machines have a purpose ( they are objective).

The opposite could not be further from the facts. After all, hardware design and software programming are both human creations. The impartiality of the datasets that are submitted to the training model determines objectivity in machine learning.

Since cognitive bias is almost unavoidable, the most challenging aspect of data preparation is minimising it as often as possible. A model often reproduces a confirmation bias passed down from its human founders — garbage in, garbage out, as they say.

Machine learning and AI are the same things.

While it is undeniable that machine learning is at the core of almost all current AI applications, the concept of machine learning, or the principle that machines can learn and adapt through experience, is just one of AI’s tools. Possibly one day, we will find new ways for solving problems that are not manageable to machine learning, such as those for which vast volumes of eligible data are unavailable.

AI refers to a broader term in which computers can perform tasks in an “intelligent” manner, i.e., identical functions to human intelligence.

However, still, there is no universally accepted definition of AI, and its boundaries are hazy. It would be more apt to refer to it as “complex information processing” or “cognitive automation,” but that would be less interesting.

AI would eliminate employment.

It will be more realistic to assume that AI innovations would eliminate some workers while transforming others, as was the case with automation and robotisation in recent decades.

To put it another way, AI will fundamentally alter the nature of employment, much as prior industrial revolutions did. However, it will not likely result in a reduction in the total number of workers. Similarly to how robotisation enabled the elimination of repetitive manual tasks, AI eliminates repetitive intellectual tasks, freeing up the capacity to function in a new and more intelligent manner.

Moreover, like robotisation, AI has the potential to be more effective than humans at some tasks. Consider an AI-based application for studying lung X-rays to detect the disease even more quickly and accurately than radiologists.

AI may not be helpful in my company.

Are you certain? AI can now optimise customer experiences, interpret data more quickly, assist in decision-making, and produce early alerts of impending disruptions, among other things.

Why should you deny yourself this pleasure? It also has numerous industrial uses, such as computer vision/recognition, which helps it identify a faulty component much more quickly and rapidly than a human operator.

Ignoring AI is akin to ignoring the advantages of automation at the expense of the company’s competitiveness. AI is merely a conceptual continuation of the automation/robotisation movement of the industrial revolution.

Super-intelligent machines would surpass human intelligence.

AI applications today are highly context-oriented, meaning they adapt to particular problems. Generalised intelligence, such as human or natural intelligence, capable of tackling a wide range of tasks, is still on the horizon and belongs in science fiction. However, back in 1865, moon travel was still considered science fiction.

Although we cannot claim with certainty that AI will not ultimately surpass humans, we believe we can confidently state that super-robots will not be able to surpass humans in all areas within our lifetimes.

Summing-up

Artificial intelligence (AI) is difficult to comprehend since it is riddled with misconceptions and inaccuracies. However, since AI is destined to become a part of our everyday lives, we must learn more about its underlying technologies and challenges to make informed decisions about it as business decision-makers, policymakers, advocates, or customers.

Whether we intend to accept the truth in these misconceptions or not, AI is here to stay. In truth, Forrester forecasts a 300 per cent rise in total investment in AI technology this year alone. Companies can make use of the power of intelligent automation to streamline processes and provide a competitive advantage by confronting and solving the most common AI misconceptions.