Debunking the most common AI myths

ARTIFICIAL INTELLIGENCE CAN’T BE TRUSTED, shouts the headline on your social media newsfeed.

Is that really true, or is it a myth?

Like many people, you’ve probably wondered if such claims are overblown. After all, you’ve likely seen at least some of the Hollywood blockbusters in which, after various AI breakthroughs, intelligent machines are enslaving humanity, with no hope of people ever regaining control.

And those movies were years ago.

Now, AI solutions, being proposed for all sorts of real-world use cases, and the digital transformation they’ve heralded, have progressed considerably. They’ve reached the point at which international organizations are trying to regulate the boundaries of artificial intelligence to ward off a host of existing and potential perils. The godfather of AI has ominously left Google and warned us about the risks that using AI poses to our existence as a species. And oh, by the way, is your job safe?

Despite all the unknowns about the different types of AI, it (particularly generative AI) has still captured public minds and hearts in a huge way, and its advancements have already transformed entire industries, with considerably more upheaval to come.

So it’s only natural that this initial era in the evolution of AI has also given rise to numerous myths and misconceptions.

If you’re an online business owner who knows that AI holds both huge promises and scary risks, you may feel ambivalent about the technology. Your rational human brain knows you don’t want your business to get left behind, but you also don’t want to get caught up in the hype, if that’s mostly what it is.

So what should you do?

The only sensible answer is to get more information by digging deeper to find out what’s really going on. To truly understand AI’s capabilities and limitations in the digital arena, you have to be able to separate fiction from fact. Then you’re in a better position to make well-informed decisions about how you might — or might not — choose to utilize AI for the financial well-being of your organization.

Why debunk the myths?

Myths create barriers to adoption

Common myths about AI can evoke fear and skepticism, which may hinder its adoption across global workforces. For example, the myth that AI steals jobs can lead to employees resisting integration of its technologies. So debunking such myths can alleviate much of the fear and open up opportunities to harness AI within companies.

Clear understanding means informed decisions

Dispelling myths allows individuals and organizations to make decisions that aren’t based on misconceptions.

Take, for example, a healthcare provider that’s hesitant to adopt AI, as management is unsure whether its benefits are worth the investment. When the team understands that AI can handle tasks such as patient data analysis and predictive diagnostics, which could improve patient care and operational efficiency, they may be more likely to embrace it as a tool for enhancing their human ingenuity.

It can make people feel less defensive

Because one contributor to the perpetuation of myths is fear, understanding the capabilities of AI and realizing the ways in which it’s not a threat to jobs or safety can take the edge off of thinking and discussions about the technology and improve how human beings work alongside machines.

Consider the field of finance, for instance. AI technology can process and analyze large volumes of market data at speeds unattainable by humans. However, human financial analysts are typically needed to interpret analyses to ascertain market conditions, apply ethical considerations, and make nuanced decisions. And this synergy between humans and machines can improve a company’s performance in a variety of ways.

AI myths to keep in mind

With AI taking center stage, it’s vital to debunk the most prevalent myths that are only growing more prevalent on office floors, in corporate boardrooms, and throughout international organizations. Ten of the most prevalent myths include:

Myth 1: AI is out for your job

Does obsessing about AI making off with your livelihood keep you up at night? Do you worry that there won’t be a new job out there if you’re laid off (or, let’s be paranoid here, fired for poor performance because you’re not as good as a robot)?

Well, close your eyes and turn over, as the reality with this one is slightly more complex and less dire.

You should know that AI’s role in the workplace is often that of a collaborator. These new technologies are particularly effective at automation of routine and repetitive tasks such as data entry.

In the field of marketing, for example, AI supplies the computing power to process and analyze large volumes of consumer data, identifying trends and insights. This can free marketing professionals from the burden of mind-numbing data crunching; they can then turn their attention to developing creative strategies and making data-driven decisions.

The transition to AI signifies a shift toward job evolution, not elimination. Many companies are aware of this fact; as PWC points out, 70% of business decision makers believe AI will help employees focus on doing meaningful work.

So there’s one reason to sleep more soundly. Here are a few more:

Myth 2: AI is biased

The myth of artificial intelligence being inherently biased represents a misunderstanding of the nature of AI systems, but given some reports lately, it is easy to see why this is the case. Bias in AI often stems from the data it is trained on, such as the particular large language model. For example, if an AI-based recruitment tool is fed historical data that contains gender or racial biases, the AI is naturally going to be likely to replicate these biases in its hiring suggestions.

So is AI going to remain biased? Not likely, say experts. With careful selection and processing of training data, and by incorporating mechanisms to detect and correct biases, AI can actually help reduce human bias in decision-making. This does involve a conscious human effort to use diverse, representative data and  continuously monitor and adjust AI systems, but by doing so, businesses can create fairer and more equitable AI systems.

Myth 3: AI and machine learning (ML) are the same

One myth of AI is that it and machine learning (along with deep learning) are interchangeable. In reality, they represent related but different concepts in the field of computer science. And understanding the distinction between them is key to effectively implementing them at work.

AI is the broader category, encompassing any technique that enables machines to mimic human intelligence. This includes reasoning, learning, problem solving, perception, and language understanding. AI applications range from simple, rule-based systems like chatbots to complex decision-making frameworks used in autonomous vehicles.

Machine learning, on the other hand, is a specific subset of AI focused on the development of algorithms that can learn and make decisions based on data. An example of ML in action is a recommendation system on an ecommerce platform like Target’s, which suggests relevant upsell products based on the shopper’s viewing history.

Myth 4: AI is only for companies with deep pocket

Only the superintelligence tech gods of data science manipulating Big Data, such as Amazon, Apple, and Google — those with infinite budgets and whole departments of data scientists —  can afford to harness the benefits of AI. Right?

Wrong. The democratization of AI technology has made it accessible and affordable for businesses of all sizes. An example: organizations can easily use ChatGPT and DALL-E neural network technology even if they don’t have a budget to invest massively in AI.

In addition, small and medium-sized enterprises are putting AI into practice for a variety of applications. For instance, customer-service chatbots are being widely used by smaller businesses to enhance shopper interaction and customer-service efficiency. Similarly, tools for content creation, market analysis, and automated administrative tasks are being effectively utilized by businesses that have limited resources.

Myth 5: AI can think like humans

While many popular science-fiction films and TV shows portray robots acting and thinking as humans might, AI can’t yet do this. According to Erik J. Larson,  an expert in natural language processing (NLP) and the author of The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do (2021), the futurists are incorrect in asserting that the human mind will soon be left in the dust by AI.

AI functionality workflows are based largely on algorithmic processing and data analysis, which is starkly different from human cognition. AI’s capabilities, though advanced, are confined to the realm of what it’s been programmed to do.

For example, when AI performs tasks like language translation and playing chess, it’s not exhibiting human thinking processes based on AI research. No, it’s only processing vast amounts of data and following predefined AI algorithms. It excels in pattern recognition and data-driven decision-making but falls short in areas requiring emotional depth or contextual judgment, such as when a shopper has a problem and the interaction with the company’s support requires human understanding and expressions of empathy.

Myth 6: AI learns on its own

Contrary to popular belief, AI does not possess the ability to learn entirely independently. Human intervention is a critical component in the development and operation of AI systems. This process begins with initial setup: humans define the problem, select suitable algorithms, and prepare the data, which often involves extensive cleaning and labeling of information to ensure data quality and relevance.

The role of humans extends to continuous tuning and adjustment, too. For instance, if an AI model for fraud detection starts producing false positives, it’s the responsibility of human engineers to identify and rectify the issues in order to ensure the effectiveness of the AI model. Plus, humans must ensure that AI operates and learns within the ethical, legal, and technical boundaries established by humans.

Myth 7: AI has no problem interpreting “messy” data

The idea that AI can effortlessly interpret unstructured data is a misconception. In reality, AI’s effectiveness largely depends on the quality of the data it processes. Well-organized, clean data is a must for AI to operate accurately and efficiently.

For instance, in the healthcare industry, an AI system used for diagnosing diseases from looking at medical images requires high-quality, accurately labeled data. If the input is inconsistent, incomplete, or poorly annotated, the AI performance can significantly drop. This can lead to the need for substantial human effort in data preprocessing to make it suitable for AI analysis.

Myth 8: AI is difficult to use

The perception that AI is inherently challenging to implement is becoming less accurate as AI technology evolves. Today’s AI platforms are designed with user friendliness in mind; they feature intuitive interfaces that cater to users who don’t have extensive technical backgrounds.

Right now, marketing professionals, who may not have in-depth technical knowledge, are routinely using AI tools for customer segmentation and campaign analysis. This shift toward more-accessible AI enables professionals in diverse fields to leverage capabilities, enhancing productivity and innovation without specialized AI training.

Myth 9: AI will take over the world

The question of whether AI will take over the planet is more aligned with the world of Hollywood and B movies than with our current reality. AI technology is largely specialized and designed for specific tasks; it’s far from possessing the general autonomous intelligence required for global dominance.

Moreover, the development and deployment of AI is increasingly being guided by ethical and regulatory frameworks. Initiatives like the EU AI Act are setting standards and guidelines for responsible use, aiming to prevent harmful consequences.

Myth 10: Your company doesn’t need AI

“Why do I need AI?”

Maybe you’ve asked yourself that and not gotten a clear answer.

The common-sense truth is, of course, that every company, government body, and industry can probably benefit from AI to at least some degree. Businesses inclined to overlook AI’s potential may lag behind in an increasingly competitive and technology-driven market. Adopting AI can lead to better customer insights, enhanced efficiency, and improved decision-making, among other positive outcomes.

In ecommerce, for example, current AI applications are massively enhancing the shopper experience through tailored marketing strategies and personalized product recommendations that can boost engagement and sales. And government organizations are leveraging AI for public-service delivery, using it to analyze large datasets for policy making, streamline processes, and engage citizens.

Truth or consequences

If this information alleviates even some of your fears about AI, we’re glad it’s a help, as our goal is to improve the effectiveness of website search, and feeling comfortable with the technology is the first step.

Our AI-powered search can help you deliver better customer experiences through understanding shoppers’ needs, driving up your customer engagement and boosting your revenue. If you want confirmation, ask our 17,000 successful customers.

Ready to put the myths about AI to rest and start taking advantage of it? Get in touch and let’s start strengthening your bottom line today.

About the authorVincent Caruana

Vincent Caruana

Senior Digital Marketing Manager, SEO

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