5 Common Misconceptions About Algorithms and What They Really Do
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Many people hold incorrect assumptions about algorithms. This article explores five common misconceptions about artificial intelligence and its algorithms.
Algorithms are deeply embedded in our daily lives. They power search engines, recommend products, analyze data, and support decisions in a wide range of areas. Despite their ubiquity, there are still many misunderstandings and false expectations about what algorithms can and cannot do. This article addresses five of the most common misconceptions and explains what is actually behind them.
Misconception 1: “The algorithm hates me”
A widely held belief is that an algorithm can intentionally act against a person. We often hear phrases like “the algorithm hates me” on social media when posts receive less visibility than expected. This implies a conscious or emotional decision, which algorithms are not capable of making.
An algorithm is a mathematical process that makes decisions or generates recommendations based on available data. If a post gets little reach, it is because the algorithm deems it less relevant to the goal it was designed to pursue. On social media platforms, this goal is usually to show content that is likely to interest as many users as possible. Low visibility is not a sign of hostility, but rather the result of data-based evaluation toward a specific programmed outcome.
Misconception 2: “The algorithm decides everything”
Another misconception is the belief that an algorithm acts as an independent decision-maker. Statements like “that’s up to the algorithm” often ignore the fact that human choices are behind every algorithm. People define the goals an algorithm should pursue, the data it may use, and the parameters it evaluates. This also applies to more advanced AI systems. While these systems may identify patterns through machine learning, the direction and goal of their learning are predefined. In practice, when a system provides a recommendation, that outcome is always based on a specific goal and the data it has been given. Final responsibility still lies with humans.
Misconception 3: “Algorithms are always objective”
Another common belief is that algorithms are inherently neutral or objective. In reality, the perceived neutrality of an algorithm depends heavily on the data it uses. If that data is biased, incomplete, or skewed, then the results will reflect those flaws. In research, this is referred to as bias. This issue became especially clear in several studies on facial recognition, which found that AI systems were significantly more accurate when identifying white men than people of color. The reason was the composition of the training data, which overrepresented certain features. Many of these systems were trained predominantly with images of white men, white women and people of color were underrepresented. As a result, the algorithms learned to recognize some faces better than others, which in the worst cases led to discriminatory or inaccurate outcomes.
A 2018 investigation by the American Civil Liberties Union (ACLU) found that Amazon’s facial recognition software misidentified 28 members of the US Congress as individuals with criminal records, with people of color being disproportionately affected. Similar findings from the MIT Media Lab showed that error rates for Black women reached as high as 34 percent, while for white men, the error rate remained below one percent.
These examples highlight a broader issue. Unequal data distribution can produce discriminatory or unreliable outcomes in many contexts. Algorithms are not inherently fair or objective. They are a reflection of the data they are trained on.
Misconception 4: “If I understand the algorithm, I can outsmart it”
Some believe that if they understand how an algorithm works, they can manipulate it. This idea is especially common in the field of search engine optimization. In the early days of SEO, many website operators tried to manipulate Google’s algorithm to achieve higher rankings in search results. These so-called black hat SEO methods included overusing keywords, hiding text on websites, or purchasing backlinks. While these tactics sometimes led to short-term success, Google quickly improved its algorithms to detect and penalize such behavior. Many sites lost their rankings and with them, their visibility and credibility.
The better approach is to focus on transparency, relevance, and long-term value. Those who work with the algorithm instead of against it will achieve more sustainable results. This means creating high-quality content, structuring data carefully, and aligning algorithmic goals with their own strategic objectives. In the end, everyone benefits when systems are used in a fair and understandable way.
Misconception 5: “Algorithms run on their own without maintenance”
Another common belief is that once an algorithm is set up, it will continue to function reliably without any further effort. Like any other technical solution, algorithms require maintenance and adaptation. Data evolves, user behavior changes, and surrounding conditions shift over time. An algorithm that was trained on data from two years ago may no longer be suitable for current use cases.
This is particularly true in dynamic environments such as e-commerce or finance, where continuous review and adjustment are essential. A 2023 study by McKinsey showed that CALCULATE NOW THE ROI OF QYMATIX PREDICTIVE SALES SOFTWARE
Conclusion: How to use algorithms to your advantage
Algorithms are not mysterious forces. They are precise tools created to pursue a clear goal. They operate on data, rules, and mathematical logic defined by humans. Those who understand how they function and what they are designed to achieve can use them to their benefit.
In social media, the goal of an algorithm is usually to keep users engaged on the platform as long as possible. That means it prioritizes content considered interesting, relevant, or engaging. To work effectively with such an algorithm, you need to create content that matches those criteria, capturing attention and encouraging interaction.
Search engines like Google follow a different but equally clear goal. Their mission is to help users find the best and most relevant information as quickly as possible. To be visible there, you need content that provides real value, meets the intent behind search queries, and builds trust. Attempts to trick the system may deliver short-term gains but often lead to long-term setbacks in visibility and credibility.
The key to making the most of algorithms is to understand their logic. Only by knowing what an algorithm aims to achieve can you align with it and make it work in your favor. This knowledge helps improve visibility, boost efficiency, and support smarter decisions. It is not blind trust that makes algorithms valuable, but informed and responsible use.