Tag: critical thinking

The Nature of Truth

Where Is the Boundary Between Objectivity and Relativism?

Truth seems like one of the simplest concepts in human life. We expect facts to be accurate, evidence to be reliable, and reality to exist independently of our personal beliefs. Yet history repeatedly shows that what societies once accepted as “truth” has often changed over time.

In today’s digital world, the question has become even more complicated. Scientific discoveries, political polarization, social media algorithms, and artificial intelligence all influence how information is created, shared, and interpreted. As a result, many people no longer ask only “What is true?” but also “Who decides what counts as truth?”

The debate is no longer confined to philosophy classrooms. It now shapes public health, democracy, journalism, education, and everyday decision-making.

1. Objective Truth: Does It Exist?

Facts Beyond Personal Belief

The traditional understanding of truth assumes that certain facts remain true regardless of individual opinion.

Scientific knowledge often illustrates this idea. The Earth orbits the Sun whether or not someone believes it. Water freezes under specific conditions regardless of cultural background. Mathematical principles remain consistent across languages and civilizations.

These examples suggest that objective reality exists independently of human perception.

The Limits of Human Knowledge

However, history reminds us that our understanding of reality evolves.

For centuries, many Europeans believed that Earth was the center of the universe. Only after the work of Copernicus, Galileo, and Kepler did the heliocentric model gradually replace the earlier worldview.

This does not necessarily mean that truth itself changed. Rather, human understanding of truth became more accurate as better evidence emerged.

2. Relativism and the Rise of Multiple Truths

The Postmodern Perspective

Postmodern thinkers argue that many forms of truth depend on language, culture, historical context, and personal experience.

Historical events, works of art, or political movements may be interpreted differently by different societies. A national hero in one country may be remembered very differently elsewhere.

From this perspective, some truths are not simply discovered—they are interpreted.

Social Media and Personalized Reality

Digital technology has amplified this phenomenon.

Recommendation algorithms often present information that reinforces existing beliefs. Over time, people may inhabit entirely different information environments despite living in the same society.

This creates what some researchers call “personalized realities,” where individuals encounter very different versions of the same event.

3. Scientific Evidence and Public Trust

Facts Alone Are Not Always Enough

Scientific consensus depends on evidence, experimentation, and continuous review.

Yet public acceptance depends equally on trust.

Climate change provides a clear example. Although the overwhelming majority of climate scientists agree that human activity contributes significantly to global warming, public opinion varies considerably across countries and political groups.

The debate often reflects differences in trust toward institutions rather than differences in scientific evidence.

When Misinformation Spreads Faster Than Facts

The digital age has made false information easier to create and distribute.

Deepfakes, manipulated images, fabricated quotations, and AI-generated content can appear highly convincing.

Consequently, critical thinking and media literacy have become essential skills for distinguishing credible information from misinformation.

4. Can Artificial Intelligence Recognize Truth?

AI as a Powerful but Imperfect Tool

Generative AI systems can summarize information, answer questions, and create persuasive content within seconds.

However, AI does not independently verify reality. Instead, it predicts likely responses based on patterns found in its training data.

This means AI may confidently produce inaccurate or misleading information when reliable evidence is unavailable or conflicting.

Human Judgment Still Matters

As AI becomes increasingly integrated into education, journalism, and research, human oversight remains essential.

Technology can assist our search for truth, but it cannot replace careful reasoning, ethical responsibility, and evidence-based evaluation.

5. Living With Uncertainty

Seeking Truth Without Absolute Certainty

Perhaps the greatest lesson is that the pursuit of truth requires both confidence and humility.

Scientific inquiry encourages us to follow evidence wherever it leads while remaining willing to revise conclusions when better evidence appears.

Likewise, democratic societies depend on open dialogue, respectful disagreement, and shared standards of evidence rather than unquestioned certainty.

Conclusion

The nature of truth lies at the intersection of objective evidence, human interpretation, and social trust.

Some truths describe the physical world with remarkable consistency. Others involve values, historical interpretation, or cultural meaning, where multiple perspectives naturally coexist.

Rather than choosing between absolute objectivity and complete relativism, modern societies may need to cultivate something more valuable: the ability to evaluate evidence critically while remaining open to new understanding.

In an age shaped by artificial intelligence, social media, and rapidly expanding information, perhaps the greatest challenge is not simply finding the truth—but learning how to recognize it responsibly.

Reader Question

Can any society function without a shared understanding of truth, or is disagreement about reality an unavoidable part of human life?

As artificial intelligence and social media continue shaping how information is created and consumed, what responsibilities do individuals have in verifying what they choose to believe?

Related Reading

If scientific knowledge continues to evolve through new discoveries and changing evidence, can any scientific conclusion ever be considered permanently true?

In Is Scientific Truth Ever Absolute?, we examine how scientific progress continually refines our understanding of reality while balancing certainty with healthy skepticism.

If history can be interpreted differently by different cultures, generations, or political perspectives, does a single historical truth truly exist?

In Is There a Single Historical Truth, or Many Narratives?, we explore how evidence, memory, and interpretation shape competing understandings of the past without abandoning the search for historical accuracy.

07/03/2026
Confirmation Bias in Investing
Why We Believe What We Want to Believe in Financial Markets

Financial markets are oceans of information.

Every day, investors are exposed to earnings reports, economic indicators, analyst opinions, news headlines, social media discussions, and countless predictions about the future.

Yet despite having access to more information than ever before, investors do not always make better decisions.

One reason is a psychological tendency known as confirmation bias.

Confirmation bias is the tendency to seek, interpret, and remember information that supports our existing beliefs while ignoring or dismissing evidence that challenges them.

Although this bias is a natural part of human psychology, it can become a costly trap in investing and financial decision-making.

Understanding confirmation bias is not merely about understanding markets—it is about understanding ourselves.

1. What Is Confirmation Bias?

Confirmation bias occurs when people favor information that reinforces what they already believe.

Rather than objectively evaluating all available evidence, individuals often pay greater attention to information that confirms their expectations.

Imagine an investor who strongly believes a particular company will become a future market leader.

When positive news appears, the investor eagerly shares it and feels increasingly confident.

When negative news emerges, however, it is often dismissed as temporary, exaggerated, or irrelevant.

The investor is not necessarily being irrational on purpose. Human beings naturally seek consistency between their beliefs and the information they consume.

The problem arises when this tendency prevents objective decision-making.

2. How Confirmation Bias Operates in Financial Decisions

Confirmation bias affects investors in several subtle but powerful ways.

Selective Information Gathering

Investors often search for information that supports their existing positions.

For example, someone who owns a technology stock may search for:
- “Why this company will dominate the future”
- “Analysts bullish on the stock”
- “Reasons to buy now”
while avoiding critical reports or bearish analyses.

In the age of algorithms, this tendency becomes even stronger.

Social media platforms, investment communities, and recommendation systems often show users content similar to what they already engage with.

As a result, investors can become trapped inside informational echo chambers.

Selective Interpretation

Even when investors encounter the same data, they may interpret it differently.

Suppose a company reports disappointing quarterly earnings.

An investor who already believes in the company might conclude:

“The long-term outlook is still excellent.”

Another investor may view the same report as evidence of deeper problems.

The data is identical.

The interpretation is not.

The Combination of Confirmation Bias and Loss Aversion

Confirmation bias becomes especially dangerous when combined with loss aversion—the tendency to fear losses more than we value equivalent gains.

When investments decline in value, many investors become emotionally attached to their original decisions.

Rather than accepting that they may have been wrong, they search for information that justifies holding the position.

In some cases, they invest even more money into a losing asset simply to reinforce their original belief.

This behavior can transform a manageable loss into a much larger one.

3. The Hidden Costs of Confirmation Bias

Poor Investment Decisions

When investors ignore contradictory evidence, they are less likely to assess risks accurately.

This can lead to excessive optimism and unrealistic expectations.

Markets often punish overconfidence.

Concentrated Portfolios

Confirmation bias can encourage investors to become overly committed to a particular company, sector, or investment theme.

Believing strongly in a single narrative may reduce diversification and increase vulnerability to market volatility.

Escalating Losses

One of the most damaging consequences occurs when investors refuse to admit mistakes.

Instead of reevaluating their thesis, they continue searching for reasons to remain invested.

The longer this process continues, the larger the potential losses can become.

4. A Lesson from the 2008 Financial Crisis

Confirmation bias affects not only individual investors but also professionals and institutions.

The global financial crisis of 2008 provides a powerful example.

For years, many investors, banks, and financial institutions believed that housing prices would continue rising indefinitely.

Evidence supporting this belief received widespread attention.

Warning signs received far less consideration.

Even as problems in the subprime mortgage market became increasingly visible, many organizations continued relying on models and assumptions that reinforced their existing confidence.

The result was one of the most severe financial crises in modern history.

The lesson is clear:

Intelligence and expertise do not eliminate confirmation bias.

In fact, strong confidence can sometimes make it even harder to recognize.

5. Strategies for Overcoming Confirmation Bias

Although confirmation bias is deeply rooted in human psychology, investors can reduce its influence.

Seek Opposing Views

Before making an investment decision, actively search for the strongest argument against your position.

Instead of asking:

“Why am I right?”

ask:

“What if I am wrong?”

This simple shift can reveal risks that might otherwise be overlooked.

Create Objective Rules

Successful investors often rely on predefined rules rather than emotional reactions.

Examples include:
- Stop-loss thresholds
- Position size limits
- Diversification requirements
- Valuation criteria
Objective frameworks reduce the influence of psychological biases during stressful market conditions.

Keep an Investment Journal

Recording investment decisions can be surprisingly powerful.

Write down:
- Why you entered the investment
- What assumptions you made
- What evidence supported your decision
Later, reviewing these notes can reveal patterns of biased thinking and improve future decision-making.

Welcome Disconfirming Evidence

Many investors view contradictory information as a threat.

The most effective investors often view it as an opportunity.

Information that challenges our beliefs may be uncomfortable, but it is frequently the most valuable information we receive.

Conclusion: The Greatest Opponent May Be Ourselves

Many people believe investing is primarily about understanding companies, markets, and economic trends.

Those things matter.

But successful investing also requires understanding human psychology.

Confirmation bias reminds us that the greatest risks do not always come from market crashes, economic recessions, or unexpected events.

Sometimes they come from our own minds.

The market does not reward what we hope is true.

It responds to reality.

The ability to question our assumptions, seek opposing perspectives, and remain intellectually flexible may be one of the most valuable investment skills of all.

In the end, better investing often begins with a simple realization:

The most important analysis is not only of the market—but of ourselves.

A Question for Readers

Have you ever held onto an investment longer than you should have—not because the evidence supported it, but because you wanted your original decision to be right?

Perhaps the greatest challenge in investing is not predicting the market, but recognizing when our own beliefs are shaping the way we see it.

Related Reading

Financial decisions are shaped not only by data, but also by the way our minds interpret information and construct beliefs. This relationship between human reasoning and the limits of objective judgment is explored further in 0 and 1 in the Age of Artificial Intelligence: The Symbolic Philosophy of the Digital World, which examines how information, logic, and human interpretation interact in an increasingly data-driven world.

At the same time, financial markets often reward those who can question their assumptions and adapt to changing realities. This broader theme of uncertainty, risk, and long-term thinking is further explored in The New Space Age: From Moon Missions to the Rise of the Space Economy, which discusses how major investments in the future require balancing optimism with critical analysis and evidence-based decision-making.

References

1. Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011.

One of the most influential books on human decision-making and cognitive biases. Kahneman explains how mental shortcuts, including confirmation bias, affect judgment in finance, business, and everyday life.

2. Montier, James. The Little Book of Behavioral Investing. John Wiley & Sons, 2010.

This book explores the psychological mistakes investors commonly make, including confirmation bias, overconfidence, and emotional decision-making. It offers practical strategies for becoming a more rational investor.

3. Thaler, Richard H., and Cass R. Sunstein. Nudge: Improving Decisions About Health, Wealth, and Happiness. Penguin Books, 2009.

A landmark work in behavioral economics that demonstrates how human decisions are often influenced by predictable psychological tendencies. The book provides valuable insights into financial behavior and decision-making.

4. Shefrin, Hersh. Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing. Oxford University Press, 2007.

An accessible introduction to behavioral finance that explains how emotions and cognitive biases shape investment outcomes. The book examines many real-world examples from financial markets.

5. Lewis, Michael. The Big Short: Inside the Doomsday Machine. W. W. Norton & Company, 2010.

This bestselling account of the 2008 financial crisis illustrates how widespread confirmation bias and groupthink contributed to one of the largest market failures in modern history.
06/25/2026
Algorithmic Bias: How Recommendation Systems Narrow Our Worldview
1. Do Algorithms Have “Preferences”?

Behind platforms we use every day—YouTube, Netflix, Instagram—are recommendation algorithms working silently.
Their task seems simple: to show content we are likely to enjoy.

The problem is that these recommendations are not neutral.

Algorithms analyze what we click, what we watch longer, and what we like.
Based on these patterns, they decide what to show next.
It is as if a well-meaning but stubborn friend keeps saying,
“You liked this, so you’ll like more of the same.”

2. Filter Bubbles and Echo Chambers

When recommendations repeat similar content, a phenomenon known as the filter bubble emerges.
A filter bubble traps users inside a limited set of information, filtering out alternative views.

For example, if someone repeatedly watches videos supporting a particular political candidate,
the algorithm is likely to recommend more favorable content about that candidate—
while opposing perspectives quietly disappear.

This effect becomes stronger when combined with an echo chamber,
where similar opinions are repeated and amplified.
Like sound bouncing inside a hollow space, the same ideas echo back,
gradually transforming opinions into unshakable beliefs.

3. How Worldviews Become Narrower

Algorithmic bias does more than simply provide skewed information.
- Reinforced confirmation bias: People encounter only ideas that match what they already believe.
- Loss of diversity: Opportunities to discover unfamiliar interests or viewpoints decrease.
- Social fragmentation: People in different filter bubbles struggle to understand one another,
  fueling political polarization and cultural conflict.
Consider someone who frequently watches videos about vegetarian cooking.
Over time, the algorithm recommends only plant-based recipes and content emphasizing the harms of meat consumption.
Eventually, this person may come to see meat-eating as entirely wrong,
leading to friction when interacting with people who hold different dietary views.

4. Why Does This Happen?

The primary goal of recommendation algorithms is not user understanding, but engagement.
The longer users stay on a platform, the more profitable it becomes.

Content that triggers strong reactions—likes, comments, prolonged viewing—gets prioritized.
Since people naturally spend more time on content that aligns with their beliefs,
algorithms “learn” to reinforce those patterns.

In this feedback loop, personalization slowly turns into polarization.

5. How Can We Respond?

Escaping algorithmic bias does not require abandoning technology, but using it more consciously.
- Consume diverse content intentionally: Seek out unfamiliar topics or opposing viewpoints.
- Reset or limit personalized recommendations when platforms allow it.
- Practice critical thinking: Ask, “Why was this recommended to me?” and “What perspectives are missing?”
- Use multiple sources: Check the same issue across different platforms and media outlets.
Conclusion

Recommendation algorithms are powerful tools that efficiently connect us with information and entertainment.
However, when their built-in biases go unnoticed, they can quietly narrow our understanding of the world.

Technology itself is not the enemy.
The real challenge lies in maintaining awareness and balance.

Even in the age of algorithms,
the responsibility to broaden our perspective—and the power to choose—still belongs to us.

A Question for Readers

If algorithms continuously show us only what we already prefer, are they helping us understand the world more clearly—

or quietly limiting the range of perspectives we are able to see?

Related Reading

The cognitive framing power of digital interfaces is examined further in How Search Boxes Shape the Way We Think.

These technical patterns also raise deeper philosophical questions addressed in If AI Can Predict Human Desire, Is Free Will an Illusion?

References
1. Pariser, E. (2011). The Filter Bubble: What the Internet Is Hiding from You.
  This book popularized the concept of the filter bubble, explaining how personalized algorithms limit exposure to diverse information and intensify social division.
2. O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy.
  O’Neil analyzes how algorithmic systems reinforce bias, deepen inequality, and undermine democratic values through real-world examples.
3. Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism.
  This work examines how search and recommendation algorithms can reproduce structural social biases, particularly related to race and gender.
01/22/2026
Algorithmic Bias
How Recommendation Systems Narrow Our Worldview

1. Do Algorithms Have “Preferences”?

We interact with recommendation algorithms every day—on platforms like YouTube, Netflix, and Instagram. These systems are designed to show us content we are likely to enjoy. At first glance, this seems helpful and efficient.

However, the problem lies in the assumption that these recommendations are neutral. They are not.

Algorithms analyze what we click on, how long we watch a video, which posts we like, and what we scroll past. Based on these patterns, they decide what to show us next. Over time, certain interests and viewpoints are repeatedly reinforced.

In effect, the algorithm behaves like a well-meaning but stubborn friend who keeps saying, “You liked this before, so this is all you need to see.”

2. Filter Bubbles and Echo Chambers

As recommendations repeat, a phenomenon known as the filter bubble begins to form. A filter bubble refers to a situation in which we are exposed only to a narrow slice of available information.

For example, if someone frequently watches videos supporting a particular political candidate, the algorithm will prioritize similar content. Gradually, opposing viewpoints disappear from that person’s feed.

When this filter bubble combines with an echo chamber, the effect becomes stronger. An echo chamber is an environment where similar opinions circulate and reinforce one another. Hearing the same ideas repeatedly makes them feel more certain and unquestionable—even when alternative perspectives exist.

3. How Worldviews Become Narrower

The bias built into recommendation systems affects more than just the content we consume.

First, it strengthens confirmation bias. We are more likely to accept information that aligns with our existing beliefs and dismiss what challenges them.

Second, it reduces diversity of exposure. Opportunities to encounter unfamiliar ideas, cultures, or values gradually diminish.

Third, it can intensify social division. People living in different filter bubbles often struggle to understand why others think differently. This dynamic contributes to political polarization, cultural conflict, and generational misunderstandings.

Consider a simple example. If someone frequently watches videos about vegetarian cooking, the algorithm will increasingly recommend content praising vegetarianism and criticizing meat consumption. Over time, the viewer may come to believe that eating meat is unquestionably wrong, making constructive dialogue with others more difficult.

4. Why Does This Happen?

The primary goal of most platforms is not user enlightenment, but engagement. The longer users stay on a platform, the more advertising revenue it generates.

Content that provokes strong reactions—agreement, outrage, or emotional attachment—keeps users engaged for longer periods. Since people tend to engage more with content that confirms their beliefs, algorithms learn to prioritize such material.

As a result, bias is not intentionally programmed in a moral sense, but it emerges structurally from the system’s incentives.

5. How Can We Respond?

Although we cannot fully escape algorithmic systems, we can respond more thoughtfully.
- Consume diverse content intentionally: Seek out topics and perspectives you normally avoid.
- Adjust or reset recommendations: Some platforms allow users to limit or reset personalized suggestions.
- Practice critical reflection: Ask yourself, “Why was this recommended to me?” and “What viewpoints are missing?”
- Use multiple sources: Compare information across different platforms and media outlets.
These small habits can help restore balance to our information diets.

Conclusion

Recommendation algorithms are powerful tools that connect us efficiently to information and entertainment. Yet, if we remain unaware of their built-in biases, our view of the world can slowly shrink.

Technology itself is not the enemy. The challenge lies in how consciously we engage with it. In the age of algorithms, maintaining curiosity, openness, and critical thinking is essential.

Ultimately, even in a data-driven world, the responsibility for perspective and judgment still belongs to us.

A Question for Readers

If algorithms continuously reinforce what we already believe and prefer, are they helping us understand the world more efficiently—

or gradually limiting our ability to encounter different perspectives and ideas?

Related Reading

Technologies originally designed to serve human convenience increasingly shape perception, attention, and behavior.
Do Humans Control Technology explores how technological systems influence modern human life beyond conscious awareness.

Algorithms not only filter information but also shape how reality is categorized and interpreted.
The Power of Naming examines how language and classification influence social understanding and power structures.

References

1. Pariser, E. (2011). The Filter Bubble: What the Internet Is Hiding from You. New York: Penguin Press.
→ This book popularized the concept of the filter bubble, explaining how personalized algorithms can limit exposure to diverse information and deepen social divisions.

2.O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown.
→ O’Neil examines how large-scale algorithms, including recommendation systems, can reinforce bias and inequality under the appearance of objectivity.

3.Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press.
→ This work provides a critical analysis of how algorithmic systems can reproduce social prejudices, particularly regarding race and gender.
01/13/2026
How Search Boxes Shape the Way We Think
The Invisible Influence of Algorithms in the Digital Age

Every day, billions of questions begin with a search box.

We type a few words,
receive suggestions,
and follow links that appear almost instantly.

But what if the search box is shaping our thoughts
before we even finish the question?

1. When Search Boxes Decide the Question

Search boxes do more than provide answers.
They subtly change the way we ask questions in the first place.

Think about autocomplete features.
You begin typing “today’s weather,” and before finishing, the search box suggests
“today’s weather air pollution.”

Without intending to, your attention shifts.
You were looking for the weather, but now you are thinking about air quality.

Autocomplete does not simply predict words.
It redirects thought.
Questions that once originated in your mind quietly become questions proposed by an algorithm.

2. How Search Results Shape Our Thinking

Search results are not neutral lists.
They are ranked, ordered, and designed to capture attention.

Most users focus on the first page—often only the top few results.
Information placed at the top is easily perceived as more accurate, reliable, or “true.”

For example, when searching for a diet method, if the top results emphasize dramatic success,
we tend to accept that narrative, even when contradictory evidence exists elsewhere.

In this way, search results do not merely reflect opinions.
They actively guide the direction of our thinking.

3. The Invisible Power Behind the Search Box

At first glance, a search box appears to be a simple input field.
Behind it, however, lie powerful algorithms shaped by commercial and institutional interests.

Sponsored content often appears at the very top of search results.
Even when labeled as advertisements, users unconsciously associate higher placement with credibility.

As a result, companies invest heavily to secure top positions,
knowing that visibility translates directly into trust and choice.

Our decisions—what we buy, read, or believe—are often influenced
long before we realize it.

4. Search Boxes Across Cultures and Nations

Search engines differ across countries and cultures.
Google dominates in the United States, Naver in South Korea, Baidu in China.

Searching the same topic on different platforms can yield strikingly different narratives,
frames, and priorities.

A historical event, for instance, may be presented through contrasting lenses depending on the search environment.

We do not simply search the world as it is.
We see the world through the window our search box provides—and each window has its own tint.

5. Learning to Question the Search Box

How can we avoid being confined by algorithmic guidance?

The answer lies in cultivating critical habits:
- Ask whether an autocomplete suggestion truly reflects your original question
- Look beyond the top-ranked results
- Compare information across platforms and languages
These small practices widen the intellectual space in which we think.

Conclusion

Search boxes are not passive tools for finding answers.
They shape questions, guide attention, and quietly train our ways of thinking.

In the digital age, the challenge is not to reject these tools,
but to use them without surrendering our autonomy.

True digital literacy begins when we recognize
that the most powerful influence of a search box
lies not in the answers it gives,
but in the questions it encourages us to ask.

A Question for You

Have you ever searched for something—and felt the results were guiding your thinking?

If what you see is filtered,
how much of your thinking is truly your own?

Related Reading

The invisible filtering mechanisms behind everyday searches are explored further in
Algorithmic Bias: How Recommendation Systems Narrow Our Worldview, where digital systems subtly shape what we see and how we interpret information.

The fragility of human perception goes even deeper in
If Memory Can Be Manipulated, What Can We Really Trust?,
which examines how memory itself can be altered, raising fundamental questions about truth, identity, and reality.

Digital participation is not shaped by citizens alone; it is also shaped by the systems that guide attention.
This issue is further explored in Clicktivism in Digital Democracy: Participation or Illusion?, where online political action is examined as both a new form of participation and a possible substitute for deeper engagement.

References

Pariser, E. (2011). The Filter Bubble: What the Internet Is Hiding from You. New York: Penguin Press.
→ Explores how personalized algorithms narrow users’ worldviews while shaping perception and judgment.

Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York: NYU Press.
→ Critically examines how search engines reflect and amplify social biases rather than remaining neutral tools.

Beer, D. (2009). Power through the Algorithm? New Media & Society, 11(6), 985–1002.
→ Analyzes algorithms as invisible forms of power that structure everyday cultural practices.
01/03/2026