The algorithm year: How AI and platforms quietly changed our daily life
This was the year algorithms stopped assisting and started deciding.
There was no announcement. No warning. No deadline. Yet somewhere between scrolling, clicking, submitting, and swiping, we quietly handed over pieces of daily life to machines that do not vote, feel, or explain themselves.
This was the year algorithms stopped assisting and started deciding.
They decide who gets work, what students learn or skip, which news survives the feed, whose creativity is worth paying for. And they do it silently.
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When software starts setting the rules
Across offices and freelance marketplaces, people are being measured by systems they will never see and cannot question.
A designer wakes up to fewer clients. A freelancer's profile suddenly sinks. An employee's performance score drops without explanation.
There is no supervisor to argue with. No HR desk to appeal to. Only a dashboard, a metric, a recalculation.
In a country where job security is already fragile, algorithms now sit between survival and silence. They reward speed, availability, compliance. They punish hesitation, nuance, and humanity.
We are told this is "efficiency." But efficiency without accountability is simply power without responsibility.
Personalised learning or quiet standardisation?
Students are no longer just studying, they are outsourcing thought. Assignments are summarised before they are understood. Answers appear before questions fully form. Learning bends toward shortcuts, because the system rewards outcomes, not struggle.
In overcrowded classrooms and under-resourced institutions, AI feels like relief. But relief can become dependence. And dependence, over time, becomes erosion.
An education system that teaches students how to use tools but not how to doubt them, produces graduates who are fast, confident, and dangerously uncritical.
When the algorithm becomes the editor
Most of the news consumers no longer "go" to the news. News comes to them, through Facebook feeds, YouTube recommendations, and Google Discover alerts.
What rises to the top is not always what matters most, but what performs best. Crime clips travel faster than policy explainers. Emotional headlines beat complex reporting. Algorithms reward reaction, not reflection.
Newsrooms feel this pressure every day. Editors must now balance public interest with platform logic. The result is a media environment where visibility is increasingly outsourced to systems owned by foreign tech companies, beyond the reach of local regulation.
When algorithms decide what the public sees, editorial independence quietly weakens.
Faster, cheaper, and less valued
Writers, designers, videographers, people who once sold skill and imagination, now compete with prompts and presets.
Clients ask for more, pay less, and expect instant delivery. Why wait, when software can generate something "good enough"?
Creativity has not died. It has been devalued. And when creativity becomes disposable, culture follows.
Why this needs policy attention now
Bangladesh has ambitious plans for a smart Bangladesh. But smart systems without oversight create silent power imbalances.
Right now:
Workers do not know how algorithms assess them. Students are using AI without clear academic guidelines. News visibility depends on platform rules, not public interest. Creators face automation without protection or recognition.
This is not a call to ban AI or not to use AI. It is a call to stop pretending these systems are neutral.
What we need is, Transparency standards for algorithmic decision-making. Clear AI guidelines in education and workplaces. Platform accountability for news distribution. Recognition and protection for human creative labour. Most importantly, we need a public conversation.
The algorithm year did not arrive with noise. That is exactly why it matters. Because the biggest changes are no longer announced, they are installed, accepted, and normalised.
And by the time we notice, the rules have already changed.
