The way we search for information online is severely flawed.

When using Google for searches, the top results primarily consist of paid advertisements. Page rankings are influenced by the prominence of websites, rather than their relevance to our search queries. Furthermore, we are tracked and our personal information retained, including our intimate secrets, which is then sold to advertisers who exploit our vulnerabilities by targeting us incessantly across the internet.

Understanding the Impact of Bias and Censorship
on Our Global Society

In the age of information, we have become heavily reliant on the internet – the digital extension of humanity’s collective knowledge. However, the keys to this treasure trove of information have been monopolized by a handful of tech behemoths, stifling our access and manipulating the data we are allowed to see. The opportunity for data dignity, for an unbiased and uninfluenced engagement with the worldwide web, has been largely a far-off dream. Enter Timpi – a visionary platform that is poised to reorient the scales of power and bring forth an era where access to the web is a dignified and inclusive right, rather than a monopoly-driven privilege.

“The problem with Google is not that it censors conservatives; the problem is that it has the power to determine what content billions of people worldwide will or not see,” Epstein told the Senate Judiciary Subcommittee on the Constitution. 

In his must-watch TEDTalk Andreas Ekström, the Swedish investigative journalist and author of The Google Code, outlines how individuals at Google regularly make manual changes to search engine algorithms based on their own moral code.  

A 2019 Wall Street Journal investigation found that Google favors large businesses in search results, collaborates with governments to censor content and alters the suggested auto-complete search terms to deliver more palatable and less incendiary results. 

Growing awareness as thought leaders and governments call out these antisocial practices.

Deepdive into biased data issues


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