Tech company Seekr Technologies has launched the beta of its search engine that uses machine learning to give users control over what they read on the internet.
According to Seekr, it wants its userbase to start making educated decisions on the type of content they consume and will teach this via a scoring system to indicate an article’s quality. There are currently two scoring methods at play: a Seekr Score and Political Lean Indicator, with more to come in the future.
Seekr compares its system to a consumer rating system, like Consumer Reports. It’s a way to educate the public on the news by serving as a platform showing what it considers good reporting versus bad.
The Seekr Score analyzes the article based on how good the information is and how closely it sticks to journalistic practices. For example, Seekr rates articles based on objectivity, clickbait, personal attacks, and incoherence, which refers to how much the title clashes with the article.
The Political Lean Indicator does the same, while also showing an article’s political lean. A small icon shows whether what you’re about to read leans left-wing, right-wing, or centrist. The website even informs people if the source has any personal connection to the story.
Seekr states that it wants to better the reputation of online reporting and have users see all sides of an argument so they can make informed decisions rather than be swayed by an algorithm.
In the future, the company plans to include ad-supported searching that points to the brand’s connection to the story.
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