Motivation

Growing up, I read a lot of news. As a kid, I read at least two newspapers in two different languages every day, pouring over politics and sports sections, mostly. I expected news to be informational, but in some cases, news articles could also be biased. So, a best practice is reading from multiple sources to give different perspectives

During our past presidential election when I read about Macedonian teenagers operating a “fake news factory” to affect the elections in United States, I was bothered. When I read about what it feels like to subscribe to fake news, I was very disturbed. I saw what happened when Facebook disastrously attempted to curate news. I have also seen what happens in Reddit’s news threads during the height of election season. I didn’t like what was happening in the news industry. I don’t want a future where news is dictated by agenda, rather than facts.

Real and factual news matter because they inform people about current events. Factual news helps us make informed decisions that affect us — our families, our future, the economy, our culture — and the kind of world we live in. If a guy like me, with a degree in Computer Science is struggling to find factual and unbiased news of current events, it must be especially hard for someone who trusts the news, i.e., my friend’s 75-year-old grandma in Ohio interested in keeping up with immigration policies or my neighbor’s nephew in Michigan actively trying to learn about our political parties and their principles as a high school student. Good information should be easy to find. Bad information should be flagged. Journalists or news sources intent on practicing either should be distinguished. That determination of “good” and “bad” information should be done impartially based on facts, patterns and not political bias or personal agendas. Since developing technologies to help people has always been my mission, it seemed this was a timely problem I wanted to solve.

While on my Christmas holiday, I started experimenting with a few news articles that seemed at first blush to be biased to me. I wasn’t positive of their bias – it was just a hunch. As I did more tests – words, phrasing, set up, tone, etc., – I realized I was on to something. If a source is indeed biased, then a pattern appears. I wanted to expose that pattern. As a computer scientist, I knew I could do this through machine learning — a type of artificial intelligence providing computers with the ability to learn without being explicitly programmed to do so. The more I refined this new resource, I felt it critical to implement it and make it available for general use. A little over a month later, I released Trusted Times.

Trusted Times is free for use. There are expenses involved with website/domain and app server hosting, but I consider that just part of my contribution to society. Trusted Times is an informational accessory for adults and an excellent education tool for young kids who want to learn how to read news effectively and analytically.

I made Trusted Times for that 75-year-old grandma from Ohio who can now get a more transparent analysis of any news article she reads. I made Trusted Times for the teachers like the ones in Seattle who are teaching their students how to read news and process information accurately. If Trusted Times can help anyone, then all my hard work will be worth it.

Disclaimer – this is my personal project and my employer isn’t involved in any shape or form. Nor do I have backing from any third party or group.