A Web of Lies (and Truths)
I really like serendipitously stumbling onto two thematically intertwined articles, as I just did. In this case, it was Charles Cooke’s Aldous Huxley and the Mendacious Memes of the Internet Age, and this:
“An unexciting truth,” Huxley noted in Brave New World Revisited, “may be eclipsed by a thrilling falsehood,” especially in such circumstances as that truth’s being disseminated across a medium that is “concerned in the main neither with the true nor the false, but with the unreal, the more or less totally irrelevant.” When we speak warmly of the Web and its consequences, we imagine that rationality will inevitably prevail. Often, we imagine in vain. Have we been liberated? Or have we been drowned?
So, are we doomed to mendacity and stupidity on the web? And that’s where the second piece, this one from David Amerland, comes into play. For in this piece, How Google Learns to ‘See’ the Truth, David outlines what Google is doing to improve the quality of news and other information on the web.
Google is going upstream to verify trustworthy sources, but as David points out, the company might very well use those signals to then assess who forwards and shares these (and less trustworthy material) in their social media streams.
It’s interesting not just at a macro, societal level, but in a direct, applied sense too. Ignore what Google’s doing here, and you risk harming your reputation over the long haul.
“The web is becoming a more truth-orientated place. Just like in the real world, trust takes a long time to develop and is easily lost. If you’re incorporating news sources, video, Tweets or other primary sources of data in your content or sharing activity, being able to verify their provenance is a necessary skill.”
“Before you share content from sources you’re not familiar with, you will also have to do your own due diligence to make sure that they’re current and can be trusted, otherwise their mistakes will affect your reputation.”
Another point that David makes is how important individuals are to establishing trustworthy information:
“As an aside, this also shows the weakness of the current stage of development of machine learning. Unless there is a sufficient volume of data for algorithms to work with and begin to organize it into patterns that allow inferences such as “true” or “false” to be made, a human is still better at understanding the context of a piece of information that is entirely new.”
Some of you may already be aware of what Google is doing on the “Knowledge-Based Trust” machine-learning front, but it’s clear that the company can’t afford to rely solely on that strategy.
More on Knowledge-Based Trust:
Knowledge-Based Trust and the Future of Search and Artificial Intelligence
#trust #knowledge #journalism