knowledge filters revisited

The concept of filtering sources of knowledge has informed the personal knowledge mastery framework for many years, as explained here in knowledge filters (2011). Recently, a “CBC News investigation found that a YouTube channel devoted to putting misleading headlines on TV stories from other stations is getting recommended more often than many mainstream news outlets.” Given the current general election in Ontario, this could be a concern for our democratic processes. But the real culprit is that our society — especially elected officials, educators, and businesses — has done little to promote real media literacy. We need better information, knowledge, and opinion filters, and nobody will give them to us. We have to create them ourselves.

Let’s review the five types of filters that Tim Kastelle so kindly shared in 2010.

I will start with Machine Filters, since this is what Google/YouTube are providing when you search for a video about the Ontario election. First of all the Algorithmic filters are based on invisible algorithms, as determined by YouTube to increase your watching time. Secondly, these are coupled with Heuristic filters that promote any video that gets strong reactions and keeps people on the platform, so there is a greater chance for them to be exposed to more advertising. Given that most platforms are driven by advertising technology (adtech), most Machine filters are skewed in favour of sensational items. Additionally, as these platforms track everything you do online, you will get more of what you like, not what is more accurate or truthful. One way to guard against this type of tailored information is to use a search engine that does not track people, like DuckDuckGo or StartPage.

Now let’s look at Human Filters. Expert filtering was the basis of the last economy, with expert opinions in newspapers, on the radio, and on television. Today’s reality shows that almost all of the experts have flawed perspectives and some are trying to influence opinion based on falsehoods, usually with money or influence as a motivator. Therefore we need to filter information from diverse networks of people with a variety of perspectives, knowledge, expertise, and opinions. This type of filtering is the most difficult, at the onset. But if we take the time to set up these filters, we have a better chance of the seeing the world for what it is, and not what advertisers, political influencers, and platforms monopolists want us to see.

One way to set up these filters is to follow a diverse group of people on Twitter. Let’s say you follow two commentators from each of the parties. Sprinkle in a few more that you disagree with for good measure. Then add some reputable sources. Read all of them and make up your mind. Over time you can refine this list. You can create a list for every election and for every field of interest you like. This will make you a more informed citizen.

You can do the same with a Feed Reader, like Feedly or InoReader, and subscribe to a variety of sources. These of course will likely be longer reads so you want to be discriminating in your selections so that it does not become a place where nothing is ever read. Other sources of opinions and ideas are podcasts, which are great for people who like to listen while exercising, commuting, or doing chores. Many national broadcasters have a wide variety of free podcasts, e.g. http://www.cbc.ca/radio/podcasts/

So the next time you search for something important, don’t let the platform monopolists like Google decide what is best for you.

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