Harold Jarche rightly points to being able to judge and shape your information filters as a critical element in keeping yourself informed about emergent crises like Covid19. What Harold calls trusted filters is the primary reason I follow people not sources in my feeds, and all of those people are selected by myself, not by someone else’s algorithm. It is how I came across Harold’s post in the first place, because he’s been in my list of feeds for many years. Feedback across filters, so that what Harold shares might get commented here, which then gets shared back to my network which includes Harold, is how patterns emerge. This of course does mean you need to ensure your filter has enough variety and churn to avoid echo chambers. Which is why hand curating my list of people to follow is important, I know these people and what I know about them is an active part of the filtering I do. In my mind, the combination of my filtering and sharing, and Harold’s filtering and sharing as well as those of others I follow, constitute a LOFAR, which is able to spot small movements and emerging interests across my networks, and recognising which noises are actually signals to my interests and concerns. Keeping my LOFAR in good working order requires regular attention, and likely more than I already pay to it.

This doesn’t mean that institutional information isn’t valuable. It is actually invaluable. Institutions are the stock of info, the residue of years of knowledge, where my networks and filters are the flow, the reflection on, application, changing and emergence of knowledge. Such knowledge is critical for crap detection, also when it comes to the stuff my network shares with me. In times of emergent crises like Covid19, such institutional knowledge about how to deal with the specifics of e.g. a pandemic is crucial. So I keep an eye on the general statistics collected at John Hopkins, the advise and info of the RIVM (the Dutch national institute for health and environment, in charge of epidemic response) concerning the Netherlands specifically, and what e.g. the WHO says about pandemic response on a personal level and organisational level (e.g. business continuity). My LOFAR in turn allows me to sense what is going on across my networks in this context.

The LOFAR ‘superterp’ in Drenthe, which has hundreds of small antennas, combining with 47 other locations into a total of some 20.000 antennas for signal detection

Abraham Lincoln famously said in the 1860’s “Don’t believe everything you read on the internet.“, and he’s right of course. George Washington already warned us a century earlier that “the greatest thing about Facebook is that you can quote something and totally make up the source.” Add to it the filter bubbles that algorithms create around you on Facebook, fake news and the influencing that third parties try to do, and you can be certain that the trustworthiness of internet is now even worse than it was in the 19th or 18th century.

Sidewalk Stencil: Abraham Lincoln
“Don’t believe everything you read on the internet.”, Abraham Lincoln hit the nail on the head in 1864 already.

Dealing with crap on the internet however sometimes seems something only for professionals. Facebook should filter better, or be more transparent. Online forensic research like Bellingcat does is the only way to disprove online deception. The problem is that it absolves you and me way too easily of our own responsibility in detecting crap. If something seems too funny, coincidental or too conveniently fitting into your own believe framework, it should trigger us into taking a step back. To take time to determine for ourselves whether Lincoln really said that, whether a picture was really taken where and when it is claimed, and if a source really exists or can be determined as trustworthy.

To be able to detect crap on the internet, you need crap detection tools. My Brainstorms-friend Howard Rheingold and others have put together a useful list of crap detection tools (of which I very often use the reverse image search tools like Tineye, to verify the actual origin of a photo). The list is well maintained and growing. The listed tools help you quickly check-up on things before you share something and reinforce a vicious cycle making more and more social media platforms toxic.

Not spreading dubious material is a civic duty, just like cleaning up after yourself in a public space. This makes crap detection a critical digital information skill. Download or bookmark the list of crap detection tools, add some of the mentioned tools as plugins to your browser, and use it to your advantage.

fake-news-detail-2