W3W maintains that their algorithm keeps similar combinations “so far apart that an error is obvious. We also worked hard to remove homophones and near homophones like sale and sail.” They rate the the chance of two confusing combinations appearing close enough to be unclear at about 1 in 2.5 million. But in a new analysis of the algorithm, currently in preprint, computer scientist Rudy Arthur argues that despite W3W’s claims this chance of confusion is far higher, and warns against adopting W3W as critical infrastructure (it’s used by emergency services, particularly in the U.K.) without testing and comparing against available alternatives. [The Register]

Previously: What3Words Hasn’t Had the Greatest Couple of Months: A Roundup.

It’s also been the subject of several parodies, including what3emojis (emojis instead of words), Four King Maps (four swear words, UK and Ireland only on account of a lack of swear words, which frankly disappoints me) and Maps Mania’s own April Fool’s joke for this year, what2figures, which expresses any point on the globe in just two numbers (I’ll wait).

But more recently it’s come under criticism for having similar sounding word combinations for addresses only a few miles apart: see Andrew Tierney’s blog post (which expands upon this Twitter thread) and What3words’s response. This is especially a problem for first responders trying to locate someone who may have misspoken or mistyped their location, or because of their accent, resulting in rescue teams being sent to the wrong location.

Previously: New York Times: How Location Data Is Gathered, Shared and Sold.

In this case the problem was traced to the National Geospatial-Intelligence Agency, which assigned the lat/long coordinates for Pretoria to this family’s front yard. The end result: one home becomes the location for one million IP addresses in Pretoria. (The NGA has since changed it.)

The problem here is twofold. First, a failure to account for accuracy radius: a city or a country is represented by a single, precise point at its centre. That’s a real problem when the data point being geotagged can’t be more specific than “Pretoria” or “United States,” because the geotagging is made artificially precise: it’s not “somewhere in Pretoria,” it’s this specific address. Second is the misuse of IP location data. It’s one thing to use a web visitor’s IP address to serve them local ads or to enforce geographical restrictions on content, quite another to use that data for official or vigilante justice. The data, Hill points out, isn’t good enough for that. [MetaFilter]

Previously: A Geolocation Glitch Creates a ‘Technological Horror Story’.

Previously: Strava Heat Map Reveals Soldiers’ Locations; Non-Anonymized Strava User Data Is Accessible; Strava, Responding to Security Concerns, Disables Features; Polar Flow User Data Can Be Used to Identify Military and Intelligence Personnel.

For the last decade, Taylor and her renters have been visited by all kinds of mysterious trouble. They’ve been accused of being identity thieves, spammers, scammers and fraudsters. They’ve gotten visited by FBI agents, federal marshals, IRS collectors, ambulances searching for suicidal veterans, and police officers searching for runaway children. They’ve found people scrounging around in their barn. The renters have been doxxed, their names and addresses posted on the internet by vigilantes. Once, someone left a broken toilet in the driveway as a strange, indefinite threat.

As Hill’s article points out, Taylor is far from the only one to be hit by this problem. MaxMind is updating its database to correct this and one other case by moving the default location to a body of water. (I can’t help but think that we will soon start hearing stories about people driving into the lake as a result of this change.) There’s no such thing as a set of coordinates that can’t be represented precisely. What’s the solution?