Secretive Alphabet division aims to fix public transit in US by shifting control to Google (from The Guardian)
Documents reveal Sidewalk Labs is offering a system it calls Flow to Columbus, Ohio, to upgrade bus and parking services – and bring them under Google’s management.
The emails and documents show that Flow applies Google’s expertise in mapping, machine learning and big data to thorny urban problems such as public parking. Numerous studies have found that 30% of traffic in cities is due to drivers seeking parking.
Sidewalk said in documents that Flow would use camera-equipped vehicles,…. It would then combine data from drivers using GoogleMaps with live information from city parking meters to estimate which spaces were still free. Arriving drivers would be directed to empty spots.
Source: Secretive Alphabet division aims to fix public transit in US by shifting control to Google
Notice that this gives Google/Alphabet a legitimate reason to track every car in the downtown area. Flow can be even more helpful if they know the destination of every car AND every traveler for the next hour.
The next logical step, a few years from now, will be to track the plans of every person in the city. For example Mary Smith normally leaves her house in the suburbs at 8:15AM to drive to her office in downtown Columbus. Today, however, she has to drop off daughter Emily (born Dec 1, 2008, social security number 043-xx-xxxx) at school, so she will leave a little early. This perturbation in normal traffic can be used to help other drivers choose the most efficient route. Add together thousands of these, and we can add real-time re-routing of buses/ Uber cars.
For now, this sounds like science fiction. It certainly contains the ability to improve transit efficiency and speed, and “make everyone better off.” But it comes at a price. Yet many are already comfortable with Waze tracking their drives in detail.
Tune back in 10 years from now and tell me how I did.
The Lindbergh Foundation’s Air Shepherd initiative uses drones to catch poachers in South Africa.
My comment: Flying at night, up to 40km away, is technically difficult. But smart autopilots, using GPS and accelerometers, mean that the operators (pilots) don’t have to do hands-on flying except landing and takeoff. Probably every component in the system except the ground vehicles is hobbyist level, although some of the specialized long-range radio gear might need to be hand built. Nothing from aerospace companies. Battery powered, so essentially noiseless. Also, the aircraft itself is the cheapest part of the system.
The article mentions flights of “up to 4 hours.” That is a very long duration, and would require lots of batteries. 2 hours or even less sounds more realistic. Efficient cruising speed is probably is probably around 40 kph (25 mph). If anyone finds other discussions of this project, please let me know.
Source: Drones Hunt Down Poachers in South Africa | Flying Magazine
Separating historical truth from myth is as hard in science as anywhere else. This article has several examples, including whether Darwin got his ideas from someone else, and a dispute about whether Semmelweis was really ignored after his discovery of the link between hand-washing and disease.
Semmelweiss teaches doctors to wash their hands c 1850 – it is still an issue today
The Hamblin article [about a supposed misplaced decimal point], unscholarly and unsourced, would become the ultimate authority for all the citations that followed. (Hamblin graciously acknowledged his mistake after Sutton published his research, as did Arbesman.)
In 2014, a Norwegian anthropologist named Ole Bjorn Rekdal published an examination of how the decimal-point myth had propagated through the academic literature. He found that bad citations were the vector. Instead of looking for its source, those who told the story merely plagiarized a solid-sounding reference: “(Hamblin, BMJ, 1981).” Or they cited someone in between — someone who, in turn, had cited Hamblin. This loose behavior, Rekdal wrote, made the transposed decimal point into something like an “academic urban legend,” its nested sourcing more or less equivalent to the familiar “friend of a friend” of schoolyard mythology. Source: Who Will Debunk The Debunkers? | FiveThirtyEight
I found a similar myth about aviation checklists. It’s a myth that they were invented because of the crash of a B-17 bomber prototype in 1935. The first B-17 checklist was in 1937, and by then many Navy aircraft had more complete checklists. Including one published before the 1935 crash.
As far as I could tell when I researched this, the B-17 checklist story was first told in a 1965 book by Edward Jablonski. Since then the myth has been passed from article to article to book, such as Atul Gawande’s generally excellent book, Checklist. The crash did happen, but checklists were invented independently of it.
Many years ago I wrote a popular (for an academic) article, “Measuring and Managing Technological Knowledge.” The basic idea is that some concepts are well understood, many others are not, and over time the tendency is to move from poorly understood (crafts) to well understood (science). Anyway, in class I used the example of romance to prove that this model is very general. “When you were 14, you had absolutely no idea how to impress a girl. When you were 20, you at least knew what the key variables are, even though you didn’t know how to make them happen reliably.” Etc. (Another example is the increasingly scientific business of prostitution – but I won’t tell that one here, and I doubt I had courage to tell it in class.)
Why do we follow digital maps into dodgy places? Something is happening to us. Anyone who has driven a car through an unfamiliar place can attest to how easy it is to let GPS do all the work. We have come to depend on GPS, a technology that, in theory, makes it impossible to get lost. Not only are we still getting lost, we may actually be losing a part of ourselves. Source: Death by GPS | Ars Technica
As usual, aviation is way “ahead.” Use of automated navigation reduces pilots’ navigation skills; automated flight reduces hand-flying skills. Commercial aviation is starting to grapple with this, but there is no easy solution.
This article describes the efforts of Facebook, Youtube, and similar hosts of user-generated content, to screen unacceptable material. (Both speech and images.) It’s apparently a grim task, because of the depravity of some material. For the first decade, moderation methods were heavily ad hoc, but gradually grew more complex and formalized in response to questions such as when to allow violent images as news. In aviation terms, it was at Stage 2: Rules + Instruments. Now, some companies are developing Stage 3 (standard procedures) and Stage 4 (automated) methods.
Proving self-driving cars are safe could take up to hundreds of years under the current testing regime, a new Rand Corporation study claims. Source: Self-driving cars may not be proven safe for decades: report The statistical analysis in this paper looks fine, but the problem is even worse for aircraft (since they are far safer per mile than autos.) Yet new aircraft are sold after approx 3 years of testing, and less than 1 million miles flown. How?
From the report:
we will show that fully autonomous vehicles would have to be driven hundreds of millions of miles and sometimes hundreds of billions of miles to demonstrate their reliability in terms of fatalities and injuries. Under even aggressive testing assumptions, existing fleets would take tens and sometimes hundreds of years to drive these miles.
How does the airline industry get around the analogous statistics? By understanding how aircraft fail, and designing/testing for those specific issues, with carefully calculated specification limits. They don’t just fly around, waiting for the autopilot to fail!