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Spot, Boston Dynamics' robot dog, has joined a police squad
The semiautonomous could help to protect officers, but some are concerned about how exactly police plan to use it.
- Spot is a four-legged, semiautonomous robot developed by Boston Dynamics.
- The robot has been used in at least two police "incidents," according to documents obtained by the ACLU.
- The ACLU said that government agencies should be more transparent about how they plan to use robots in the field.
Spot, the robot dog from Boston Dynamics, is working with a police squad
Massachusetts State Police (MSP) has used Spot — it's four-legged and semiautonomous — in at least two police "incidents," according to documents obtained by the American Civil Liberties Union of Massachusetts.
The documents, first reported by Ally Jarmanning at WBUR in Boston, describe Spot as a "mobile remote observation device" that is an "invaluable component of tactical operations" for state police, but they don't elaborate on the two "incidents" in which the robot was involved. In September, Boston Dynamics began leasing Spot to companies that might benefit from having a robot helper in the field: construction firms, oil, and gas companies, etc.
In dangerous police situations, Spot could help officers identify the location of suspects or bombs, sense hazardous gases and inspect suspicious packages.
"Robot technology is a valuable tool for law enforcement because of its ability to provide situational awareness of potentially dangerous environments," state police spokesman David Procopio wrote in the documents. Spot's features include:
- Top speed: 3 mph
- Average runtime: 90 minutes
- Carrying capacity: 30 pounds
- 360-degree, low-light camera
- Extendable arm
Mass. State Police got to use @BostonDynamics’ Spot the robot dog for three months this year. That’s raising questi… https://t.co/XtOtCqh8U0— ally jarmanning (@ally jarmanning)1574685158.0
What Spot isn't equipped with is a weapon: Boston Dynamics vice president for business development Michael Perry told WBUR that the agreement with MSP included a clause that Spot cannot be used to "physically harm or intimidate people."
"Part of our early evaluation process with customers is making sure that we're on the same page for the usage of the robot," he said. "So upfront, we're very clear with our customers that we don't want the robot being used in a way that can physically harm somebody."
Still, some have expressed concern over the lack of transparency and regulations in police departments using autonomous robots.
Is using robot police dogs worth the risks?
Police departments in the U.S. have used robot helpers for years. In 2016, Dallas officers used a robot loaded with explosives to kill the man who murdered five police officers during a protest, in what was the first time a police robot has been used to kill a suspect. No charges were filed against the officers behind the controls of that police robot.
However, with new technology comes new concerns about how exactly officers will employ semiautonomous robots in the field.
"There is a lot we do not know about how and where these robotics systems are currently deployed in Massachusetts," Kade Crockford, Technology for Liberty program director at the ACLU of Massachusetts, told Gizmodo via email.
In addition to weaponization, Crockford said it's possible for police departments to use Spot with other technologies, for purposes such as surveillance.
"We just really don't know enough about how the state police are using this," Crockford told WBUR. "And the technology that can be used in concert with a robotic system like this is almost limitless in terms of what kinds of surveillance and potentially even weaponization operations may be allowed."
Boston Dynamics said the agreement with MSP is its only "public safety-focused relationship to date," and that robots like Spot can help save officers' lives.
"Sending a nimble robot like Spot into these situations can remove humans from potentially life-threatening environments and provide emergency responders with better situational awareness of a crisis," the company's staff wrote in an email to Gizmodo. "These are the same capabilities that oil and gas, electric utility, nuclear decomissioning [sic] and mining customers will use to perform critical safety inspections without exposing people to risk."
In a statement to TechCrunch, Crockford said that the public "urgently need[s] more transparency from government agencies, who should be upfront with the public about their plans to test and deploy new technologies."
- New A.I. police car brings us one step closer to Robocop - Big Think ›
- If Your Robot Commits Murder, Should You Go to Jail? - Big Think ›
A Mercury-bound spacecraft's noisy flyby of our home planet.
- There is no sound in space, but if there was, this is what it might sound like passing by Earth.
- A spacecraft bound for Mercury recorded data while swinging around our planet, and that data was converted into sound.
- Yes, in space no one can hear you scream, but this is still some chill stuff.
First off, let's be clear what we mean by "hear" here. (Here, here!)
Sound, as we know it, requires air. What our ears capture is actually oscillating waves of fluctuating air pressure. Cilia, fibers in our ears, respond to these fluctuations by firing off corresponding clusters of tones at different pitches to our brains. This is what we perceive as sound.
All of which is to say, sound requires air, and space is notoriously void of that. So, in terms of human-perceivable sound, it's silent out there. Nonetheless, there can be cyclical events in space — such as oscillating values in streams of captured data — that can be mapped to pitches, and thus made audible.
Image source: European Space Agency
The European Space Agency's BepiColombo spacecraft took off from Kourou, French Guyana on October 20, 2019, on its way to Mercury. To reduce its speed for the proper trajectory to Mercury, BepiColombo executed a "gravity-assist flyby," slinging itself around the Earth before leaving home. Over the course of its 34-minute flyby, its two data recorders captured five data sets that Italy's National Institute for Astrophysics (INAF) enhanced and converted into sound waves.
Into and out of Earth's shadow
In April, BepiColombo began its closest approach to Earth, ranging from 256,393 kilometers (159,315 miles) to 129,488 kilometers (80,460 miles) away. The audio above starts as BepiColombo begins to sneak into the Earth's shadow facing away from the sun.
The data was captured by BepiColombo's Italian Spring Accelerometer (ISA) instrument. Says Carmelo Magnafico of the ISA team, "When the spacecraft enters the shadow and the force of the Sun disappears, we can hear a slight vibration. The solar panels, previously flexed by the Sun, then find a new balance. Upon exiting the shadow, we can hear the effect again."
In addition to making for some cool sounds, the phenomenon allowed the ISA team to confirm just how sensitive their instrument is. "This is an extraordinary situation," says Carmelo. "Since we started the cruise, we have only been in direct sunshine, so we did not have the possibility to check effectively whether our instrument is measuring the variations of the force of the sunlight."
When the craft arrives at Mercury, the ISA will be tasked with studying the planets gravity.
The second clip is derived from data captured by BepiColombo's MPO-MAG magnetometer, AKA MERMAG, as the craft traveled through Earth's magnetosphere, the area surrounding the planet that's determined by the its magnetic field.
BepiColombo eventually entered the hellish mangentosheath, the region battered by cosmic plasma from the sun before the craft passed into the relatively peaceful magentopause that marks the transition between the magnetosphere and Earth's own magnetic field.
MERMAG will map Mercury's magnetosphere, as well as the magnetic state of the planet's interior. As a secondary objective, it will assess the interaction of the solar wind, Mercury's magnetic field, and the planet, analyzing the dynamics of the magnetosphere and its interaction with Mercury.
Recording session over, BepiColombo is now slipping through space silently with its arrival at Mercury planned for 2025.
Research suggests that aging affects a brain circuit critical for learning and decision-making.
As people age, they often lose their motivation to learn new things or engage in everyday activities. In a study of mice, MIT neuroscientists have now identified a brain circuit that is critical for maintaining this kind of motivation.
Researchers develop the first objective tool for assessing the onset of cognitive decline through the measurement of white spots in the brain.
- MRI brain scans may show white spots that scientists believe are linked to cognitive decline.
- Experts have had no objective means of counting and measuring these lesions.
- A new tool counts white spots and also cleverly measures their volumes.
White spots and educated guesses<p>The white spots, or "hyperintensities," are brain lesions—fluid-filled holes in the brain believed to have been left behind by the breaking down of blood vessels that had previously provided nourishment to brain cells.</p><p>Prior to the new research, the quantity of white spots was assessed using an imprecise three-point scale indicating ascending likelihoods of dementia: A minimal number of spots was considered as level 1, a medium number of spots level 2, and a great number of them level 3.</p>
How the new measurements were derived<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDYwMTc1OS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYzNDQ1ODExNX0.vqhQJSvL99KjOe24TOs4E8R7c6-pprbXYSrGcIqbVps/img.jpg?width=980" id="c64d9" class="rm-shortcode" data-rm-shortcode-id="002d9b8ef47b5a86c3a387ad2cd90629" data-rm-shortcode-name="rebelmouse-image" />
Credit: sfam_photo/Shutterstock<p>The team of researchers from NYU's Langone's <a href="https://med.nyu.edu/departments-institutes/neurology/divisions-centers/center-cognitive-neurology" target="_blank">Center for Cognitive Neurology</a> and <a href="https://med.nyu.edu/departments-institutes/neurology/divisions-centers/center-cognitive-neurology/alzheimers-disease-research-center" target="_blank">Alzheimer's Disease Research Center</a> were led by <a href="https://med.nyu.edu/faculty/jingyun-chen" target="_blank">Jingyun "Josh" Chen</a>. They analyzed 72 MRI scans from a national database of older people taken as part of the <a href="http://adni.loni.usc.edu" target="_blank">Alzheimer's Disease Neuroimaging Initiative</a> (ADNI). The scans were mostly of white people over age 70, and there were a roughly equivalent number of men and women. Some had normal brain function, some were presenting moderate cognitive decline, and some had severe dementia.</p><p>Without knowing each individual's diagnosis, the researchers analyzed the white spots in their scans. While the team counted each scan's lesions, the innovation they introduced was the production of a 3D measurement for each lesion's fluid volume. The measurement was derived by measuring a lesion's distance from opposite sides of the brain.</p><p>Measurements of 0 milliliters (mL) were assessed for areas without white spots, with other white spots coming up as containing 60 mL of fluid. Chen's team predicted that volumes over 100 mL could signify severe dementia.</p><p>"Amounts of white matter lesions above the normal range should serve as an early warning sign for patients and physicians," Chen told <a href="https://nyulangone.org/news/white-matter-lesion-mapping-tool-identifies-early-signs-dementia" target="_blank">NYU Langone Health NewsHub</a>.</p><p>When the team compared the likely diagnoses derived from their calculations against the individuals' medical records, they found that their predictions were correct about 7 out of 10 times.</p><p>The researchers compiled their formulas into an online tool that's available to physicians for free via <a href="https://github.com/jingyunc/wmhs" target="_blank" rel="noopener noreferrer">GitHub</a>. The researchers plan to further refine and test it using an additional 1,495 brain scans representing a more diverse group of individuals from the ADNI database.</p>