RideAlong is helping police officers de-escalate 911 calls with data designed for the field

RideAlong keeps people in mind, and that’s a good thing. The company, founded by Meredith Hitchcock (COO) and Katherine Nammacher (CEO), aims to make streets safer, not with expansive surveillance systems or high-tech weaponry but with simple software focused on the people being policed. That distinction sounds small, but it’s surprisingly revelatory. Tech so oftens […]

RideAlong keeps people in mind, and that’s a good thing. The company, founded by Meredith Hitchcock (COO) and Katherine Nammacher (CEO), aims to make streets safer, not with expansive surveillance systems or high-tech weaponry but with simple software focused on the people being policed. That distinction sounds small, but it’s surprisingly revelatory. Tech so oftens forgets the people that it’s ostensibly trying to serve, but with RideAlong they’re front and center.

“The thing about law enforcement is they are interacting with individuals who have been failed by the rest of society and social support networks,” Nammacher told TechCrunch in an interview. “We want to help create a dialogue toward a more perfect future for people who are having some really rough things happen to them. Police officers also want that future.”

Ridealong is specifically focused on serving populations that have frequent interactions with law enforcement. Those individuals are often affected by complex forces that require special care — particularly chemical dependence, mental illness and homelessness.

“I think it is universally understood if someone has a severe mental illness… putting them through the criminal justice system and housing them in a jail is not the right thing to do,” Nammacher said. For RideAlong, the question is how to help those individuals obtain long-term support from a system that isn’t really designed to adequately serve them.

Made for field work, RideAlong is a mobile responsive web app that presents relevant information on individuals who frequently use emergency services. It collects data that might otherwise only live in an officer’s personal notebook or a police report, presenting it on a call so that officers can use it to determine if an individual is in crisis and if they are, the best way to de-escalate their situation and provide support. With a simple interface and a no-frills design, RideAlong works everywhere from a precinct laptop to a smartphone in the field to a patrol car’s dash computer.

Nammacher explains that any police officer could easily think of the five people they interact with most often, recalling key details about them like their dog’s name and whether they are close to a known family member. That information is very valuable for responding to a crisis but it often isn’t accessible when it needs to be.

“They’ve come up with some really smart manual workarounds for how to deal with that,” Nammacher says, but it isn’t always enough. That real-time information gap is where RideAlong comes in.

How RideAlong works

RideAlong is designed so that police officers and other first responders can search its database by name and location but also by gender, height, weight, ethnicity and age. When a search hits a result in the system, RideAlong can help officers detect subtle shifts from a known baseline behavior. The hope is that even very basic contextual information can provide clues that mean a big difference in outcomes.

So far, it seems to be working. RideAlong has been live in Seattle for a year, with the Seattle Police Department’s 1,300 sworn officers using the software every day. Over the course of six months with RideAlong, Seattle and King County saw a 35% reduction in 911 calls. That decrease, interpreted as a sign of more efficient policing, translated into $407,000 in deferred costs for the city.

“It really assists with decision making, especially when it comes to crisis calls,” Seattle Police Sergeant Daniel Nelson told TechCrunch. Officers have a lot of discretion to do what they think is best based on the information available. “There is so much gray space.”

Ridealong has also partnered with the San Francisco Department of Public Health where a street medicine team is putting it to use in a pilot. West of Seattle, Kitsap County Sheriff’s Office is looking at RideAlong for its team of 300 officers.

What this looks like in practice: An officer responds to a call involving a person they known named Suzanne. They might remember that normally if they ask her about Suzanne’s dog it calms her down, but today it makes her upset. Rather than assuming that her agitated behavior is coming out of the blue, the responding officer could address concerns around Suzanne’s dog and help de-escalate the situation.

In another example, an officer responds to someone on the street who they perceive to be yelling and agitated. Checking contextual information in RideAlong could clarify that an individual just speaks loudly because they are hard of hearing, not in crisis. If someone is actually agitated and drawing helps them calm down, RideAlong will note that.

“RideAlong visualizes that data, so when somebody is using the app they can see, ‘okay this person has 50 contacts, they’ve been depressed, sad, crying,’” Nelson said. “Cops are really good at seeing behavior and describing behavior so that’s what we’re asking of them.”

The idea is that making personalized data like this easy to see can reduce the use of force in the field, calm someone down and open the door to connecting them social services and any existing support network.

“I’ve known all along that we’ve got incredible data, but it’s not getting out to the people on the streets,” said Maria X. Martinez, Director of Whole Person Care at San Francisco Department of Public Health. RideAlong worked directly with her department’s street medicine on a pilot program that gave clinicians access to key data while providing medical care in to the city’s homeless population.

Traditionally, street medicine workers go do their work in the field and return to look up the records for the people they interacted with. Now, those processes are combined and 15 different sets of relevant data gets pulled together and presented in the field, where workers can add to and annotate it. “It’s one thing to tell people to come back and enter their data… you sort of hope that that does happen,” Martinez said. With RideAlong, “You’ve already done both things: documented and given them the info.”

Forming RideAlong

The small team at RideAlong began when the co-founders met during a Code for America fellowship in 2016. They built the app in 2016 under the banner of a data-driven justice program during the Obama administration. Interest was immediate. The next year, Nammacher and Hitchcock spun the project out into its own company, became part of Y Combinator’s summer batch of startups and by July they launched a pilot program with the entire Seattle police department.

Neither co-founder planned on starting a company, but they were inspired by what they describe as a “real-time information gap” between people experiencing mental health crises and the people dispatched to help them and the level of interest from “agencies across the country, big and small” who wanted to buy their product.

“There’s been more of a push recently for quantitative data to be a more central force for decision making,” Nammacher said. The agencies RideAlong has worked with so far like how user friendly the software is and how it surfaces the data they already collect to make it more useful.

“At the end of the day, our users are both the city staff member and the person that they’re serving. We see them as equally valid and important.”

RideAlong is helping police officers de-escalate 911 calls with data designed for the field

RideAlong keeps people in mind, and that’s a good thing. The company, founded by Meredith Hitchcock (COO) and Katherine Nammacher (CEO), aims to make streets safer, not with expansive surveillance systems or high-tech weaponry but with simple software focused on the people being policed. That distinction sounds small, but it’s surprisingly revelatory. Tech so oftens […]

RideAlong keeps people in mind, and that’s a good thing. The company, founded by Meredith Hitchcock (COO) and Katherine Nammacher (CEO), aims to make streets safer, not with expansive surveillance systems or high-tech weaponry but with simple software focused on the people being policed. That distinction sounds small, but it’s surprisingly revelatory. Tech so oftens forgets the people that it’s ostensibly trying to serve, but with RideAlong they’re front and center.

“The thing about law enforcement is they are interacting with individuals who have been failed by the rest of society and social support networks,” Nammacher told TechCrunch in an interview. “We want to help create a dialogue toward a more perfect future for people who are having some really rough things happen to them. Police officers also want that future.”

Ridealong is specifically focused on serving populations that have frequent interactions with law enforcement. Those individuals are often affected by complex forces that require special care — particularly chemical dependence, mental illness and homelessness.

“I think it is universally understood if someone has a severe mental illness… putting them through the criminal justice system and housing them in a jail is not the right thing to do,” Nammacher said. For RideAlong, the question is how to help those individuals obtain long-term support from a system that isn’t really designed to adequately serve them.

Made for field work, RideAlong is a mobile responsive web app that presents relevant information on individuals who frequently use emergency services. It collects data that might otherwise only live in an officer’s personal notebook or a police report, presenting it on a call so that officers can use it to determine if an individual is in crisis and if they are, the best way to de-escalate their situation and provide support. With a simple interface and a no-frills design, RideAlong works everywhere from a precinct laptop to a smartphone in the field to a patrol car’s dash computer.

Nammacher explains that any police officer could easily think of the five people they interact with most often, recalling key details about them like their dog’s name and whether they are close to a known family member. That information is very valuable for responding to a crisis but it often isn’t accessible when it needs to be.

“They’ve come up with some really smart manual workarounds for how to deal with that,” Nammacher says, but it isn’t always enough. That real-time information gap is where RideAlong comes in.

How RideAlong works

RideAlong is designed so that police officers and other first responders can search its database by name and location but also by gender, height, weight, ethnicity and age. When a search hits a result in the system, RideAlong can help officers detect subtle shifts from a known baseline behavior. The hope is that even very basic contextual information can provide clues that mean a big difference in outcomes.

So far, it seems to be working. RideAlong has been live in Seattle for a year, with the Seattle Police Department’s 1,300 sworn officers using the software every day. Over the course of six months with RideAlong, Seattle and King County saw a 35% reduction in 911 calls. That decrease, interpreted as a sign of more efficient policing, translated into $407,000 in deferred costs for the city.

“It really assists with decision making, especially when it comes to crisis calls,” Seattle Police Sergeant Daniel Nelson told TechCrunch. Officers have a lot of discretion to do what they think is best based on the information available. “There is so much gray space.”

Ridealong has also partnered with the San Francisco Department of Public Health where a street medicine team is putting it to use in a pilot. West of Seattle, Kitsap County Sheriff’s Office is looking at RideAlong for its team of 300 officers.

What this looks like in practice: An officer responds to a call involving a person they known named Suzanne. They might remember that normally if they ask her about Suzanne’s dog it calms her down, but today it makes her upset. Rather than assuming that her agitated behavior is coming out of the blue, the responding officer could address concerns around Suzanne’s dog and help de-escalate the situation.

In another example, an officer responds to someone on the street who they perceive to be yelling and agitated. Checking contextual information in RideAlong could clarify that an individual just speaks loudly because they are hard of hearing, not in crisis. If someone is actually agitated and drawing helps them calm down, RideAlong will note that.

“RideAlong visualizes that data, so when somebody is using the app they can see, ‘okay this person has 50 contacts, they’ve been depressed, sad, crying,’” Nelson said. “Cops are really good at seeing behavior and describing behavior so that’s what we’re asking of them.”

The idea is that making personalized data like this easy to see can reduce the use of force in the field, calm someone down and open the door to connecting them social services and any existing support network.

“I’ve known all along that we’ve got incredible data, but it’s not getting out to the people on the streets,” said Maria X. Martinez, Director of Whole Person Care at San Francisco Department of Public Health. RideAlong worked directly with her department’s street medicine on a pilot program that gave clinicians access to key data while providing medical care in to the city’s homeless population.

Traditionally, street medicine workers go do their work in the field and return to look up the records for the people they interacted with. Now, those processes are combined and 15 different sets of relevant data gets pulled together and presented in the field, where workers can add to and annotate it. “It’s one thing to tell people to come back and enter their data… you sort of hope that that does happen,” Martinez said. With RideAlong, “You’ve already done both things: documented and given them the info.”

Forming RideAlong

The small team at RideAlong began when the co-founders met during a Code for America fellowship in 2016. They built the app in 2016 under the banner of a data-driven justice program during the Obama administration. Interest was immediate. The next year, Nammacher and Hitchcock spun the project out into its own company, became part of Y Combinator’s summer batch of startups and by July they launched a pilot program with the entire Seattle police department.

Neither co-founder planned on starting a company, but they were inspired by what they describe as a “real-time information gap” between people experiencing mental health crises and the people dispatched to help them and the level of interest from “agencies across the country, big and small” who wanted to buy their product.

“There’s been more of a push recently for quantitative data to be a more central force for decision making,” Nammacher said. The agencies RideAlong has worked with so far like how user friendly the software is and how it surfaces the data they already collect to make it more useful.

“At the end of the day, our users are both the city staff member and the person that they’re serving. We see them as equally valid and important.”

The FDA OK’d an app as a form of birth control

Don’t want to get pregnant? There’s a Food and Drug Administration approved app for that. The FDA has just given the go ahead for Swedish app Natural Cycles to market itself as a form of birth control in the U.S. Natural Cycles was already in use as a way to prevent pregnancy in certain European […]

Don’t want to get pregnant? There’s a Food and Drug Administration approved app for that. The FDA has just given the go ahead for Swedish app Natural Cycles to market itself as a form of birth control in the U.S.

Natural Cycles was already in use as a way to prevent pregnancy in certain European countries. However, this is the first time a so-called ‘digital contraceptive’ has been approved in America.

The app works using an algorithm based on data given by women using the app such as daily body temperature and monthly menstrual cycles. It then calculates the exact window of days each month a woman is most fertile and therefore likely to conceive. Women can then see which days the app recommends they should avoid having sex or use protection to avoid getting pregnant.

Tracking your cycle to determine a fertile window has long been used to either become pregnant or avoid conceiving. However, Natural Cycles put a scientific spin on the age-old method by evaluating over 15,000 women to determine its algorithm had an effectiveness rate with a margin of error of 1.8 percent for “perfect use” and a 6 percent failure rate for “typical use.”

What that means is almost two in every 100 women could likely conceive on a different date than the calculated fertile window. That’s not exactly fool-proof but it is higher than many other contraceptive methods. A condom, for instance, has an 18 percent margin of error rate, according to the Centers for Disease Control (CDC).

And though the app makers were able to convince the FDA of its effectiveness, at least one hospital in Stockholm has opened an investigation with Sweden’s Medical Products Agency (MPA) after it recorded 37 unwanted pregnancies among women who said they had been using the app as their contraception method.

“Consumers are increasingly using digital health technologies to inform their everyday health decisions, and this new app can provide an effective method of contraception if it’s used carefully and correctly,” assistant director for the health of women in the FDA’s Center for Devices and Radiological Health Terri Cornelison said in a statement.

However, she also acknowledged there was a margin of error in the app’s algorithm and other contraceptive methods. “Women should know that no form of contraception works perfectly, so an unplanned pregnancy could still result from correct usage of this device,” she said.

Hacking the websites responsible for election information is so easy an 11 year-old did it

It’s time to talk about election security. Over the weekend at Def Con, the annual hacker convention in Las Vegas to discuss some of the latest and greatest (or scariest) trends in the wild world of hacking, a pair of election security hacking demonstrations set up for adults and kids alike offered up some frightening […]

It’s time to talk about election security.

Over the weekend at Def Con, the annual hacker convention in Las Vegas to discuss some of the latest and greatest (or scariest) trends in the wild world of hacking, a pair of election security hacking demonstrations set up for adults and kids alike offered up some frightening revelations about America’s voting infrastructure. (I’m not even going to begin to touch Voatz.)

For 11 year-old Emmett from Austin, hacking the website for the Florida Secretary of State was as easy as a simple SQL injection.

While it took Emmett only 10 minutes to break into the election reporting section of the Florida Secretary of State web page, it’s important to note that these pages were set up as replicas.

The idea, according to event organizers from Wickr (a secure communications platform), “was mainly focused on breaking into the portions of the websites that are critical to the election process, [so] the kids worked against the replicas of the webpages where election results are reported by secretaries of state.”

The replicas were built by the team at Wall of Sheep Village and they issued the following statement: “The main issues with the live sites we are creating the replicas of are related to poor coding practices. They have popped up across the industry and are not vendor specific.”

And while the National Association for the Secretaries of State had some choice words for the Voting Machine Hacking Village, they didn’t address the hacks the kids made on their actual web sites.

In all, some 47 kids participated in the election hacking contest and 89% of them managed to get in to the virtual web sites set up by Wickr and Wall of Sheep Village.

Emmett, whose dad works in cybersecurity and who has been attending Def Con now for four years, has some thoughts on how easy it was for him to get into the system and change the vote tallies for election results.

“It’s actually kind of scary,” the 11 year-old said. “People can easily hack in to websites like these and they can probably do way more harmful things to these types of websites.”

The point, according to Wickr’s (badass) founder Nico Sell, is to bring attention to just how flawed security operations remain at the state level in areas that are vital to the nation’s democracy.

“The really important reason why we’re doing this is because we’re not taking the problem serious enough how significantly someone can mess with our elections,” said Sell. “And by showing this with eight year old kids we can call attention to the problem in such a way that we can fix the system so our democracy isn’t ruined.”

Some executives at big corporations share the same concerns. For Hugh Thompson, the chief technology officer at Symantec, the risks are real — even if the problems won’t manifest in the most important elections.

As Thompson (who worked on election security in the early 2000s) told The Financial Times, “The risk that I think most of us worried about at that time is still the biggest one: someone goes into a state or a county that doesn’t really matter in the grand scheme of the election, is not going to change the balance on x, y or z, but then publishes details of the attack,” he said. “Undermining confidence in the vote is scary.”

Stakes are incredibly high, according to experts familiar with election security. Despite the indictments that Robert Mueller, the special counsel investigating Russian interference, issued against 12 Russian nationals for targeting the 2016 US election, Russian hacking remains a threat in the current election cycle.

Microsoft has already said that it has detected evidence of attempted Russian interference into three campaigns already in the 2018 election cycle.

As Fortune reported in July, Microsoft’s vice president for customer security, said that researchers at the company had discovered phishing campaigns that were linked to the GRU, the Russian military intelligence unit tied to the DNC election hacks from 2016.

For security officers working on the websites for the secretaries of state in the battleground states that the tween and teen hackers targeted during Def Con, young Emmett has some advice.

“Use more protection. Upgrade your security and obviously test your own websites against some of the common vulnerabilities,” the 11 year-old advised. 

Your vegetables are going to be picked by robots sooner than you think

In the very near future, robots are going to be picking the vegetables that appear on grocery store shelves across America. The automation revolution that’s arrived on the factory floor will make its way to the ag industry in the U.S. and its first stop will likely be the indoor farms that are now dotting […]

In the very near future, robots are going to be picking the vegetables that appear on grocery store shelves across America.

The automation revolution that’s arrived on the factory floor will make its way to the ag industry in the U.S. and its first stop will likely be the indoor farms that are now dotting the U.S.

Leading the charge in this robot revolution will be companies like Root AI, a young startup which has just raised $2.3 million to bring its first line of robotic harvesting and farm optimization technologies to market.

Root AI is focused on the 2.3 million square feet of indoor farms that currently exist in the world and is hoping to expand as the number of farms cultivating crops indoors increases. Some estimates from analysis firms like Agrilyst put the planned expansions in indoor farming at around 22 million square feet (much of that in the U.S.).

While that only amounts to roughly 505 acres of land — a fraction of the 900 million acres of farmland that’s currently cultivated in the U.S. — those indoor farms offer huge yield advantages over traditional farms with a much lower footprint in terms of resources used. The average yield per acre in indoor farms for vine crops like tomatoes, and leafy greens, is over ten times higher than outdoor farms.

Root AI’s executive team thinks their company can bring those yields even higher.

Founded by two rising stars of the robotics industry, the 36 year old Josh Lessing and 28 year old Ryan Knopf, Root is an extension of work the two men had done as early employees at Soft Robotics, the company pioneering new technologies for robotic handling.

Spun out of research conducted by Harvard professor George Whiteside, the team at Soft Robotics was primarily comprised of technologists who had spent years developing robots after having no formal training in robot development. Knopf, a lifetime roboticist who studied at the University of Pennsylvania was one of the sole employees with a traditional robotics background.

“We were the very first two people at Soft developing the core technology there,” says Lessing. “The technology is being used for heavily in the food industry. What you would buy a soft gripper for is… making a delicate food gripper very easy to deploy that would help you maintain food quality with a mechanical design that was extremely easy to manage. Like inflatable fingers that could grab things.”

Root AI co-founders Josh Lessing and Ryan Knopf

It was radically different from the ways in which other robotics companies were approaching the very tricky problem of replicating the dexterity of the human hand. “From the perspective of conventional robotics, we were doing everything wrong and we would never be able to do what a conventional robot was capable of. We ended up creating adaptive gripping with these new constructs,” Lessing said.

While Soft Robotics continues to do revolutionary work, both Knopf and Lessing saw an opportunity to apply their knowledge to an area where it was sorely needed — farming. “Ag is facing a lot of complicated challenges and at the same time we have a need for much much more food,” Lessing said. “And a lot of the big challenges in ag these days are out in the field, not in the packaging and processing facilities. So Ryan and I started building this new thesis around how we could make artificial intelligence helpful to growers.”

The first product from Root AI is a mobile robot that operates in indoor farming facilities. It picks tomatoes and is able to look at crops and assess their health, and conduct simple operations like pruning vines and observing and controlling ripening profiles so that the robot can cultivate crops (initially tomatoes) continuously and more effectively than people.

Root AI’s robots have multiple cameras (one on the arm of the robot itself, the “tool’s” view, and one sitting to the side of the robot with a fixed reference frame) to collect both color images and 3D depth information. The company has also developed a customized convolutional neural network to detect objects of interest and label them with bounding boxes. Beyond the location of the fruit, Root AI uses other, proprietary, vision processing techniques to measure properties of fruit (like ripeness, size, and quality grading).  All of this is done on the robot, without relying on remote access to a data-center. And it’s all done in real time.

Tools like these robots are increasingly helpful, as the founders of Root note, because there’s an increasing labor shortage for both indoor and outdoor farming in the U.S.

Meanwhile, the mounting pressures on the farm industry increasingly make robotically assisted indoor farming a more viable option for production. Continuing population growth and the reduction of arable land resulting from climate change mean that indoor farms, which can produce as much as twenty times as much fruit and vegetables per square foot while using up to 90% less water become extremely attractive.

Suppliers like Howling Farms, Mucci Farms, Del Fresco Produce and Naturefresh are already producing a number of fruits and vegetables for consumers, said Lessing. “They’ve really fine tuned agriculture production in ways that are meaningful to broader society. They are much more sustainable and they allow you to collocate farms with urban areas [and] they have a much more simplified logistics network.”

That ability to pare down complexity and cost in a logistics supply chain is a boon to retailers like Walmart and Whole Foods that are competing to provide fresher, longer lasting produce to consumers, Lessing said. Investors, apparently agreed. Root AI was able to enlist firms like First Round CapitalAccompliceSchematic Ventures, Liquid2 Ventures and Half Court Ventures to back its $2.3 million round.

“There are many many roles at the farm and we’re looking to supplement in all areas,” said Lessing. “Right now we’re doing a lot of technology experiments with a couple of different growers. assessment of ripeness and grippers ability to grab the tomatoes. next year we’re going to be doing the pilots.”

And as global warming intensifies pressures on food production, Lessing sees demand for his technologies growing.

“On a personal level I have concerns about how much food we’re going to have and where we can make it,” Lessing said. “Indoor farming is focused on making food anywhere. if you control your environment you have the ability to make food…. Satisfying people’s basic needs is one of the most impactful things i can do with my life.”

Indian H-1B applicants face particular scrutiny in Trump’s work visa crackdown

Coming to the U.S. on a work visa is getting harder across the board, but workers from India in particular are feeling the effects of recent policy shifts from the Trump administration. A new report from the National Foundation for American Policy sheds light on how the “Buy American and Hire American” executive order from […]

Coming to the U.S. on a work visa is getting harder across the board, but workers from India in particular are feeling the effects of recent policy shifts from the Trump administration. A new report from the National Foundation for American Policy sheds light on how the “Buy American and Hire American” executive order from April 2017 has impacted H-1B applicants in the last year. The H-1B visa, popular in Silicon Valley, lets skilled foreign workers live and work in the U.S. for a six year term.

For the three months period starting in July 2017, H-1B denial rates went from 15.9% to 22.4%. In the same time period, Requests for Evidence seeking additional documentation in the fourth quarter of 2017 nearly equaled the total amount of Requests for Evidence from the year’s other three quarters combined (63,184 and 63,599 requests, respectively).

Drilling down, workers from India appear to be the most affected. From July to September 2017, U.S. Citizenship and Immigration Services (USCIS) demanded additional documentation from 72% of Indian H-1B applications, compared to the 61% rate of other countries considered together. During that same three month period, 23.6% of Indian applications were rejected, up from 16.6% between April and June 2017.

“The increase in denials and Requests for Evidence of even the most highly skilled applicants seeking permission to work in America indicates the Trump administration is interested in less immigration, not ‘merit-based’ immigration,” the report adds.

“… U.S. Citizenship and Immigration Services has enacted a series of policies to make it more difficult for even the most highly educated scientists and engineers to work in the United States.”

In January, rumors of a ban on H-1B extensions for green card applicants had H-1B workers nervous. In June, new rules shortening visas for Chinese STEM students went into effect. While China only accounted for 9.4% of total H-1B visa applications in the 2017 fiscal year compared to India’s whopping 76%, the Trump administration will likely continue to tighten immigration policies targeting China as it obsessively tries to turn the screws on its perceived trade nemesis.