Testing a pay-per-mile tax in Oregon

Looking for more revenue, Oregon is starting a test program of paying for miles driven rather than gasoline used:

The program is meant to help the state raise more revenue to pay for road and bridge projects at a time when money generated from gasoline taxes are declining across the country, in part, because of greater fuel efficiency and the increasing popularity of fuel-efficient, hybrid and electric cars.

Starting July 1, up to 5,000 volunteers in Oregon can sign up to drive with devices that collect data on how much they have driven and where. The volunteers will agree to pay 1.5 cents for each mile traveled on public roads within Oregon, instead of the tax now added when filling up at the pump…

Private vendors will provide drivers with small digital devices to track miles; other services will also be offered. Volunteers can opt out of the program at any time, and they’ll get a refund for miles driven on private property and out of state…

Drivers will be able to install an odometer device without GPS tracking.

For those who use the GPS, the state and private vendors will destroy records of location and daily metered use after 30 days. The program also limits how the data can be aggregated and shared. Law enforcement, for example, won’t be able to access the information unless a judge says it’s needed.

 

I suspect a number of governments will be interested in how this test works out. One big hurdle to overcome would seem to be privacy, though government tracking of vehicles may not be far off anyhow (through cell phones, insurance company monitoring devices, black boxes, toll booths/devices, license plate readers, etc.). The argument about deincentivizing electric or hybrid cars doesn’t really hold up because these vehicles still use the roads and add to the maintenance burden. Yet, ultimately this will be about revenue: is this a better model for bringing in the money needed for roads?

New gadgets, apps want more location data from users

Location data is valuable and more new gadgets make use of the information:

Location-tracking lets developers build fast, useful, personalized apps. They’re enticing, but they come with tradeoffs: your gadgets and apps maintain a log of where you’ve been and what you’re doing, and more of them than you think are sharing that data with others.

It’s going to advertisers, mostly, so they can lure you into the Starbucks a block away or the merch tent at Coachella. It’s as creepy as any other targeted marketing, but most of us have come to accept that it comes with the territory. Jennifer Lynch, a senior staff attorney at the Electronic Frontier Foundation, says it goes deeper. Your data might get sold to your credit reporting agency, which wants to know more about you as it determines your credit score. It might go to your insurance company, which is very interested in your whereabouts. It might be subpoenaed by the government, for just about any reason. Maybe none of that is happening. Maybe all of it is. There’s really no way for us to know…

Your phone’s ability to pinpoint your exact location and use that info to deliver services—a meal, a ride, a tip, a coupon—is reason for excitement. But this world of always-on GPS raises questions about what happens to our data. How much privacy are we willing to surrender? What can these services learn about our activities? What keeps detailed maps of our lives from being sold to the highest bidder? These have been issues as long as we’ve had cellphones, but they are more pressing than ever.

Another major trade-off that I suspect most users will make without much fuss in the coming years. The cynical take on the advantages for the user is that this is primarily about customizable marketing that can account for both your individual traits and where exactly you are. In other words, sharing location data will give consumers new opportunities. More consumerism! On the flip side, it is less clear how or when location data might be used against you. But, when it is, it probably won’t be good.

The broader issue here is whether people should have geographical freedom that is not known to others. This is increasingly difficult in today’s world even as we would celebrate the mobility Americans have within their own communities, country, and to travel throughout the world.

“We don’t lie to our search engine. We’re more intimate with it than with our friends, lovers, or family members.”

Wired has an interesting excerpt from a new book Data and Goliath:

One experiment from Stanford University examined the phone metadata of about 500 volunteers over several months. The personal nature of what the researchers could deduce from the metadata surprised even them, and the report is worth quoting:

Participant A communicated with multiple local neurology groups, a specialty pharmacy, a rare condition management service, and a hotline for a pharmaceutical used solely to treat relapsing multiple sclerosis…

That’s a multiple sclerosis sufferer, a heart attack victim, a semiautomatic weapons owner, a home marijuana grower, and someone who had an abortion, all from a single stream of metadata.

Web search data is another source of intimate information that can be used for surveillance. (You can argue whether this is data or metadata. The NSA claims it’s metadata because your search terms are embedded in the URLs.) We don’t lie to our search engine. We’re more intimate with it than with our friends, lovers, or family members. We always tell it exactly what we’re thinking about, in as clear words as possible.

The gist of the excerpt is that while people might be worried about the NSA, corporations know a lot about us: from who we have talked to, where we have been, who have interacted with through metadata and more personal information through search data. And perhaps the trick to all of this is that (1) we generally give up this data voluntarily online (2) because we perceive some benefits and (3) we can’t imagine life without all of this stuff (even though many important sites and social media barely existed a decade or two ago).

The reason I pulled the particular quote out for the headline is that it has some interesting implications: have we traded close social relationships for the intimacy of the Internet? We may not have to deal with so much ignorance – just Google everything now – but we don’t need to interact with people in the same ways.

Also, this highlights the need for tech companies to put a positive spin on all of their products and actions. “Trust us – we have your best interests at heart.” Yet, like most corporations, their best interests deal with money rather than solely helping people live better lives.

Early 1990s proposal for Personal Rapid Transit in the Chicago suburbs

Officials are still trying to develop effective mass transit in the Chicago suburbs but perhaps they missed something: an early 1990s proposal for Personal Rapid Transport from several suburbs.

I came across a 1991 “Proposal for a Personal Rapid Transit Demonstration System” from the Village of Rosemont. Envision, if you will, a network of autonomous, futuristic five-person pods zipping through the glassy canyon of corporate headquarters near O’Hare, alighting at their passengers’ chosen destination…

It wasn’t the only avant-garde transportation idea that the RTA was considering at the time “in an effort to coax drivers, particularly in the suburbs, out of their cars.” In June of 1992, as the competition to get PRT continued, the agency was also investigating SERCs, or “stackable electric rental cars,” approximately the size of a Honda Accord, with a range of 28 miles and a top speed of 50-60 miles an hour. The system would allow workers to take the Metra to a SERC station, drive the last few miles to the office or home, and return it by the next day—sort of like bike-share for tiny electric cars. It doesn’t seem to have gone beyond a symposium on the technology.

But the PRT plan got serious. Rosemont retained Winston & Strawn—around the same time the RTA hired them for lobbying work—at a cost of $50,000. They spent another $50,000 to prepare for the application. The mayor told the Tribune in May of 1991 that they were prepared to spend another $100,000 to get the RTA experiment. And Rosemont got the nod, though it took two years.

In 1998, eight years after and $22.5 million dollars after the RTA set it in motion, Rosemont’s PRT system came to life. It came to life on a test track at Raytheon in Massachusetts, but nonetheless, it existed, in RTA-emblazoned glory. RTA officials were pleased.

Moser suggests the plan was killed by two main factors: cost overruns and then Raytheon got out of this particular business. But, I just don’t see how this would have been attractive to average suburbanites. Monorail like lines would have to be constructed to connect major buildings and nodes; how many want to live around those (even with little noise)? It still requires a certain level of density in order to have consistent ridership. This might work great along office corridors – which the suburbs in on this proposal, Rosemont, Naperville, Deerfield, and Schaumburg, all have – where there are thousands of workers on a regular basis. The primary advantage is that people don’t have to ride with many others, something that wealthier commuters seem to like and would pay to get. But, in the end, this seems like a more private form of train/monorail/bus linking higher density areas.

Using social media data to predict traits about users

Here is a summary of research that uses algorithms and “concepts from psychology and sociology” to uncover traits of social media users through what they make available:

One study in this space, published in 2013 by researchers at the University of Cambridge and their colleagues, gathered data from 60,000 Facebook users and, with their Facebook “likes” alone, predicted a wide range of personal traits. The researchers could predict attributes like a person’s gender, religion, sexual orientation, and substance use (drugs, alcohol, smoking)…

How could liking curly fries be predictive? The reasoning relies on a few insights from sociology. Imagine one of the first people to like the page happened to be smart. Once she liked it, her friends saw it. A social science concept called homophily tells us that people tend to be friends with people like themselves. Smart people tend to be friends with smart people. Liberals are friends with other liberals. Rich people hang out with other rich people…

On the first site, YouAreWhatYouLike, the algorithms will tell you about your personality. This includes openness to new ideas, extraversion and introversion, your emotional stability, your warmth or competitiveness, and your organizational levels.

The second site, Apply Magic Sauce, predicts your politics, relationship status, sexual orientation, gender, and more. You can try it on yourself, but be forewarned that the data is in a machine-readable format. You’ll be able to figure it out, but it’s not as pretty as YouAreWhatYouLike.

These aren’t the only tools that do this. AnalyzeWords leverages linguistics to discover the personality you portray on Twitter. It does not look at the topics you discuss in your tweets, but rather at things like how often you say “I” vs. “we,” how frequently you curse, and how many anxiety-related words you use. The interesting thing about this tool is that you can analyze anyone, not just yourself.

The author then goes on to say that she purges her social media accounts to not include much old content so third parties can’t use the information against them. That is one response. However, before I go do this, I would want to know a few things:

1. Just how good are these predictions? It is one thing to suggest they are 60% accurate but another to say they are 90% accurate.

2. How much data do these algorithms need to make good predictions?

3. How are social media companies responding to such moves? While I’m sure they are doing some of this themselves, what are they planning to do if someone wants to use this data in a harmful way (say, affecting people’s credit score)? Why not set limits for this now rather than after the fact?

Chicago to collect big data via light pole sensors

Chicago is hoping to collect all sorts of information via a new system of sensors along main streets:

The smooth, perforated sheaths of metal are decorative, but their job is to protect and conceal a system of data-collection sensors that will measure air quality, light intensity, sound volume, heat, precipitation, and wind. The sensors will also count people by observing cell phone traffic…

While data-hungry researchers are unabashedly enthusiastic about the project, some experts said that the system’s flexibility and planned partnerships with industry beg to be closely monitored. Questions include whether the sensors are gathering too much personal information about people who may be passing by without giving a second thought to the amount of data that their movements—and the signals from their smartphones—may be giving off.

The first sensor could be in place by mid-July. Researchers hope to start with sensors at eight Michigan Avenue intersections, followed by dozens more around the Loop by year’s end and hundreds more across the city in years to come as the project expands into neighborhoods, Catlett said…

While the benefits of collecting and analyzing giant sets of data from cities are somewhat speculative, there is a growing desire from academic and industrial researchers to have access to the data, said Gary King, director of the Institute for Quantitative Social Sciences at Harvard University.

The sort of data collected here could be quite fascinating, even with the privacy concerns. I wonder if a way around this is for the city to make clear now and down the road how exactly they will use the data to improve the city. To some degree, this may not be possible because this is a new source of data collection and it is not entirely known what might emerge. Yet, collecting big data can be an opaque process that worries some because they are rarely told how the data improves their lives. If this simply is another source of data that the city doesn’t use or uses behind the scenes, is it worth it?

A quick hypothetical. Let’s say the air sensors along Michigan Avenue, one of Chicago prime tourist spots, shows a heavy amount of car exhaust. In response to the data, the city announces a plan to limit congestion on Michigan Avenue or to have clean mass transit. This could be a clear demonstration that the big data helped improve the pedestrian experience.

But, I could also imagine that in a year or two the city hasn’t said much about this data and people are unclear what is collected and what happens to it. More transparency and clear action steps could go a long way here.

Health includes social and behavioral dimensions

There may be privacy concerns about the government having behavioral and social data as part of medical records but that doesn’t necessarily mean they aren’t important factors when looking at health:

The Centers for Medicare and Medicaid Services (CMS) wants to require health care providers to include “social and behavioral” data in Electronic Health Records (EHR) and to link patient’s records to public health departments, it was announced last week.

Health care experts say the proposal raises additional privacy concerns over Americans’ personal health information, on top of worries that the Obamacare “data hub” could lead to abuse by bureaucrats and identify theft…

The “meaningful use” program already requires doctors and hospitals to report the demographics of a patient and if he smokes to qualify for its first step. The second stage, planned for 2014, will require recording a patient’s family health history.

The National Academy of Sciences will make recommendations for adding social and behavioral data for stage three, which will be unveiled in 2016.

Maybe these are separate concerns: one might argue such data is worthwhile but they don’t trust he government with it. But, I suspect there are some who don’t like the collection of social and behavioral data at all. They would argue it is too intrusive. People have made similar complaints about the Census: why exactly does the government need this data anyway?

However, we know that health is not just a physical outcome. You can’t separate health from behavior and social interactions. There is a lot of potential here for new understandings of health and its multidimensionality. Take something like stress. There are physical reactions to it but this is an issue strongly influenced by context. Solutions to it could include pills or medicine but that is only dealing with the physical outcomes rather than limiting or addressing stressful situations.

We’ll see how this plays out. I suspect, federal government involvement or not, medical professionals will be looking more at the whole person when addressing physical concerns.

Born into digital lives: average newborn online within an hour of birth

The newborns of today arrive online very quickly:

The poll found that parents were the most likely to upload pictures of the newborns (62 per cent), followed by other family members (22 per cent) and friends (16 per cent).

The most popular platform for displaying these first baby images was Facebook, followed by Instagram and Flickr…

Marc Phelps of baby photo agency http://www.posterista.co.uk, which commissioned the survey, said: “The fact that a picture of the average newborn is now online within an hour just goes to highlight the enormous impact social media has had on our lives in the past five years, and how prevalent these pages are in helping to keep loved ones informed on the special occasions in our lives, such as the birth of a new child.

Some more on the survey:

The poll by print site http://www.posterista.co.uk, which surveyed 2,367 parents of children aged five and under, aimed to discover the impact social media have had on the way new parents share information and images of their offspring…

The top five reasons cited for sharing these images online included keeping distant family and friends updated (56%), expressing love for their children (49%), describing it as an ideal location to store memories (34%), saying it is a great way to record children’s early years (28%), and to brag to and “better” other parents’ photos (22%).

It sounds like complete digital immersion. The most common reason given for this practice mirror the main reasons users give for participating in SNS like Facebook: to remain connected with others. But, the next four reasons differ. The second and fifth reasons suggest posting photos about newborns is about social interactions, first with the new baby (positive, though the baby doesn’t know it – plus, this could be part of a public performance of how love is shown in the 2010s) but then also in competition with others (negative). The third and fourth reasons are more about new digital tools; instead of developing film or printing pictures, SNS can be online repositories of life (offloading our memories online).

Thinking more broadly, what are the ethics of posting pictures of people online who haven’t given their permission or don’t know they are online? This could apply to children but this could also apply to friends or even strangers who end up in your photos. Some have suggested companies like Facebook have information on people who don’t have profiles through the information provided by others. Plus, if you don’t go online, others might think you are suspicious. So, perhaps the best way to protect your content online is not to withdraw and try to hide but rather to rigorously monitor all possible options…

Getting the data to model society like we model the natural world

A recent session at the American Association for the Advancement of Science included a discussion of how to model the social world:

Dirk Helbing was speaking at a session entitled “Predictability: from physical to data sciences”. This was an opportunity for participating scientists to share ways in which they have applied statistical methodologies they usually use in the physical sciences to issues which are more ‘societal’ in nature. Examples stretched from use of Twitter data to accurately predict where a person is at any moment of each day, to use of social network data in identifying the tipping point at which opinions held by a minority of committed individuals influence the majority view (essentially looking at how new social movements develop) through to reducing travel time across an entire road system by analysing mobile phone and GIS (Geographical Information Systems) data…

With their eye on the big picture, Dr Helbing and multidisciplinary colleagues are collaborating on FuturICT, a 10-year, 1 billion EUR programme which, starting in 2013, is set to explore social and economic life on earth to create a huge computer simulation intended to simulate the interactions of all aspects of social and physical processes on the planet. This open resource will be available to us all and particularly targeted at policy and decision makers. The simulation will make clear the conditions and mechanisms underpinning systemic instabilities in areas as diverse as finance, security, health, the environment and crime. It is hoped that knowing why and being able to see how global crises and social breakdown happen, will mean that we will be able to prevent or mitigate them.

Modelling so many complex matters will take time but in the future, we should be able to use tools to predict collective social phenomena as confidently as we predict physical pheno[men]a such as the weather now.

This will require a tremendous amount of data. It may also require asking for a lot more data from individual members of society in a way that has not happened yet. To this point, individuals have been willing to volunteer information in places like Facebook and Twitter but we will need much more consistent information than that to truly develop models like are suggested here. Additionally, once that minute to minute information is collected, it needs to be put in a central dataset or location to see all the possible connections. Who is going to keep and police this information? People might be convinced to participate if they could see the payoff. A social model will be able to do what exactly – limit or stop crime or wars? Help reduce discrimination? Thus, getting the data from people might be as much of a problem as knowing what to do with it once it is obtained.