Viewing entries tagged
digital systems

Backcasting Urban Planning and Design for Autonomous Cars and Social Robotics



Advancements in technology do not necessarily lead to improvements in society.  Social policies created in response to technology might generate social safeguards but do not always promote social benefits. While we can witness technological developments with delight, we must take a moment to ask ourselves, what kind of future are we creating?

Just last week the US Secretary of Transportation described an infrastructure deficit, not only in terms of existing infrastructure, but also as a lack of planning for future needs. Around the same time the Consumer Electronics Show displayed an array of emerging automotive technologies. Companies ranging from Ford to Mercedes revealed concept cars for autonomous vehicles to roll out in the next few years. Using multiple LIDAR sensors, GPS, and new interior configurations, engineers and industrial designers are redesigning the future of automobile transportation.

But are civil engineers and urban planners actively promoting a sufficient infrastructure to accommodate new use patterns.  To some extent, yes. Much discussion was prompted when IHS released a study speculating that autonomous vehicles will dominate the landscape by 2035.  Some economists speculate that congestion and fuel use will increase. There are even proposals that traffic tickets will be reduced and proposals that cities will be configured around changes in parking, density, and speed limits. It is also thought that changes of car ownership and use will change, such as operating buses more like trains.

It is clear the urban landscape will need to be reconfigured and there are some ideas to determine what this means. Yet if we look at the bigger picture, what are we working toward? What is the future we are constructing? In a city with less traffic tickets or city parking, how will taxes change? If buses are so streamlined, then does the freedom of private car ownership become reserved only for the wealthy?

The present planning and development trend of speculation on social robotics is insufficient because it relies upon a purely constructivist approach.  We had previous industry and technologies that resulted in todays conditions, so now we are creating new technologies in response to those conditions.  Naturally this will create a new scenario, accompanied by additional problems, and there will be a demand to innovate out of that situation into another. But to what ends? What is the end game?

In the existing approach we are saying that fuel and spatial demands will adjust in response to autonomous transportation technologies.  Yet how will this response occur in relation to existing problems such as income inequality, underemployment, poor access to health care, and poor quality infrastructure such as housing, water, and roads?  At present I see no evidence that social robotics will help the existing socio-economic problems but might do more to proliferate them.

In 2035, will only poor people need to drive their cars?  Will the price of driven cars become more expensive from reduced demand, placing additional financial burden on low-income communities? While those who now 1-2 freed hours of time per day (since they are not driving) be able to use that time for study, extended work hours, and business meetings? How will those still using their time to drive be able to compete in the workforce? Will those unable to access social robotics find their entire communities collapsing upon outdated infrastructures?  Will property values shift dramatically creating new ghettos and devastated landscapes?

What if we propose a different vision?  What if citizens and leaders took responsibility to say "In 2035 want my community to look like X?"  It takes imagination and guts to state such a declaration. Yet by setting a clear vision, it is possible to work backwards, to reverse engineer pathways to that vision and align current choices accordingly.  To backcast the future of social robotics might create a future that is more grounded in the social than the robotic.  To plan with a goal in mind, rather than through continued ad hoc remedies, perhaps our high-tech future could be a place where someone might actually want to live. Even if they can't afford it.

The New Digital Divide: Transforming the Global South into Reliable Data

Transforming the world's most hard-to-access and uncertain landscapes into digital data. Sutika Sipus 2014.
Everyday urban professionals, data scientists, economists, and geographers sit in front of a computer screen and create extraordinary visualizations and statistical methods to unravel the world.  Geographic information systems such as QGIS, statistical programs like "R", spreadsheet softwares like Excel and lines of python code have empowered us with the ability to understand economies at scale, measure and predict public health, monitor pollution and deter violence.  Data is good.

Yet what about cities, states, and nations that do not or cannot generate reliable data?  In his recent book, Poor Numbers, author Morten Jerven reveals the faulty statistics collected and published by government agencies throughout Africa.  Over the last three years that I was in Afghanistan, I witnessed nearly every single aid agency or government research contractor rely upon "perception based" data which means researchers confronted too much danger in the field to collect actual information, but could only ask locals their opinion on matters ranging from conflict to education and corruption.  This method is safe but provides zero validity.  It might as well be make-believe.

The result is the global data gap.  Governments and institutions that can transform intangible social dynamics into quantifiable data can conduct sophisticated analysis and move forward at a faster pace. This sensibility was the foundation of my initiative in Mogadishu, to create a comprehensive map of the city that fused business and residential management with geography.  As my operation was too small to go beyond the proof of concept, the vision was eventually passed via the local government and integrated into a longstanding UN initiative to develop a city planning department which is advancing with some success.  Yet while Mogadishu may be on the cusp of a digital governance revolution, problems persist.  Data dies.  Situations change.  More dramatically, very little of the world is generating the data sets commonly enjoyed throughout the west.

The global data gap is economically inhibitive. Imagine if your company sought a new market opportunity because the markets your normally serve are saturated with your product and your competitors.  Most companies would never imagine distribution in an African nation, partly because of misled beliefs on stability of those markets, but that those misconceptions are ultimately founded on a lack of reliable data.  With no local data, there is no global opportunity.

This is also a failure for companies that already working in data-deficient nations.  A few months ago I had a meeting with Afghanistan's largest tele-communications provider, Roshan, and when I asked about coverage, they could only give vague feedback.  When I asked for data on every household using Roshan to access the internet in Kabul, they could not give this information because Kabul doesn't have a postal address system, so all installations are tied to a person's name and neighborhood, but not a specific address.  In this instance I created alternative solution, where after about three weeks of combing selected neighborhoods, I was able to generate a GPS location for every Wi-Fi network and mobile tower in each area which could then be joined with the existing data.  We could filter Roshan networks vs competitor networks and now had sufficient data to improve marketing and coverage strategies.

Location and evaluation of strength of Wi-Fi access in Kabul, Afghanistan. Sutika Sipus 2014.
Having worked throughout Africa and Asia as a researcher since 2007,  I have developed an array of techniques to get past this problem, focusing on the creation and testing of indirect indicators.  In Zimbabwe economic wealth could be measured by counting the number of water jugs in front of each house.  In the Philipines, one could count denim jeans swinging on the clothesline of an apartment.  In a variety of Somali refugee camps I found that metal roofing materials separated the less-poor from the more-poor.  In Afghanistan I have steadily been testing and re-testing the presence of graffiti as a predictor of social protest and conflict with success.  The advantage of these Rapid Rural Appraisal techniques is that they are safe, fast, efficient, and quantifiable.  To determine an RRA indicator requires extensive time on the ground, but once established, we can effectively measure anything, anywhere.  There are of course other methods, standard survey techniques, but my efforts generate GPS location, culturally relative valuation, and easily shared outcomes.  RRA is not new, but my method of fusing RRA with traditional research methods, GIS tools, and mobile technologies does create a new outcome. I produce valid, quantifiable and mappable data that is customized to the problem and the location, but can accommodate different scales.

Digital Data Collection and Mapping.
Cambodia. Sutika Sipus 2014.
To me, the global data gap is a new frontier of untapped opportunity.  Maybe more people will realize this sooner than later and I'll encounter some digital cowboys, wandering deserts with laptops and satellite phones, their backpacks sagging beneath the weight of external hard drives.  I won't be the only one canvasing the worlds most remote locations.

Maybe soon more companies will ask "what about Nigeria?  what about Ghana or Bangladesh?" and they will need answers.  They will look online and see some global statistics that are 5 years old and impossible to trust.  They will need a fresh perspective they can trust and they can see.  Something they can drop into their software and understand.  Good thing I'm easy to find.


The Human Latency of Smart Cities and Data Driven Reward Systems


Last week the number of participants registered with the US healthcare website were released and the results were unimpressive. This could be for many reasons, although personally, I have not enrolled simply because the website, like all technologies, is an iterative process.  Whenever a new operating system rolls out for my laptop or ipad, I'm always excited, but I'm never an immediate adopter.  I typically wait until an update is launched, which is typically about 2 weeks later.  I'm rather excited by the healthcare initiative, but it would be foolish to rush into enrollment.  The website, like all technologies is a work in progress.

The constant media coverage about the dismal enrollment numbers has been paralleled only by NSA scandals which has done much to raise the social dialogue on issues of connectivity, surveillance, and our data driven lives.  In a few previous blog posts I've reflected on the persistence of data beyond communal memory.  This week I've had some time to read some of Anthony Townsend's new book Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia.  Concurrently I've also been reading Addiction By Design: Machine Gambling in Las Vegas by Natasha Dow Schüll.  While both of these texts appear to handle different subjects, I'd argue that their is actually a strong link between these works and the current issues of technology in society.

Within Smart Cities, Townsend begins with a historical overview of urban technology development and describes the evolution of major corporations presently working with these issues such as Siemens, Cisco, and IBM.  He identifies established and emerging systems to contend with urban planning issues of climate change, traffic, and economic growth.  But Townsend isn't advocating for these mega-companies to dominate data-driven urban development.  Rather, he advocates for a more widely distributed net of stakeholders, consisting of empowered everyday citizens who use technology to interface with their governments and businesses to create a bottom-up model of a well designed urban landscape.  

I've met Anthony a couple times and have followed his work for many years.  Last June I sat in the audience at Poptech The City Resilient and listened to his talk on designing a wireless network in New Jersey that will continue to function under threat of natural disaster.  His faith in smart systems is optimistic, yet carefully hesitant, and I believe his argument for the creation of smart cities to be a more democratic process to be on target.   

Yet my own concern about smart cities is less about the actors involved in the creation of the technology and the control of the data, but is more interested in the actual "recipes" used to streamline the city.  When I lived in Cincinnati, I recall it had demographic and economic qualities nearly identical to the city of St. Louis.  Consequently, it was common for these two city governments to simply share or sell each other studies on their own cities (such as research on industrial clusters) rather than conduct the work internally.  If somethings works in St. Louis, then it should work in Cincinnati!  On a different scale, I've also sat in several meetings with members of the United Nations advocating a similar boiler-plate approach to urban development - even if the project failed in the first instance, it would be replicated and applied to the second.  

Consequently I believe that an extensive level of qualitative research must be done before any quantitive system can be constructed and applied to a given city.  Of course this is expensive and methodical mess, so probably not in the interest of companies like IBM.  This is where Anthony and I overlap.  If the work is done by the local communities, then the outputs will likely best conform to the local demands.  

Anthony advocates and hopes for the widespread participation of urban citizens in the creation of smarter cities.  He does well to identify many small organizations working to teach programming and give momentum to local-scale smart city development.  But here we differ again... my outlook is gloomier.

For much of internet history, we have mostly lived under the 90-9-1 rule - wherein 1% of internet users create content, 9% curate, and 90% consume.  In the 20 years we have had the internet, this has improved as online content creation has risen with the advent of social media.   In 2004, The Pew Research center found that 44% of internet users had actually created content on the internet.  Now, Pew has found that number has drifted upward to 54% in 2013. I should add that the Pew Research Center released another study identifying that 15% of Americans are not even online.    I realize this is a a very small snapshot, but does this rate imply that it will take 99 years for 100% of internet users to also become content creators?  But what is a more reasonable number? 50 years? 20?  

If 20 years of global internet access has resulted in only 50% of all internet users to become content creators, how will this translate to more technical processes such as coding?  Yes - there are many high quality online tools today for people to learn computer programming skills for free.  I am personally a frequent user of such tools.  But this stuff is not easy, requires discipline, and is not a skill set available in a readily consumable manner.  More importantly - there is an issue of incentive.

Participation in any enterprise requires an incentive, but the situation darkens when the enterprise has a steep learning curve.  Apparently health care and national security are not a sufficient incentive for most Americans to use a website or forsake personal data.  But in contrast, millions of Facebook users supply very personal details of their lives to the Facebook company for the satisfaction of gossip, shared photos, and adorable cat videos.  What incentives exist for a democratized process of urban systems design?

This is where I feel Schüll's research on human addiction to casino machine gambling might provide light.  Casino machines are highly refined to maximize the amount of time an individual spends on the machine.  Casinos also employ various design techniques to drive customers toward machines and increase time of play.  But many casino's now feature data driven analytics to refine the experience further, to create new machines, and to ultimately derive far higher profits.  An excellent example is the use of rewards cards.

Subscribed loyalty rewards programs encourage repeat visits but they also give customers a reason to share data.  By providing customers with free rooms, meals and tickets to special events - or even paid weekend resort getaways for high rollers - casinos provide a series of convenience and in exchange, capitalize on the windfall of collected data.  Many casinos maintain 90 different demographic categories on each customer, can predict future calendars and budgets, and generate behavior reports to assemble the best package of rewards to offer each individual.  If a customer strays from pattern... for example, a habitual gambler stops making visits, that person will be emailed, snail mailed, and telephone called with enticing offers to return.  

This creepy surveillant system has been of great value to the casino industry.  It works.  But it also appears to be popular with patrons.  According to Schüll, in Las Vegas casinos, "70% of gamblers use loyalty club cards" and the number continues to rise.  Apparently the provision of personal information to a corporation is okay in exchange for a hotel room and a prime-rib dinner.  But website enrollment for affordable healthcare?  Snooze.

A distinct difference between the task/reward systems of the casinos and the healthcare enterprise is that in the healthcare website, an individual must still express a level of work and payment in exchange for the reward.  Whereas in the casino system, it appears to consist entirely of rewards for the user.  The array of losses are behind the scenes.

So returning to the issue of "who" leads the charge in the creation of smart cities, I honestly don't see a great degree of grass-roots design unless the amount of effort is reduced and a direct system of ongoing incentives is increased.   The success of the Citi Bike initiative in New York City is a good example. Users enjoy the convenience of an affordable system, brought about through public-private partnership, and the primary sponsor CitiBank maintains a constant influx on user data with which to capitalize. Perhaps in the end the only real winner will be the bank, but right now it appears as a worthwhile exchange for over 100,000 enrolled bike users. 

Perhaps this rewards model can be applied somewhere as we continue down the road of data driven city optimization.  Maybe a clear system of direct incentives can be provided in exchange for citizens to contribute to the creation of better neighborhoods and the sharing of personal data.  Maybe one day, however, the simple rewards of a safer, cleaner neighborhood will be enough?