How Lime, Bird and other vehicle-sharing companies can help us design our cities better

16

October

2019

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Dockless scooters have been the hype of the past 2 years. In 2018, a Santa-Monica based company called Bird introduced the world to small-sized vehicle-sharing as a solution to the first and last mile challenge. Now, backed by over 500 million USD, the start-up is valued at 2.5 billion USD, and operates their massive fleet of scooters in over 100 cities across North-America and Europe (Hawkins, 2019). Similar companies, such as Lime (US), Scooter (US), and even felyx (NL) were quick to launch their own version of shared mobility.

Although these scooters have faced a lot of frustration and pushback, we shouldn’t deny their huge success. They’ve shown that people are hungry for new modes of transportation. For instance, felyx facilitated 430,000 km in rides in their first year in Amsterdam (Keswiel, 2018). Because of the built-in GPS tracker of scooters, these trips are documented, stored, and very valuable. Given the free-floating nature of the scooters, this trip-level data basically shows the complete travel behavior of citizens in a given city, which public transportation data cannot offer. This is because of its fixed time schedule and routes. Public transportation serves the average citizen, whereas shared mobility has the ability to serve every citizen.

Through data collection, scooters have the ability to change urban city design.
Through data collection, scooters have the ability to change urban city design.

 

So what are the opportunities? Shared-vehicle mobility companies can leverage this data to build a stronger relationship with municipalities. Essentially, data collected by these companies on the individual trip-level data is valuable real-time feedback on urban city designs (Woyke, 2019). It accurately explains how people move through cities and helps municipalities point out where the pain points from an urban design perspective. Also, it allows municipalities and these companies to work together in deciding on how to tackle the problem of scooters hindering pedestrians and taking up side-walk space. In short, aside from being a complementary service to existing transportation networks of cities, these vehicle-sharing companies can be contributors to urban city design through their business model by selling its data (Stuart, 2019).

Do you guys think that these types of rider data is also valuable in the Netherlands, a country where the bike line infrastructure is already really good. I’d like to hear your thoughts. Thanks.

References

Hawkins, A. J. (2019). Bird raises new funding at 2.5 billion valuation, thanks to longer-lasting scooters. The Verge. Retrieved from: https://www.theverge.com/2019/10/3/20895798/bird-scooter-fundraising-valuation-unit-economics

Keswiel, M. (2018). Deelscooter-startup felyx laat 324 scooters los op Rotterdam, dankzij 3 miljoen euro groeigeld. Retrieved from: https://www.sprout.nl/artikel/startups/deelscooter-startup-felyx-laat-324-scooters-los-op-rotterdam-dankzij-3-miljoen-euro

Stuart, S.C. (2019). How Scooters (and the Data They Collect) Can Transform Cities. Medium. Retrieved from: https://medium.com/pcmag-access/how-scooters-and-the-data-they-collect-can-transform-cities-e5316a7267e7

Woyke, (2019). The Secret Data Collected by Dockless Bike Is Helping Cities Map Your Movement. Medium. Retrieved from: https://medium.com/mit-technology-review/the-secret-data-collected-by-dockless-bikes-is-helping-cities-map-your-movement-54ec6c2b97dc

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The people who create our solutions

16

October

2019

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I believe that many people, including me, put a lot of trust in technology. And why shouldn’t we? Technology in agriculture such as fertilizers and machinery have given us the ability to produce more food than we can eat. We live longer, healthier lives because of technological improvements in the medical field. We can even build giant cities in deserts.

But what about information technologies. Can we trust (future) information-based technologies to solve all our problems? I want to illustrate this with an example.

If you want to know more about your ancestry, or you might want to know if you’re genetically more prone to certain health issues, there’s 23andMe – a FDA-cleared DNA genetics testing start-up firm. For around 200 USD, they can tell you everything you want to know about your health, traits, and ancestry, which is all based on your genes (Freakonomics Radio, 2019).

 

23andMe is a DNA Genetics Testing start-up in Mountain view, CA.

 

Well actually, your personalized report is based on the 23andMe DNA database. They match your DNA with everyone who has ever sent in their DNA sample. This database is currently filled with more than 10 million unique people (TheDNAgeek, 2019), supposedly adding to greater result-accuracy. However, the problem is that this database is predominately European-centric. In fact, 80% of all users are from European descent, implying low genetic diversity (Freakonomics, 2019). This is not necessarily a problem if you are white, but it does seem to discourage or even lower accessibility if you’re a person of color because you might wonder if your personalized 23andMe results are less precise.

This is not necessarily the fault of 23andMe, because the company relies on the DNA input of its users. But in order to increase accessibility for everyone, databases should be representative of all populations. Not only in the case of genetic testing, but in all parts of our society in which we use information-based technologies to solve problems. From applications that use face recognition to machine learning models that help determine what advertisements we get to see.

Technology is made by humans. Their ideas, values, and views are expressed in their work, which have serious impact on the people using these technologies (Blauw, 2019). How do we ensure that the people who create our solutions, do so in an unbiased way? I’d like to know what you guys think. Thanks.

I was inspired to write this blog by Sanne Blauw, a reporter at the Correspondent. She wrote an interesting article about the people behind artificial intelligence. If you’re interested, I’ve included a link below. She also made a podcast, if you’re more into that.

 

Sanne’s article (De Correspondent): decorrespondent.nl/10589/kunstmatige-intelligentie-is-menselijker-dan-het-lijkt-wie-zitten-erachter/154098688546-984c0d3d

Sanne’s (15 min) podcasts: open.spotify.com/episode/2dnsWAa4IxvKqDS1YfYdm4?si=-_lNaYUOTliLC9XSswUwdA

References

Freakonomics Radio. (2019). 23andMe (and You, and Everyone Else). Stephen, J. Dubner/Freakonomics Radio. Retrieved from: https://medium.com/s/freakonomicsradio/23andme-and-you-and-everyone-else-18ab5941c95d

TheDNAgeek. (2019). 23andMe Has More Than 10 Million Customers. Retrieved from: https://thednageek.com/23andme-has-more-than-10-million-customers/

Blauw, S. (2019). Kunstmatige intelligentie is menselijker dan het lijkt. Wie zitten erachter? De Correspondent. Retrieved from: decorrespondent.nl/10589/kunstmatige-intelligentie-is-menselijker-dan-het-lijkt-wie-zitten-erachter/154098688546-984c0d3d

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