Author Archives: Ton Zijlstra

First TTN Enschede Meet-Up A Success

Last Thursday the first TTN Enschede Meet-up was held. The Things Network (TTN) is an open infrastructure, using LoRaWan, which lets Internet of Things (IoT) devices communicate data to the cloud, from which it can be approached over regular internet connections.

What fascinates me in this, is that one can implement a city or region wide infrastructure for very little money, where normally the infrastructure is the expensive part. Especially after the TTN Amsterdam initiators ran a kickstarter campaign offering the gateways for just 200 Euro, last October. With several volunteers here in Enschede, we can quickly achieve city wide coverage, and open it up to all comers. And that is what is indeed happening, as it looks like at least 6 gateways will become available in the city soon. One gateway, which Timothy at Innovalor placed on top of the highrise of the University of Applied Sciences Saxion in the city center, is already operational, since last week. The rest will follow in June.

The meeting last Thursday of fifteen TTN and IoT interested people in Enschede was a good first encounter. Besides getting to know eachother, it was good to exchange ideas, experiences, and talk about what we could actually do once the infrastructure is in place.

As it turns out, thinking about use cases is not easy, and that will definitely need more thought and discussion.

Meanwhile one of the participants, JP, showed his LoRaWan device that measures signal strength of the mentioned gateway. On his mobile phone he combines those measurements with his phone’s GPS location. This way he built a signal strength map of the Saxion gateway while cycling around town over the course of his normal activities. The LoRaWan receiver and the map are shown below. As it turns out more people are currently doing this type of wardriving, trying to crowdsource a coverage map of the Netherlands.

LoRaWan wardriving results Enschede

Our family name and open archives

In the 1980’s my dad spent many days searching paper archives to reconstruct his paternal family tree. I am going through some of his archives now that we are dissolving my parents household. What was hard work then, now after digitisation, is often available online.

Regional archives have done a lot of work to digitize records of birth, marriage, and death, and make them searchable online. Through the website allefriezen.nl (all Frisians dot nl) one can search for documents by name. The picture below (archive source) is the registration of our family name on 20 February 1812. This was under Napoleonic rule when France had annexed the Netherlands (1810-1814) and family names became compulsory.

Popke Jacobs the great-grandfather of my grandfather registered our name in the “Municipality Ureterp, Canton Beetsterzwaag, Arondissement Heerenveen, Departement Vriesland” (sic). It is weird to see those French government structures in the document.

aannamezijlstra

The full text reads:

“Before us Maire (mayor) of the Municipality Ureterp, Canton Beetsterzwaag, Arondissement Heerenveen, Departement Vriesland, having appeared Popke Jacobs, living in Ureterp, has himself declared that he adopts the name of Zijlstra as family name and has the following number of sons and daughters, to know, Jakob, old 18 years, living in Grouw. Klaas old ten years, Jan old one in his second year, both living in Ureterp, Geeske old 17 years, living in Drachten, Aukjen old 15 years living on the Groote Gast and Trijntje old 13 years living in Ureterp and has signed this with us 20 February 1812.”

It is interesting to note that my ancestor signed his own name, so he was literate. Others registered in the same document signed with a shaky “X”. His occupation was listed as “worker”, meaning he was a hired hand and day laborer.

Open Communities / Refugeehack Wuppertal

Last November I attended the yearly Open Communities North-Rhine Westphalia barcamp (OKNRW), which was combined with a hackday called #refugeehack. The latter focused on using open data to help refugees find their way in Germany.

I presented my experiences working with local governments to help them use open data as a policy instrument. We did a year long project with 9 municipalities and 1 province in 2014-2015. The driving thought behind it was that releasing data can be a deliberate intervention in a policy field, as having data in my hands changes a stakeholder’s agency. Slides shown below.

Now a video, showing how the OKNRW 2015 & Refugeehack played out has been released (in German).

When Governments Don’t Walk the Talk

Last fall the European open data portal project published two reports. One on the potential economic value of open data in Europe, the other taking a look at the maturity of open data efforts in European countries.

Both reports contain interesting insights and conclusions.
Both reports are also useless.

Because the data underneath the reports has not been published. Without explanation.

That is of course rather surprising because the subject of the reports is open data. At least when the topic is openness, all the related material should be open. That is why, when we built the EU PSI Scoreboard in 2011, we published all the underlying data right alongside the scoreboard. As does the Open Data Barometer. As does the Open Data Index. As does the Digital Agenda Scoreboard. But not the European Open Data Portal project. I would have expected the data under both reports by the European Open Data Portal to actually be available in the European Open Data Portal.

Missing data destroys the report’s value
Not having the data renders the report on open data maturity useless:

  • it makes interpretation of the conclusions impossible, as there is no way to see if the assertions chime with the collected data, nor if that data chimes with ones own experience in the field
  • it makes any meaningful discussion about the merits of the report impossible, even where it gives rise to questions (such as, what makes Bulgaria an open data trendsetter?)
  • it makes formulating actions aimed at improvement impossible, as the data to determine what improvements can be made are not available

Thus after reading the report nobody is, nor can they be, any the wiser as to how to move forward.

Cold feet
I approached the European Commission, and through them the authors, to request the data. After a few messages back and forth, the reason that the data is not published became clear: the national representatives involved in the project, such as the members of the EU PSI Group, have witheld publication of the data. I assume because of cold feet and dreading actual comparison between countries. Not publishing the data however, even if not intended as such, is also sending a clear message: “we’re not serious about openness.” The verdict when it comes to European open data maturity therefore is likely “not very mature”.

Requesting data per country needed
A very few countries may pro-actively publish the data about themselves, but most will not. To obtain the data used for the open data maturity report, it is now needed to approach all the national government representatives involved and request the data from them.

Which I intend to do. Help is welcome. [UPDATE: I have approached most of the governments involved, to ask for the information that could make the maturity report actually useful.]

Closed
Off to get some closed data

The Utility of Tags

Earlier this week I came across a Lifehacker posting “Get a Better Creative Workflow in Evernote by Ditching Tags” by Melanie Pinola, quoting Tiago Forte who’s into productivity, which proposes one might as well get rid of tags in Evernote because :

  • “When you rely heavily on tags, you have to perfectly recall every single tag you’ve ever used, and exactly how it is spelled and punctuated.”
  • “The real problem with tags, and why they not only fail to help, but actually even hurt people’s creative self-esteem, is that they give the impression that keeping a useful collection of personal notes requires nothing less than a heroic feat of comprehensive planning, followed by years of meticulous, unwavering cataloging and annotating”

This does not make much sense to me at all. For me tags are a key ingredient in provoking serendipity, as well as a navigational aid. Both play a strong role in my creativity process. If you think tags limit your creativity, I think it is likely because of how you use tags.

Tags vs Categories
It seems both Forte and Pinola see tags as categories. Tags aren’t categories. Yes, categories do require you have a good understanding of how they are organized, and need you to stick with it thoroughly, as otherwise everything ends up in the ‘miscellaneous basket.’ Categories are things you make up before you start categorizing. Tags work the other way around: you add tags to things as you go along. Over time a structure may emerge from the tags which you could adopt as categories, but that isn’t the purpose of tagging. With tags everything starts out as miscellaneous. This key difference is the difference between approaching information from a hierarchical perspective (categories) and from a connected perspective (tags). In the networked age, Everything Is Miscellaneous, as David Weinberger put forth in 2007.

Categories in Evernote
Evernote has no explicit categories functionality, but allows you to work with categories in 2 ways.

  • One is dividing your notes in different notebooks. This is something you can use for fixed and mutually exclusive categories. I have different notebooks for different areas of responsibility.
  • The other is using the tagging functionality. These can be used for non-exclusive categories (as a note cannot be in more than 1 notebook at the same time, but can be in several categories). I use tags like this as categories as well, for instance to indicate project status, or that a note is related to a specific project. However those tags as categories are just a small part of the tags I use.

How I add tags (e.g. in Evernote)
My tags do not form a structure of categories / a taxonomy. They are reflective of my associations with a piece of information. I add tags to capture what a piece of information means to me, what I associate it with, or how I might use it. All of this in a non-prescribed way, and not as a ‘must’ either. There’s plenty of stuff I don’t tag at all, and there is no planned consistency in my tagging. It simply evolves with my own internal dialogue and idiom (something I would have tagged socialsoftware in 2002, would maybe have been tagged socialmedia in 2009 and socmed in 2015).

Key here is that with my tags I do not try to capture what something is “objectively” about, like the echo of systematic categories, but why I saved it. A piece about an animal may be tagged with collaboration or with business_models based on the associations I had while reading it.

My tags may very well not be used or present in the information I tag with it. (In general if you ask people to tag stuff or title it based on what it means to them, there is a good chance they use words not present in the tagged information itself).

I also save material in about half a dozen languages, and then tagging is a way of connecting material together and make it findable in ways that full-text search cannot do, as search is monolingual.

There is likely a power-law distribution in my use of tags: most will get used maybe once or twice, some will get used heavily. The more heavily used ones, if I notice it as a pattern, can become a sort-of de facto category. So I don’t need to remember all my tags and how I used them, as suggested in the linked article above, I usually only remember the less than 10 I use frequently. I am not bothered if I don’t use them.

How tags help my creativity
There are two ways in which tagging aids my creativity.

The first is that it aids my serendipity. If I search my notes it surfaces things not only based on the content of those notes, but also on the associations I used as tags, and other words I used as tags that are not in the content itself. That way unexpected search results, but nevertheless relevant to or overlapping with my search question, can pop up. So that when I search e.g. for business models the example article about the animal I mentioned above will pop up. That way I find things I did not realize I was looking for.

The second is that tags allow me to navigate and pivot through my collected material. I see social software / networked tools as working in triangles (see my 2006 posting Social Software Works in Triangles).
Such a triangle is formed out of an information item (a Flickr photo, a Delicious bookmark, or indeed a note in Evernote), the person that created/shared it (in Evernote usually myself), and one or more descriptors (tags, locations etc.).
The point is that tags are not just descriptors, they are also turning points on the path through my data. These pivots or forks in the road, allow me to hop-step-jump from an article to other things within the same context through a tag, like another article, and then through to the author of it and maybe onwards to one of their other writings, to somebody’s bookmark collection of which it is a part, to that person’s blog etc.
It allows for navigation and triangulation that way, bringing me places I didn’t know about. That is a richness in association, multiple viewpoints etc, that a category system cannot produce. ( I even dreamt about tags and pivots once, in 2007)

So, don’t ditch tags because they cramp your style. Uncramp your style so you can use tags fruitfully.

Are Boarding Pass Barcodes Scary Or Not?

In various FB-feeds I see people posting warnings about not throwing away your boarding pass or showing it to others before you’ve returned home. This all because the barcodes on your boarding pass supposedly contain ‘all your personal information’ which hackers can then steal by scanning.

Sounds scary right, evil hackers having scanning apps and getting your personal information?

Well, there’s nothing scary about bar code scanners, you can download any number of them (Android, iOS). And if you do, you can scan your own boarding pass, just like the ominous hypothetical hacker in the video!

When you do that you realize: there is usually nothing in that barcode, that is not already printed on the boarding pass itself for all to read in clear text. So if you weren’t worried before that the info on your boarding pass might be useful to someone else, the barcode does not change that.

Taking a look at my own boarding passes
Here are two of my recent boarding passes.
Please note that the first boarding pass is an exception: usually the airline keeps the large part, that contains the barcode, when you board. In other cases such as self-printed boarding passes that’s not the case.
I scanned them with my phone, to reveal the information that the barcode contains.

boardingpass1 Scanned boarding pass 2
boarding pass, and scanned barcode

As you can see the barcode reveals:
M1ZIJLSTRA/ANTONARNOLDE CDGAMSAF 1640 343Y015F0048 147>1181OO5343BEY 2979690574758 0

You can find the standard used for boarding pass barcodes from the International Air Transport Association (IATA). The UN Agency ICAO has a (2009) version of that bpbc standard (PDF) available online. I have used page 39 for reference.

Let’s compare the contents of the barcode with what is already visible on the boarding pass. The barcode reads:

M: format code
1: 1 leg of my trip is on this boarding pass
ZIJLSTRA>ANTONARNOLD: my name
E: ticket electronically issued
CDGAMS: flight from CDG (Paris Charles de Gaulle) to Amsterdam
AF: Air France
1640: flight number
343: date (Julian calendar), 9 December
Y: Economy class
015F: my seat
0048: my check-in number
1: passenger status
47: Field size of following variable size field
>: beginning of version number
1: version number
18: size of following structured message
1: passenger description
OO5: Source of check-in, source of boarding pass issuance
343: date of issue of boarding pass, 9 December
B: document type (boarding pass)
EY:airline designator for boarding pass issuer
29: field size of following message
79690574758: airline numeric code (7) and document serial number (ticket number)
0: selectee indicator

All of this is also on the boarding pass.

Boarding pass comparison

Interestingly some readable information on the boarding pass itself, a reference number (BEG4AP) is not in the barcode. This however is the one piece of info, in combination with my name, that could be used before a flight, e.g. to change seating. So here the boarding pass contains more information than the barcode on it.

Let’s look at another boarding pass, a mobile boarding pass from another part of the same trip, Paris to Belgrade a few days earlier.

boarding2 Scanned boarding pass

Scanning the QR-code reveals
M1ZIJLSTRA/A E6Y933Y CDGBEGJU 0315 338Y014C0002
317>503 M0E05796905747580

What is noticable is that it does not give my first name (it does on the boarding pass itself) and it mentions a different airline and flight number (JU 0315) than the boarding pass itself (AF6292). This because it was a code share with JU 0315 the ‘real’ flight carrier and number.

Here the barcode does contain one piece of information that isn’t on the boarding pass: the booking reference 6Y933Y. With it and my name one could change my bookings for the other parts of the trip (such as return flights), before they were made. Both the booking reference and PNR number on the other boarding pass are only useful before flights have taken place. As they are short, 6 positions, they get recycled quickly afterwards.

Other boarding passes I had
I have checked several other boarding passes I had,from various airlines and flights. A lot have the booking reference printed on it (e.g. Easyjet). I noticed that Lufthansa encodes my frequent flier number into the barcode, which is not always on the boarding pass (although often it is, Malaysia Airlines prints my freq flier number on the boarding pass). This too is one piece of information that might be used, in combination with the booking reference or a weak password or PIN-code to log into your frequent flyer account. Much depends on how ‘easy’ your airline makes it for ‘you’, and thus for others. KLM does not encode my frequent flier number as far as I can tell, but usually I don’t add my frequent flier number to my bookings at the point of booking.

Summary
In summary, scanning your barcode does not expose ‘all your personal information’, usually just what is printed on your boarding pass already. Sometimes your booking reference is encoded and not on the boarding pass, and sometimes your frequent flier number is encoded and not on the boarding pass, But not always by far, often they are also printed on your boarding pass already.

Booking references can potentially be used to change aspects of your flights, which is a risk if parts of your booking are still in the future (such as return flights). Frequent flier numbers can be used to attempt to login to your profile at the airline, which can be a risk if your account is only guarded with a PIN number or a weak password. The weakness there is in the airline’s website.

So throwing away your boarding passes only after your entire trip is generally a good idea. But not because of the barcodes per se, because of the information that is usually already readable on it (reference codes and frequent flier numbers).

Oh and of course if you post a boarding pass somewhere and have made some information invisible, then don’t forget to also make the barcode unscannable as it contains the same information.

Looking Back On 2015: the Tadaa! List

As every year it is time to post the list of things that gave me a feeling of accomplishment, that made me go ‘tadaa!’. I am always very much forward focussed, which leads me to easily overlook the things I did, or how those things form a bigger whole. As a reminder I post this yearly list, triggered by my friend Ernst in 2010 (read the 2010, 2011, 2012, 2013, 2014 editions)

To be clear, 2015 was not a good year. We lost our first pregnancy and both my parents died. That is a lot to cope with, and it was what took most energy and attention. Nevertheless, plenty other things happened as well. These were the things (mostly professionally oriented) that stood out positively for me this year, in no particular order:

  • I spent time with both my parents, taking care of them and being with them in their final days, and with my sisters hopefully did right by them both.
  • Elmine and I spent a great month together in Lucca after a spring that started out hopeful and then saw those hopes dashed. It is wondrous how just being together heals us both, always. (week 1, 2, 3, 4, 5)
  • Lucca Firenze
    In Lucca and Firenze

  • Took time for events and projects, just because it was something I wanted to do for myself out of curiosity. Gave myself the luxury of just attending some events, without speaking or actively contributing there. (Went to BorderSessions, OKNRW, ThingsCon and joined the Things Network)
  • Worked with great people in Serbia in June and December on bringing open data forward.
  • Joined the Big Data Advisory Panel of the government of Malaysia, which likely will turn into renewed visits in 2016.
  • Treated Elmine to a fun weekend together in Rotterdam to celebrate her birthday, and gave her a painting as present.
  • Gradisca Düsseldorf
    Hanging out with friends in Gradisca (I) and Düsseldorf (D)

  • Had friends be there for me (thank you!), got to be there for friends
  • Returned twice to Kyrgyzstan to follow-up and present my work of last year, including visiting the beautiful lake Issyk-Kul beneath the towering mountains for a hackathon.
  • Issyk-Kul Driving from Issyk-Kul to Bishkek

  • Worked in Belgium, Germany, Netherlands, Italy, Switzerland, Finland, Kyrgyzstan, Malaysia and Serbia this year, allowing me to experience a wide variety of people and perspectives to inspire and inform my work.
  • Found much better words to express what unifies my work and activities. Agency of individuals in the contexts of their communities is the summary. Hopefully much more on that in 2016.
  • Started self-reflection through collecting my own daily stories for pattern detection, dubbed self-pni.
  • Started working with Andre Golliez on shaping a national data infrastructure in Switzerland, moving from presenting at the Swiss national open data conference to funded research now.
  • Finished a great year-long and unique open data project with 10 local governments with a high-energy event together with my colleague Frank. It may be used as a template in the near future for other local governments in Europe.
  • Designed and implemented a new training program with my colleague Frank called ‘the data trip’ that lets civil servants use open data in their everyday work. (description in Dutch). Hopefully something we can repeat next year in other places.
  • PNH eind event maart 2014 PNH eind event maart 2014
    Frank and I doing our open data ‘dance’ (at the March ‘PNH Slimmer’ final event)

    PNH eind event maart 2014 Utrecht Data Trip oktober 2014
    Working with civil servants in North-Holland (in a year long program) and in Utrecht (for the Data Trip)

  • Hired a financial life planner to bring financial planning into the everyday toolbox for us, and align it with my other strategic choices and tools.
  • Read and summarized some 40 reports on the economic potential of open data to translate them to the Flemish and Belgian context. Boosting my own understanding of this space as well as providing the client with input for rigorous discussion and decision making.
  • Knowing there is enough to do lined up for 2016 already.

In 2015 I spent 88 days outside the country in 10 countries, though luckily just over half of that was together with Elmine. It is also less travel than previous years, or at least travel that was more efficiently planned. I worked 1941 hours, which is around 49 weeks full time equivalent. Given the month away in the summer, and the number of weeks I did not work after the summer due to family circumstances, it still means I have not succeeded in bringing my work load down to more healthy levels. This is the main challenge for 2016, and I’m looking to address it by hiring others more often so I get to focus on the tasks that suit me best.

I’m glad this year is over, although I don’t attach much symbolical value to arbitrary boundaries and counting systems like calendar years. In the coming days around New Year we’ll be spending time with dear friends in Switzerland. I’m looking forward to the next year. It is already shaping up to be a much more constructive year both personally and professionally. Here we go!

Rigi
Celebrating the new year from a Swiss lake shore

Open Data Readiness in Serbia

Last June I spent time in Serbia doing an open data readiness assessment for the World Bank. Early this month I returned to present the findings, and to mentor a number of teams at the first Serbian open data hackathon. The report I wrote is now also available online through the UNDP website.

odrareportthe printed ODRA report

The UNDP organized a conference to present the outcome of the readiness assessment and discuss next steps with stakeholders. At the conference I presented my findings to the Minister for Public Administration and Local Self Government (MPALSG), and a printed version was made available to all present.

ministerme conf1
(l) the minister (center, me left of her) on open data (photo Ministry PALSG), (r) discussing presented app datacentar.io (photo Hakaton.rs)

At the conference the 11 teams that created open data applications at the hackathon the weekend before, called Hakaton.rs, were also presented. The hackathon took place in the recently opened StartIT Centar, a coworking space (which got funded through kickstarter). I had the pleasure to be a mentor to the teams (together with Georges and Brett from Open Data Kosovo), to channel my experience with open data communities around Europe and open data app-building in the past 8 years. The quality of the results was I think impressive, and it was the first hackathon where I saw people trying to incorporate deep-learning tech. I aim to post separately on the different applications built.

mentorMentoring during the hackathon, with Milos and Nemanja. (photo Hakton.rs)

That the hackathon was about open data was possible because five public sector institutions (Ministry for Interior, Ministry of Education, Agency for Environmental Protection, Agency for Medicines and Medical Devices, and the Public Procurement Office) have been working constructively to publish data after our first visit in June. In the coming months I hope to return to Belgrade to provide further implementation support.

The report is also embedded below:

Serbia Open Data Readiness Assessment

Loracoverage

Building an IoT Infrastructure for My City

Earlier this year a group of Internet of Things enthusiasts in a month or so launched an open communication infrastructure across the entire city of Amsterdam, enabling anyone to let their IoT devices communicate. Without the need for 4G, Wifi or BT connections, it uses LoRaWan, which allows low bandwith but long range traffic, at low energy usage levels. They call it The Things Network.

Currently The Things Network is running a Kickstarter campaign to bring LoRaWan devices into the hands of more people, and thus create IoT infrastructure in more cities. The gateways on offer cost about 20% of what similar devices cost, and this is a great opportunity to implement a solid city wide infrastructure at very low cost. With an old fraternity friend, Ian Kennedy, we are now looking to create such an infrastructure for my hometown Enschede.

The Things Network from Soda Content on Vimeo.

Enschede is a town of about 160.000 people, and covering the city will require 3 or 4 gateways, to which nodes and devices can connect to communicate. Both Ian and I ordered a gateway through the Kickstarter campaign, and are now looking to connect to more people locally with an interest in IoT. Ideally one or two others will also fund a gateway, ensuring city wide coverage. The coverage between the two of us is shown in the image at the top, and as you can see especially the southern suburbs still need coverage. We will likely also reach out to companies and the city government to see who else is interested in experimenting with this new infrastructure. As delivery of the devices is scheduled for late spring next year, still a long time away, we have plenty of time to get the ball rolling before that.

Interested in making Enschede IoT ready? Join the newly created mailing list Things Enschede (running on my own mail server), and/or help create the infrastructure by adding hardware through the TheThingsNetwork Kickstarter campaign. We will aim to organize a meet-up in November to get local conversations going.

If there are a few others willing to join us, we will certainly add Enschede to the growing list of cities in the The Things Network community. UPDATE: Others are indeed also active, and have been arranging gateways too. That ensures we will have enough hardware to get city wide coverage up and running. Meanwhile a local Enschede community page has been opened, but not yet filled.

Why False Dilemmas Must Be Killed to Program Self-driving Cars

MIT Technology Review: Why self driving cars must be programmed to kill
An article popped up multiple times in my Facebook-stream in the past days, titled “Why self driving cars must be programmed to kill.”, published in the MIT Technology Review. I think the “impossible ethical dilemma” the article says it posits is false. I think saying that it needs to be solved “before they can become widespread” is even more wrong as the problems will be in the transition much more than in the new normal.

Google’s self-driving car
photo Saad Faruque

Autonomous cars will not become mainstream because they know what is the ‘morally right’ thing to do in screwed-up situations. They will be mainstream because they will not allow those screwed-up situations to arise. Unlike us. That is the point of self-driving cars: not to be like us drivers, but to be unlike us.

In fact self-driving cars will not be autonomous at all in the literal sense. They will be networked-driving. They will be autonomous only relative to the passenger formerly known as driver, but in synchronisation and negotiation with everything else.

Let’s look at the false dilemma first
The premise of the article is that a car ends up heading towards a group of ten people in the road and no time to stop. It then has to choose: run over those 10 people, killing them. Or drive into the wall on the side, killing the driver. Or alternatively driving into the same wall on the side, killing a child or a granny standing there on the sidewalk.

The first question here is not what the car software should do to figure out ‘the right thing’, as the article says however. The first question is, how on earth did a self driving car end up in a situation where it was ‘too late to stop’ at all? The article lamely explains how such a situation came up: “One day, while you are driving along, an unfortunate set of events causes the car to head toward a crowd of 10 people crossing the road. It cannot stop in time.” The solution however is in that lead-up that is not described.

The two key elements here that cars need to solve, so the ethical choice above need not be made at all, are:
1) preventing ‘unfortunate sets of events’ to arise in the first place
2) preventing it is ever ‘too late to stop’ by erring on the side of caution

Autonomous cars will not go where there is no data

The last one is a good example of how self-driving cars already are different from human drivers. If a human has insufficient data he will keep going on (I assume there are likely no obstacles on my road until I see otherwise). If a car has insufficient data it will slow down or stop (It won’t move until data tells it there is no obstacle to moving). Autonomous cars will not go where there is no data.

The first one, preventing an ‘unfortunate set of events’ requires more attention therefore, as it contains some assumptions to unpack. But the short answer is: it’s not just the car.

The car is not the sole unit of sensing, nor the sole source of data
There seems to be an underlying assumption in these discussions that the car is the only unit with sensors. There is no reason why that would be the case when autonomous traffic is widespread, or even before. Everything will have sensors.

Sensors are cheap or getting cheap fast. All cars have them, all phones have them, buildings have them, and realistically every road sign, lamp post, piece of road surface, piece of clothing can have them too. If they don’t already.

A self-driving car will be able, and needs to be able, to take in data from external data sources, to get a better understanding of its environment. Those external data sources can be anything and are already growing up in parallel to the self-driving car, ready to be used.

Lamp posts in the inner city of Eindhoven (Living Lab Stratumseind, link in Dutch) already monitor noise levels, crowd movement, and detect altercations. They can change light levels and color to influence passers-by. These lamp posts already are registering the 10 people from the dilemma above and their overall behaviour, and are able to tell your car before you come around the corner, allowing a car to reduce speed anticipating they will suddenly cross the road if their behaviour indicates such a thing. So it will stop in time, or avoid needing to stop at all.

All main roads in the Netherlands already know the number of vehicles passing by in each lane and their speed at any given time, and all that data is published on-line in real time. Those sensors already now are able to tell you whether you should be slowing down because traffic in front of you is denser or slower than you, well before you see their tail lights. Parking spaces along roads in various cities already know if they are occupied or in the process of being vacated. Intelligent Transportation Systems (ITS) in general are blanketing the EU road system in sensors.

Data pheromones, just like ants, will keep us from bumping into each other

The cars themselves will also be communicating and sharing sensor data. Allowing your car to ‘smell’ unexpected crowds of pedestrians blocks away, and navigate around it, with ‘data pheromones’.

Tesla cars already compare notes amongst eachother, and “work as a network“. Your own car already takes in satellite data every journey. Your own navigation software already shares your car’s behaviour with every other user of that software, to help detect detours, traffic speed changes, route changes, roadblocks and traffic jams. Beyond sharing descriptive data, any other machine actor could just as easily share intentions (“I will turn left in 250 meters, and slow down for it starting in 90 meters / 5 seconds”), allowing others to pre-emptively respond.

The omnipresence of data sources will only increase. The road surface can tell if it is covered in oil, water or ice, and slippery, and let the world know. Traffic lights already can tell what speed of approach will allow you to get through fastest and could let your car know. Where a human driver would try to run an orange light, an autonomous car would stop if it knows it would not influence the overall speed of its journey or that stopping would allow a ‘green wave’ in subsequent lights.
Even the phones of those 10 pedestrians in the original dilemma are able to detect and signal sudden changes in speed and direction, and soon sensors in their clothing or shoes might too.

When the roadsurface, lamp posts, phones and clothing, every car, or every other vehicle (bike, skateboard, moped) around you are part of the eyes and ears of your car, all to better navigate and negotiate passage, there will be no surprises. Surprises happen when you have just one range-limited sensor: the eyes of the driver.

The autonomous car software will take advice from anything around it, except your and my brainstem

An autonomous car is not autonomous really, other than freed from the driver’s control. It is driving on tracks just like existing driverless metro trains, except these tracks are made of data. Where those tracks run is continuously shifting based on all traffic actors continuously negotiating passage, and the signalled actions and intentions of every other actor.

The car will not be the sole unit of decision making either
Another faulty assumption I think is to see the car as sole unit of decision making. Just as anything around the car can be providing data, anything can also be an actor itself, forcing a response from ‘my’ car as it sees its environment changing. Every other vehicle, and immobile objects too, will make decisions.

Road surfaces can go beyond merely detecting they are slippery because of ice, so that cars decide to slow down, by actively declaring itself closed for the coming 23 minutes and 42.5 seconds while a salt truck is on its way there. Road signs, taking data from lamp posts about increased pedestrian activity can signal to change the road to one-way traffic or close it off until the crowd has dispersed.

Traffic will ride on tracks. Tracks made of data. Traffic rules will be fluid, and traffic flow emergent.

Sensors are cheap, and adding algorithms to each of them to act on its own sensor data is not much more expensive. Where traffic rides on tracks of data, the rules of traffic can be datafied too. Fluid traffic rules will result, and autonomous cars will obey them (and even if they don’t all other actors will see that in the data streams and adapt accordingly).

Saying the self-driving car is not autonomous other than from the previously needed driver, is not the same however as saying someone else or something else is at the helm. There no longer is a helm to be at. There is just traffic flow, emerging from the negotiated decisions from each actor continuously optimizing its journey by endless series of ‘probe, sense, respond’.

Existing ongoing analog trends will also play a role
Already in many cities around the world various types of traffic are separated into different streams. Separate lanes, or even separate routes altogether. Where that separation is not possible other measures (like speed reduction in residential streets) are usually taken. With all those things also becoming reflected in data, it will be even easier to do. It will also be much easier to locally change the primacy of the car in traffic design on the data level than in physical reality.

False dilemmas shift attention away from getting solutions faster
So the solution to the article’s ‘impossible dilemma’ is to not just look at the system ‘car with sensors and software’ but at both the other similar systems (cars, pedestrians, bicycles) around it, and at the super system it operates in (the road, built up environment, road design, traffic design) as well. The car will stop in time because the lamp posts, grandma’s coat, the road surface and every other sensing object will collaborate with it to there being no urgency at all.

So no ethical dilemma’s then? On the contrary!
While choosing to run over granny or crash into a group of ten other people is a false dilemma, there are many other real ethical dilemma’s to solve.

The article in MIT Technology Review suggested the false dilemma needs to be solved as a precondition of autonomous cars becoming normal. I think the period before those cars are normal will be much more challenging. When only a handful of cars are rational actors because they are autonomous from drivers, they will be experienced as weird and unpredictable by you and me who still have only our eyes to go by.

We’ve got 99 ethical problems, but killing granny ain’t one.

When we do get to mainstream, when traffic has become highly datafied, including street signs, lamp posts, road surfaces etc., there are many ethical dilemma’s as to who gets to influence the algorithms and data streams a car takes as input. Already in the US cars are being remotely shut down if their owners don’t pay their car loans on time. Should that be allowed? Can local government declare an entire neighbourhood a no-go area for specific groups of, or all, cars by having the roads tell the data layer they are closed? Can your insurance company tell my car to not do something? Do we even need insurance? Will individual car ownership still make sense, and if not, who then owns fleets? Can a lamp post be allowed to discriminate who gets to drive down the street (residents only!), or signal the police if it profiles a car as burglars? Can cars even be used by burglars anymore, because the cars know where they’ve been, and the lamp posts know which cars were there?

And right now, can we see, check and change the software in our cars? Can we see what type of algorithmic influences have been programmed in? No, I can’t, nor can I for most other sensing devices around me. Don’t you need to know how your current car, drive-by-wire as it already is, makes autonomous decisions? Already your Volkswagen autonomously decides from sensor data if it is on a test track or out on the road, and changes behaviour accordingly. Already John Deere tractors is ready to sue farmers for checking and altering the software on their tractors, basically arguing your tractor isn’t yours, you’ve only rented a license to an operating system.

So the conclusion of the article I fully share: we need an ethics of algorithms. Just not for deciding when it’s ok to run over granny.