The truth at any cost lowers all other costs — curated by former US spy Robert David Steele.
The Best of iRevolution in 2013
iRevolution crossed the 1 million hits mark in 2013, so big thanks to iRevolution readers for spending time here during the past 12 months. This year also saw close to 150 new blog posts published on iRevolution. Here is a short selection of the Top 15 iRevolution posts of 2013:
ANALYSIS: Circular and sharing, when two become one?
If there is one thing the sustainability movement appears to want ownership of, it is the word ‘economy'. A circular version has been doing the rounds for some time, but it could be under threat from a new kid on the block, equally as caring, but perhaps, well, more sharing.
A circular economy. Or a sharing economy. Which would you put your money on? The first would claim to have more gravitas as it involves a seismic shift in not only how business works, but how resources are utilised. It is also potentially worth big bucks to corporations – hundreds of billions within the EU alone, according to the Ellen MacArthur Foundation. Some would also argue that a true sharing economy could not exist unless a circular economy was already in place.
Continue reading “Jean Lievens: The Circular Sharing Economy — Profitable Beyond Measure?”
I’ve been invited to give a “very provocative talk” on what humanitarian response will look like in 2025 for the annual Global Policy Forum organized by the UN Office for the Coordination of Humanitarian Affairs (OCHA) in New York. I first explored this question in early 2012 and my colleague Andrej Verity recently wrote up this intriguing piece on the topic, which I highly recommend; intriguing because he focuses a lot on the future of the pre-deployment process, which is often overlooked.
Continue reading “Patrick Meier: Humanitarian Response in 2025”
Forget about Growth Hacking, the future is in the Collaborative Economy
VIDEO
Anyone working in digital can somewhat relate to the overuse of loosely defined marketing words – think ‘big data’ or ‘cloud computing’ (bzzzz). Growth hacking seems to be just another one of them.
In colloquial terms, growth hacking is associated with the exploitation of loopholes and the use of illegal techniques online to grow business development. Of course, in some cases this has been reality. When PayPal was first used on eBay, it was actually breaching the retailer’s T&C’s. Similarly, when Airbnb first started they poached their customers from Craigslist by spamming listings and inviting users to join their directory instead.
However, growth hacking can also simply be described as the ingenious use of tools, platforms and environments for business development, online AND offline – Google campus in East London, for example, is a good case of growth hacking taking place offline as start-ups use a shared working environment to maximise their potential. Online, growth hacking is the use of tracking and metric tools that teach us where our time is best spent; and the leveraging of platforms where target audiences and key players are.
‘Hacking’ does not necessarily equal to detrimental consequences for larger corporations either. Indeed, Paypal was then bought by eBay, and when Airbnb developed its interface it added the option to ‘post to Craigslist’.
Live Crisis Map of Disaster Damage Reported on Social Media
Digital humanitarian volunteers have been busing tagging images posted to social media in the aftermath of Typhoon Yolanda. More specifically, they’ve been using the new MicroMappers ImageClicker to rate the level of damage they see in each image. Thus far, they have clicked over 7,000 images. Those that are tagged as “Mild” and “Severe” damage are then geolocated by members of the Standby Volunteer Task Force (SBTF) who have partnered with GISCorps and ESRI to create this live Crisis Map of the disaster damage tagged using the ImageClicker. The map takes a few second to load, so please be patient.
The more pictures are clicked using the ImageClicker, the more populated this crisis map will become. So please help out if you have a few seconds to spare—that’s really all it takes to click an image. If there are no picture left to click or the system is temporarily offline, then please come back a while later as we’re uploading images around the clock. And feel free to join our list-serve in the meantime if you wish to be notified when humanitarian organizations need your help in the future. No prior experience or training necessary. Anyone who knows how to use a computer mouse can become a digital humanitarian.
The SBTF, GISCorps and ESRI are members of the Digital Humanitarian Network (DHN), which my colleague Andrej Verity and I co-founded last year. The DHN serves as the official interface for direct collaboration between traditional “brick-and-mortar” humanitarian organizations and highly skilled digital volunteer networks. The SBTF Yolanda Team, spearheaded by my colleague Justine Mackinnon, for example, has also produced this map based on the triangulated results of the TweetClicker:
There’s a lot of hype around the use of new technologies and social media for disaster response. So I want to be clear that our digital humanitarian operations in the Philippines have not been perfect. This means that we’re learning (a lot) by doing (a lot). Such is the nature of innovation. We don’t have the luxury of locking ourselves up in a lab for a year to build the ultimate humanitarian technology platform. This means we have to work extra, extra hard when deploying new platforms during major disasters—because not only do we do our very best to carry out Plan A, but we often have to carry out Plans B and C in parallel just in case Plan A doesn’t pan out. Perhaps Samuel Beckett summed it up best: “Ever tried. Ever failed. No matter. Try Again. Fail again. Fail better.”
Digital Humanitarians: From Haiti Earthquake to Typhoon Yolanda
We’ve been able to process and make sense of a quarter of a million tweets in the aftermath of Typhoon Yolanda. Using both AIDR (still under development) and Twitris, we were able to collect these tweets in real-time and use automated algorithms to filter for both relevancy and uniqueness. The resulting ~55,000 tweets were then uploaded to MicroMappers (still under development). Digital volunteers from the world over used this humanitarian technology platform to tag tweets and now images from the disaster (click image below to enlarge). At one point, volunteers tagged some 1,500 tweets in just 10 minutes. In parallel, we used machine learning classifiers to automatically identify tweets referring to both urgent needs and offers of help. In sum, the response to Typhoon Yolanda is the first to make full use of advanced computing, i.e., both human computing and machine computing to make sense of Big (Crisis) Data.
We’ve come a long way since the tragic Haiti Earthquake. There was no way we would’ve been able to pull off the above with the Ushahidi platform. We weren’t able to keep up with even a few thousand tweets a day back then, not to mention images. (Incidentally, MicroMappers can also be used to tag SMS). Furthermore, we had no trained volunteers on standby back when the quake struck. Today, not only do we have a highly experienced network of volunteers from the Standby Volunteer Task Force (SBTF) who serve as first (digital) responders, we also have an ecosystem of volunteers from the Digital Humanitarian Network (DHN). In the case of Typhoon Yolanda, we also had a formal partner, the UN Office for the Coordination of Humanitarian Affairs (OCHA), that officially requested digital humanitarian support. In other words, our efforts are directly in response to clearly articulated information needs. In contrast, the response to Haiti was “supply based” in that we simply pushed out all information that we figured might be of use to humanitarian responders. We did not have a formal partner from the humanitarian sector going into the Haiti operation.
What this new digital humanitarian operation makes clear is that preparedness, partnerships & appropriate humanitarian technology go a long way to ensuring that our efforts as digital humanitarians add value to the field-based operations in disaster zones. The above Prezi by SBTF co-founder Anahi (click on the image to launch the presentation) gives an excellent overview of how these digital humanitarian efforts are being coordinated in response to Yolanda.
While there are many differences between the digital response to Haiti and Yolanda, several key similarities have also emerged. First, neither was perfect, meaning that we learned a lot in both deployments; taking a few steps forward, then a few steps back. Such is the path of innovation, learning by doing. Second, like our use of Skype in Haiti, there’s no way we could do this digital response work without Skype. Third, our operations were affected by telecommunications going offline in the hardest hit areas. We saw an 18.7% drop in relevant tweets on Saturday compared to the day before, for example. Fourth, while the (very) new technologies we are deploying are promising, they are still under development and have a long way to go. Fifth, the biggest heroes in response to Haiti were the volunteers—both from the Haitian Diaspora and beyond. The same is true of Yolanda, with hundreds of volunteers from the world over (including the Philippines and the Diaspora) mobilizing online to offer assistance.
A Filipino humanitarian worker in Quezon City, Philippines, for example, is volunteering her time on MicroMappers. As is customer care advisor from Eurostar in the UK and a fire officer from Belgium who recruited his uniformed colleagues to join the clicking. We have other volunteer Clickers from Makati (Philippines), Cape Town (South Africa), Canberra & Gold Coast (Australia), Berkeley, Brooklyn, Citrus Heights & Hinesburg (US), Kamloops (Canada), Paris & Marcoussis (France), Geneva (Switzerland), Sevilla (Spain), Den Haag (Holland), Munich (Germany) and Stokkermarke (Denmark) to name just a few! So this is as much a human story is it is one about technology. This is why online communities like MicroMappers are important. So please join our list-serve if you want to be notified when humanitarian organizations need your help.
Big Data & Disaster Response: Even More Wrong Assumptions
“Arguing that Big Data isn’t all it’s cracked up to be is a straw man, pure and simple—because no one should think it’s magic to begin with.” Since citing this point in my previous post on Big Data for Disaster Response: A List of Wrong Assumptions, I’ve come across more mischaracterizations of Big (Crisis) Data. Most of these fallacies originate from the Ivory Towers; from social scientists who have carried out one or two studies on the use of social media during disasters and repeat their findings ad nauseam as if their conclusions are the final word on a very new area of research.
The mischaracterization of “Big Data and Sample Bias”, for example, typically arises when academics point out that marginalized communities do not have access to social media. First things first: I highly recommend reading “Big Data and Its Exclusions,” published by Stanford Law Review. While the piece does not address Big Crisis Data, it is nevertheless instructive when thinking about social media for emergency management. Secondly, identifying who “speaks” (and who does not speak) on social media during humanitarian crises is of course imperative, but that’s exactly why the argument about sample bias is such a straw man—all of my humanitarian colleagues know full well that social media reports are not representative. They live in the real world where the vast majority of data they have access to is unrepresentative and imperfect—hence the importance of drawing on as many sources as possible, including social media. Random sampling during disasters is a Quixotic luxury, which explains why humanitarian colleagues seek “good enough” data and methods.
Continue reading “Patrick Meier: Big Data & Disaster Response: Even More Wrong Assumptions”
