Crowd Sourcing Maps in the Wake of Typhoon Haiyan

The Red Cross and the UN Office for Coordination of Humanitarian Affairs are on the ground in the Philippines after typhoon Haiyan. An urgent need? Understanding the lay of the land.  Which streets are usable?  What buildings are still there, and which ones have collapsed?  OpenStreetMap – the wikipedia of the mapping world, is stepping into the breach – providing a platform to crowdsource an up-to-the-minute picture of the situation on the ground.

Typhoon Haiyan - OpenStreetMap Changes

 

As of today, over 700 people have contributed over a million and a half changes to the shared map of the ground (update: as of 9  December the numbers stand at 1618 people and 4.4 million changes. Click the link to see the current stats.) To make the information accessible to aid workers, the Humanitarian OpenStreetMap team is releasing daily exports for GPS devices and other information systems.

OpenStreetMap has been involved in helping in humanitarian crises before, but this is the first time they are doing so at the behest of the Red Cross themselves.  Updated satellite imagery may have been just as helpful as the crowd-sourced map.  Apparently, the DoD has that, and they’ve been telling the Red Cross where to focus their attention, but they haven’t yet released the images.  It’s not as easy to get ahold of eye-in-the-sky images as one might think, not even for the Red Cross.

What is the Medium?

Medium.com is working to remake online publishing.  Again.

Medium.com is a project of Ev Williams.  His creds for remaking media are impressive.  He was a co-founder of blog pioneer Blogger and then of micro-messaging pioneer Twitter. Both companies changed the way the world communicates.  Blogs turned every person into a publisher, and twitter wired up the global nervous system.

The rolls-royce domain name gives the site a primacy of placement, and telegraphs the scope of the founder’s ambition.  It’s reasonable to assume that Medium.com was a 6 figure, and perhaps a 7 figure, purchase.  We’re looking here at another bid to remake media.

“It’s not too late to rethink how online publishing works and build a system optimized for quality, rather than popularity. Where anyone can have a voice but where one has to earn the right to your attention. A system where people work together to make a difference, rather than merely compete for validation and recognition. A world where thought and craftsmanship is rewarded more than knee-jerk reactions.”

from Welcome to Medium

It’s hard to read “Medium.com” without recalling Marshall McLuhan’s seminal and concise teaching – “The Medium is the Message.”  McLuhan seemed to presage the birth of Twitter in particular when he spoke of the explosive impact of electronic media.  Instant information overthrows governments.  And more.

It’s that kind of understanding of the sensitive dependance on the structure of the medium that seems to be underlying the work of the company.  They’re creating a publishing system that aims to improve the quality of conversation, and they’re doing it from the medium on up.

Livehoods

Livehoods uses social media check-ins, mainly from Foursquare, to show the neighborhoods of a city as they are actually lived.

It’s a good idea, and decent execution, but once I scratched the surface, it just didn’t jive with my lived experience.

When I’m in Brooklyn, I happen to land at the intersection of three of their hoods. It’s true, these are three different neighborhoods culturally, and a preponderance of people probably see the lines on the Livehoods map as a psychological boundary. Still, my life takes me into all of them – I crash in one and work just over the line in the other, walking back and forth, dropping in to stores along the way. I’m betting that most people do something similar – either with two neighboring neighborhoods or on two (or more) ends of a subway line.

From another angle, there are pieces of a single hood that are very relevant to me, and other places, physically proximate, that might as well be on another planet. Coffee shop next door? relevant. Child and Family services next door? Not so much. But a coffee shop one hood over? Also relevant.

There are likely many neighborhoods coexisting in the same space, layered on top of each other. Some of those neighborhoods will overlap strongly, and some won’t overlap at all. Some neighborhoods may not even be physically contiguous – the neighborhood of fine-art goers, for example, or the neighborhood of frequent business travelers. Is the neighborhood of a car owner similar to the neighborhood of a bike-rider? How similar?

What this needs is a demographic or psycho-graphic axis of some-sort, or even cooler – demographic and psycho-graphic derived entirely from the check-in data itself.

The Filter Bubble’s Filter

Just came across a link to a TED talk by Eli Pariser in support of his new book – The Filter Bubble.

From watching the video, the argument is interesting.  In short, he claims that the big gateway sites – Google, Facebook, etc. are increasingly using algorithms to tailor information to their viewers, only showing them what they want to see and ‘hiding’ from them all other information, be it boring or unpleasant or disquieting or what-have-you.  Ultimately, he claims, this threatens the dream of the Internet as the great connector.  These algorithms, he claims, are in the same seat as the Newspaper editors of the 20′s, and need to be programmed to include the lessons learned from those times – editorial balance, etc.

From this short presentation, though, it looks to me like he does a lot of his own filtering of facts in order to set up this equivalence between the newspaper editors of the ’20s and the algorithms of today.  The biggest difference is that in the 20s, most people saw exactly 1 newspaper, and that’s how they got their picture of the world.  On the web, you choose your sources of info.  Most people have many, and everyone can have as many as they like.

The Internet is an information marketplace and a filter marketplace.  There are any number of different kinds of filters – each person decides which ones they use, and the market as a whole decides which ones become popular.  Moreover – even the big ‘fitlerers’ that he fingers – Google and Facebook – don’t block out any information.  You want to see what your conservative friends are up to?  Click on their pages.  Facebook’s response?  It’ll show you more about them.  Want to learn about any topic at all in Google?  Search for it.  Nothing’s hidden.

The argument here boils down to a claim that lazy people who aren’t interested should be given a default mix that has broader boundaries.  Yet, there’s no reason to claim that once a particular website / filter / presentation of information becomes popular it suddenly has to change it’s magic-mix that made it popular in order to make sure people get a a balanced picture.  If people want a balanced picture there is no barrier to them getting it, besides habit.  Why does any particular website have to be paternalistic about what info it shows its users?  “They want Justin Beiber, but we’ll give them Greek Philosophy.”  It’s silly.

Should a website make it’s filter explicit and adjustable?  If people want it, then there will be websites that do.  All the rules of open markets apply.

You don’t have to be a fanboy…

Pretty much every time I read Seth Godin, I get a good reminder to step outside of my narrow thinking and look broader.  It happened this time as well, but there’s one point I need to take issue with in his post on Senior Management.

It’s the Steve Jobs assessment that doesn’t sit well with me. You just don’t grab dominant market share in areas where you didn’t even have a footprint without having a deep understanding of how the market currently works.  It’s also misleading to claim the Apple has no significant online or social media presence.  iTunes doesn’t obey the rules of the open web, but it is certainly both an online and social destination.  By any metric you’d like to use, it’s one of the top destinations of the Internet.

Wave Hello to Web 3.0

My spider sense tells me that we’re looking at Web 3.0 on this one – the next big step up – and what could very well be a serious crimp in Facebook’s style. It’s a communication and collaboration platform. It’s open. It’s got an API. It’s open to community development. It’s got Google momentum and mass exposure to make it happen.

It’s email, it’s live chat, it’s a wiki, it drags and drops files from the desktop, it embeds itself everywhere. Garden walls comes down. And it’s open – it’s just the beginning. Think whiteboard, think document collaboration, think task tracking, think project management, think collective web browsing. Zing!

You can see a demo and dig deeper at the Google Wave Site. Mashable gives you a distillation.

My wheels are just starting to turn on this one…sensing big potential…bubble, bubble.

Getting My Geek Head Around Twitter

My brain balks at fully understanding Twitter. I feel as if I can understand other media – newsprint, TV, Wiki, whatever. Twitter feels to me as if it’s half born – as if we haven’t yet seen what this baby is going to do.

Global Social Message Bus



In essence, it’s the pure social network – no frills, hobbies, books I’ve read, pokes, movie reviews. It’s just nodes, directed connections, and the ability to pass messages along those connections.


Massive Messaging Anything Market



The power is multiplied when combined with URLs. Nodes, directed connections, and the ability to pass ANYTHING along those connections.

Neurons and Synapses – Rewire at Will



We’ve spoken for decades about electronic communication becoming the nervous system of the planet. This baby is laying it bare and bringing it out to the edges.

How do we judge truth in the Twitter age?

Massive messaging markets (3M?) are changing the game in news reporting. The generation of news is already a distributed and complex interweaving of parsed and recombined news streams – we can expect that to only grow and take on new forms. It will be staccato and rapid fire.

Living in what is arguably the most focused-on city in the world, I am well acquainted with how even reputable news outlets routinely slant their stories.  With tens of millions of news providers, all of whom adjust and filter what they report consciously or sub-consciously, how will we judge what is true?  How do we judge truth in the Twitter age?

Instinctively, we judge the reality of a message by how distributed and consistent the corroboration is from multiple sources.  This already is, and will continue to be, gamed by groups with targeted agendas.  Any group with a semblance of organization is busy flooding relevant forums with their message.

When the same message comes from varied quarters – people from many different backgrounds – it starts to earn believability.  But this too can be gamed. 

‘Witnessing’ has a certain power and weight – one who claims to have seen an event with their own eyes.  Yet, the claim is easy, how do I know it’s true?

A rare, but convincing, argument for the truth of a story is when it is propagated by someone with an explicitly contrary agenda – a story which is injurious to the teller. To even come to this evaluation, though, I need to be acquainted with the teller’s true leanings.

So tell me, how do you know when what you read is true?


Questions for Social Media Man


We teeter hysterically on the consequences of rumor
about President Eisenhower’s viscera.



These are Marshall McLuhan’s words (circa 1955) about the impact of electronic media on the human psyche and society.  Substitute ‘twitter’ for ‘teeter’ and virtually anything for Eisenhower and you have a compelling picture of the present age. Information moving instantaneously to all parts of the globe, he writes, is explosive. 

We can, and do, have world events pouring through us like electricity.  I can easily become a twitching, twittering nerve cell in a massive identity-robbing global network.

What are the emotional impacts of this for the individual?

Do we have a moral obligation to be present to all of this information – to feel it?

How can I live if I do not put up walls or selectively empathize?

Who do I become if I do put up walls and selectively empathize?

Why it’s hard to sell me on the Semantic Web – Part 3

This is the third in a series.  Part 1 covered the basics of the Semantic Web vision. Part 2 gave a brief overview of 3 problems in the way – all of them of a technical nature.  This post looks at a problem that is not just technical – Trust.

When it comes to computer agents answering questions for me, trust is an essential problem, not a technical one.  Whenever I ask a question and get an answer, I’m outsourcing trust.  I’m believing in the answer and in the source of that answer.  If I’m asking a computer, I’m trusting the computer and the results that it will return.

What’s Good to Eat Around Here?
If I’m asking a simple question like “where’s the nearest stop for the 17 bus”, there’s not much room for mistrust, but if the question is any more complex, trust becomes a serious issue.  Let’s say I’m asking the question – “Where is the nearest place I can get a good sandwich at a decent price?”  Of course there are issues of ontology, markup, and reasoning involved here (What’s qualifies as a sandwich?  Am I talking about food or construction supplies?  How does one determine ‘decent price’?  How does one define ‘nearest’?)  But let’s look at the one word which begs the trust question – good.

Nowadays, to find out if a restaurant has a good sandwich, I can hit a whole bunch of websites looking for reviews.  For each piece of information I see, I make a judgment about whether to trust that piece of information.  I’ll use all sorts of subtle and not-so-subtle clues to decide to trust or not.  I look at what site it’s on, what else the person there has posted, how they express themselves, whether it’s balanced, whether it uses criterion I value – ultimately, there’s an element of intuition to it.  When I ask my computer the question and the computer comes back with an answer, the decisions of trust are left to the computer. 

Is there a Doctor Nearby?
The word “good” begs the trust question directly, but the question comes up even in less opinion-oriented questions.   The computer’s entire concept of reality is taught to it by people.  Who do you trust to teach your computer about what exists?  To teach it what is consequential and what is not, what is worthy of mention and what is not, what is part of reality and what is not?    

Let’s keep it simple.  If I own a restaurant that serves wraps, and I know that most of the world searches for “sandwiches”, not “wraps”.  I’ll publish an ontology that says “A wrap is a sandwich (a really valuable sandwich)”. My competitor down the street, a standard deli, will publish an ontology that says “Wraps aren’t sandwiches, people looking for sandwiches don’t want wraps, and wraps aren’t worth anything.”  Which one does the computer trust?  Similar questions will come up in all domains – politics, economics, news, medicine, nutrition, etc.

If businesses know that I am searching through semantic agents, they’ll do everything they can to optimize their business to be discovered by semantic agents.  This includes, of course, declaring themselves as fit in as many ways as they possibly can. With computer agents returning information, we can expect this to be standard practice by any business looking to attract customers.

As soon as we farm off our question answering to an outside agent, we can’t avoid this problem.  The definitions of everything will still be up for great debate – only we will have abdicated our right to answer the question and entrusted it to our computers. 

Who do you Trust?
There may be a first light of a solution to this question in the social network. The social network provides an explicit declaration of who I trust.  The computer can tell me “You can believe this review, because someone you trust (or someone who they trust) posted it.” 

The current networks are far too limited to cover the broad range of issues that will come up.  I may be interested in something that none of my friends know anything about.  To broaden the footprint of trust, we may see the formation of societies of mutual trust.  They will collectively form a vision of reality and self police to insure the lack of misleading information.  There would have to be many of these, as my conception of reality may not jive with yours.  The same question will have different answers depending on the differing underlying assumptions and network of trust.

In Summary
So that’s a capsule of my thoughts on the Semantic Web.  We’re making slow progress on each of these questions, but the questions are big and the progress is incremental.  The “Semantic Web” is growing organically – don’t buy it when the next start-up tells you they are delivering it to your door.