Tag Archives: Erik Hersman

Make Mine Mobile

Now this is ninja. Erik has set up African Signals, a wiki to gather information about mobile networks in Africa. This is a great idea that will definitely benefit from a crowdsourced approach, and I hope that it builds into a vital resource for everybody working in Africa, private and public sector alike. It’s one of those ideas that seems so simple, but it’s unlikely any single person could put it together – but drawing on the expertise of people working around the continentcan achieve it fairly quickly and keep it updated more effectively. So what can we all do, Erik?

Your Job:

Find your country and enter whatever you know about your local costs, speeds and service levels for mobile phone operators and internet service providers (ISPs).

Take 5 minutes and jump see if you can add anything new, or if the info is correct. Then, tell your tech friends from that country too, share this. It’s a resource, something for you to give to and to take from. It is strengthened by your information, and I hope that you in turn will benefit from it too one day.

In similar vein, Steve Song has a table of SMS costs in Africa in 2008, drawn from the ITU Measuring the Information Society report – also worth checking out.

Compare and contrast

Alex Evans at Global Dashboard:

The point about Twitter and other social networking technologies is that in our hyper-networked age, we just haven’t yet had the time to develop the collective mechanisms to make sure that this awesome power to aggregate, to build positive feedback loops, is channelled safely.

Erik Hersman at The Ushahidi Blog:

Since we don’t believe there will ever be one tool that everyone uses for gathering information on global crisis, we see a future where a tool like Swift River aggregates data from tools such as the aforementioned Twitter, Ushahidi, Flickr, YouTube, local mobile and web social networks. At this point what you have is a whole lot of noise and very little signal as to what the value is of the data you’re seeing.

Anyone who has access to a computer (and possibly just a mobile phone in the future), can then go and rate information as it comes in. This is classic “crowdsourcing”, where the more people you have weighing in on any specific data point raises the probability of the finding the right answer. The information with greater veracity is highlighted and bubbles to the top, weighted also by proximity, severity and category of the incident.

The question is, how viable is a tool like Swift River as one of the “collective mechanisms” that Alex correctly identifies the need for? I think the Ushahidi developers are on an interesting track, but I think that there are limitationss to what crowdsourcing can achieve – not a problem when it’s a forum like Digg (for example) where the weight of numbers has a levelling effect on any individual distortions, and where the ratings are trivial.1 However I’m still waiting to be convinced about the value of crowdsourcing in an emergency, because it’s crowdsourcing of the type which Alex describes in his example of a potentially dangerous Twitter meme.