When the authorities are pressed for time, or have no leads, perhaps the internet can help.
The search for the mysteriously missing Malaysian Airlines MH370 plane has led to a wide array of theories, opinions, and conflicting pieces of ‘evidence’ as to what happened, where the aircraft is, and why it vanished. While the physical search is being undertaken by a number of international police, military, and rescue services, now the average internet user can help too.
DigitalGlobe, a commercial vendor of space imagery and geospatial content, has uploaded 3,200 square kilometres of satellite footage to its crowdsourcing site, Tomnod, and is regularly adding more. Using the site, the public can tag images of interest which may be potential rafts, wreckage, oil slicks or other indicators of the plane’s whereabouts.
This is no new concept, as crowdsourcing information in a disaster responses is merely an extension of volunteer response work implemented in a digital way. In recent times, it has become more organised and structured due to the rise of social media and mobile technology, and even adopted and endorsed by official humanitarian organisation relief efforts.
Crowdsourcing disaster relief recently made headlines during the Boston Marathon bombing of 2013, where many people took it upon themselves to help propose bomber identities after analysing available footage of the event. Then there are more formalised efforts, such as those during the Philippines typhoon. The Humanitarian OpenStreetMap Team (HOT) is an example of an organisation officially tasked by authorities such as the Philippine Red Cross to setup crowd sourced assistance as soon as the impending typhoon was identified.
Although these crowdsourcing tools can bring extra information quickly, integrating them officially into disaster responses can be complex, and requires some review. Heralded as the new way to do police work, there are many positive aspects, but a variety of issues that must be addressed.
First is the ambiguity around privacy when releasing imagery of classified, non-censored areas, people and infrastructure. Of course, saving human life and preventing future harm is a priority, however there appears to be little consideration around who could gain access to satellite imagery and situation data in these instances, and any malicious use of these as a result.
Second is the scope for people to jump to conclusions or encourage bizarre theories. The general public is not trained forensically to identify perpetrators, discover crime evidence, or pinpoint potential leads. As such there are questions around the reliability and validity of crowdsourcing, particularly related to general crime events.
Last, another issue is around the sheer amount of crowdsourced information that could be generated by the public in a disaster. While sometimes useful, ‘bad’, inaccurate, or misleading information from the public can slow down response teams, as data must be reviewed by authorities before it can be properly acted upon.
In all, crowdsourcing during disasters can quickly discover and deliver critical information to relief efforts, and provide essential assistance to life saving operations. While there are many benefits to its use, as evidenced by its impact in recent disaster scenarios, there should be more formalised and critical evaluation of the best way to integrate it properly. The best practise use of crowdsourcing is yet to be determined, and as such, there is much untapped potential around ‘putting it to the crowd’.