Disrupting Big Media
How the power of open source investigation can disrupt the media, tackle disinformation and drive new revenue.
Bellingcat is an independent group of investigators and journalists who use open source and grey-market data aggregation to expose issues such as crimes against humanity and weapons proliferation. From their website, Bellingcat has 18 full time employees and around thirty independent contributors. The advantage of open-source intelligence is that it is publicly verifiable and publicly disclosable. Bellingcat publishes their data and methods so that anyone can recreate their investigations. Amongst others, Bellingcat has exposed Russian military involvement in the downing of commercial airlines MH17, Russian intelligence involvement in the poisoning of Sergey Skripal, Syrian regime war-crimes, and billions of dollars of money laundering through Scottish Limited Partnerships.
Bellingcat relies on grey-market data-sources, social media scraping and often manual analysis. They are mostly funded from donors and by selling investigative courses. The achievements of Bellingcat have been astonishing, but they have not, perhaps through a conscious decision, made progress in commercializing their business to help them scale. There are significant near-term opportunities in open-source investigation via data aggregation. 5G linked IOT devices will see a proliferation of available data and cloud computing and automation will democratize capabilities which were previously only available to governments and multi-national corporations.
To create value, Bellingcat could pivot to a business model of selling Data and Investigation as a Service to media organizations. Mainstream media has made some advances, but the origin of most of their content is still in traditional journalism. Big media has, however, innovated in content delivery by harnessing the power of apps, online ads, streaming, and, to an extent, social media delivery. There would be a symbiotic partnership between big media, with their reach and ability to deliver information, and the power of a scaled and automated Bellingcat. There would be an efficiency in keep these essentially distinct endeavors apart to allow for specialism and skills focus. Moreover, it would free traditional media from some of the liabilities of handling data.
In the value chain, Bellingcat could handle data collection, data processing and analysis, story identification, linguistic translation, and fact-checking. Traditional media would focus on content delivery, formatting and style, advertising, customer analytics and customer demand.
Challenges to be addressed include 1) overcoming the disruption of a traditional media model in which companies both produce and disseminate content, 2) legal liabilities when incorrect information was published (which could be addressed contractually), 3) resistance from those within the organizations who already do this work, and 4) maintaining compliance with privacy regulations such as GDPR when accessing future data. The result would be a news service which was transparent, publicly verifiable, and more attuned to customer demand. This would drive down disinformation, increase trust and therefore increase revenue.
Iain – thanks for a super interesting post! Before reading this article, I would have never thought that using big data or data analytics would be either useful or efficient as a resource for investigative journalism. I am curious as to how much this practice has caught on and for what purposes / sectors more broadly. I’m also curious as to how readers would be able to verify the sources and analysis given that there is a bit of a “black box” nature to these analyses. Thanks for sharing!