On both sides of the Atlantic, governments, foundations, and companies are looking at how to solve the problem of online dis/misinformation. Some emphasize the demand side of the problem, believing it important to focus on consumer behavior and the use of media literacy and fact-checking. Some focus on legal remedies such as platform-liability and hate-speech laws as well as privacy protections. Meanwhile, others try to raise the quality of journalism and support local news in the hope that creating more reliable content will be a counterweight to the dis/misinformation found online.
In short, there are myriad solutions aimed at addressing the problem of online dis/misinformation. This study looks at one kind of fix: the small companies in the information ecosystem that use natural language processing as well as human intelligence to identify and, in some cases, block false or inflammatory content online. There are impediments to the success of this entrepreneurial approach, including the fact that disinformation detection by algorithms is complicated, it is hard to scale, and that it is unclear whether the platforms have an incentive to adopt such technology. It is very likely that platforms such as Facebook or Twitter—which already screen, block, and remove fake accounts and content—will copy the technology or will buy out the small firms for the skills of their staff and for their products in order to gain access to the AI needed for further screening.
This paper looks at thirteen such companies, most of which are building solutions to identify false information online through a combination of people and natural language processing. Nascent and not yet widespread, these businesses
– Anya Schiffrin, with introduction by Ellen P. GoodmanRead whole article …