New technologies are enabling the creation of new forms and high quantities of data that can inform policy-making processes, improving the effectiveness and ip camera efficiency of public policy and administration. However, inaccuracies can exist in the data used – either because data is not regularly updated, relates only to a sample of the population, or lacks contextual analysis. A recurring criticism of big data and its use to analyse socio-economic trends for the purpose of developing policies and programmes is the fact that the big data collected does not necessarily represent those towards whom these policies are targeted. The collection of data may itself be exclusionary when it only relates to users of a certain service (health care, social benefits), platforms (i.e. Facebook users, Twitter account holders, etc.) or other grouping (i.e. online shoppers, loyalty card members of airlines, supermarkets, etc.) In the developing world, only 31 per cent of the population is online, 63 in 100 inhabitants have a mobile phone and 11 per cent have access to mobile-broadband. Ninety per cent of the 1.1 billion households that are not connected to the Internet are located surveillance camera[/URL in the developing world. Some countries in Africa have less than 10 per cent of their population active on the internet. This means whole populations can be excluded in data-based decision-making processes. So what must be done? As noted by Linnet Taylor, researcher at the Oxford Internet Institute working on a project about big data and its meaning for the social sciences, a quick analysis of the big data discourse reveals a clear double standard: There is a certain irony here: 90% of the discussion at the forum[URL=http://www.ipcctvcamera.net]wifi ip camera referred to big data as a tool for 8 channel dvr surveillance, whereas the thread of debate that focused on developing countries alone, treated it as a way to ‘observe’ the poor in order to remedy poverty”.
Post je objavljen 24.08.2014. u 10:23 sati.