Opportunities and Challenges in Southeast Asia, 2019 (Bangkok, Thailand) 23 producing inequality and discrimination” (Hintz & Milan, 2018, p. 3943). The data representation of entities goes beyond individuals. Technological advances such as smart home applications enable us to build data models of homes to control their security and ambience; in smart cities there are sensors deployed or data collected in other ways to give us a treasure trove of data which can analyse and moderate traffic, air pollution, crime rates, and so on. Measurable characteristics and behaviour of physical entities are abstracted into data representations, enabling a multitide of usages with societal implications. Data protection, security, and privacy therefore becomes the centre of this set of digital rights, with the understanding that digital technologies enable efficient collection and analysis of data, to “good” and “bad” ends. While we will not dwell on philosophical questions of what good and bad are, there are certain baseline agreements. Bad data practices have been observed to include mass gathering of data without transparency and accountability (sometimes illegally and unethically) and the increased use of that data in algorithmic decision-making, which involves the masses but is often opaque and unaccountable. Good data practices, on the other hand, protect and promote human rights and social justice towards achieving sustainable development (Mann, Devitt, & Daly, 2019). The datafication of society has brought about implications at a global scale. For one, there is the use of data for surveillance both for the ends of corporate interests and state control. Surveillance capitalism (Zuboff, 2015) has emerged as a new form of market capitalism, set to surpass previous forms that were based on products and services, or financial markets and speculation. Zuboff explains that surveillance capitalism involves the following model: 1) companies push for more users and collect user data and data from users’ online behaviour, 2) the data is analysed through artificial intelligence (AI) and machine learning, 3) these analysis are converted into products that predict human behaviour, and 4) prediction products are refined into products that convert human behaviour. As can be imagined, the ability to change human behaviour is highly coveted, and can have many consequences ranging from making sales to fixing elections. Hintz & Milan (2018) flatly state that data-based surveillance is a brand of “Western” authoritarianism in the digital realm that is institutionalised in law and normalised in society through popular culture, with implications no less powerful than “classic” authoritarian practices in targetting civil society and democratic institutions. From a Southeast Asian perspective, some of the issues that were mentioned in the FGDs include the mass collection of citizen data through national identification and/or biometric systems, massive data breaches of citizen information, blanket and targetted digital surveillance, and the lack of public awareness of the importance of keeping their data safe and private. Data flows are transnational, as most popular services used are not local companies, with servers located all over the world. Respondents pointed out that users of the services have no control over their own data and how it is used by