Perspective Question for Today
Here’s my response:
Researchers seem to be quite optimistic about the burgeoning applications in data. In this article, Joshua Blumenstock described several studies that indicate prospects of data application in different fields. Based on the smartphone data collected from users, algorithms can evaluate the debt repayment condition of loan borrowers and sort out those who are eligible for online financial products. By analyzing the number of international calls in certain region, algorithm may tell which sections of an area do wealthier people live and where do people in need may accumulate. Humanitarian support may then be more promptly and accurately delivered. Analyzing people’s footprint may also help carrying out health intervention during epidemics, for instance, during COVID-19, if someone is tested positive, his or her recent travel route can be quietly tracked so that other who are potentially exposed may soon be acknowledged.
However, the limitations of such applications are not unimaginable. Firstly, compared with the vulnerable, the empowered are much more able to benefit from big data. For example, when people in severe poverty fail to repay their loans, they are likely to be trapped in these debts, which prevent them from further borrowing. Secondly, the flaws of new approached to obtain data are not thoroughly understood and the accuracy of algorithms will drop sharply over time. Besides, when dealing with large amounts of data from all over the world, a small part of those data representing the disadvantaged will be ignored, not to say people are required to possess smartphones and Facebook accounts before their data could be collected. Finally, data privacy is a huge concern. Private companies’ pursuit of profit and governments’ abuse of power make it difficult to guarantee users’ data privacy, so there’s still a long way to go in terms of regulation.
Ways to overcame these pitfalls are simple: validation, customization and collaboration. New data should be complemented to the old ones instead of replacing them. Decisions should be made accordingly to a region’s specific situation instead of base purely on information outputs made by algorithms. As for data regulation, efforts are needed to enhance collaboration among data scientists, governments, civil societies, development experts, private companies and people in the country.
Simply by holding a good intend is definitely not enough for people’s experiences. All the Apps “promise” to keep users’ information in privacy, but it turns out that some companies would sell users’ name and telephone numbers a third parties driven by profit. Users would then occasionally receive text messages from certain weird agencies which end up harassments. Compared with a good intend, strict and clarified supervision policies and incentive measures should be taken to regulate the market.
Data transparency is a must in contemporary internet environment which is related to the trust links between businesses and consumers. Businesses should be specific on what customer data they are collecting and customers should be fully acknowledged of what information they are giving and consenting to receive. Businesses should enable customers to manage their own data to demonstrate their respects to users’ privacy.
As for the third statement, I think it depends on what hinderances are referring to. If the hinderance is derived from people’s unwillingness to share their data, it is difficult for developers to promote the applications of bid data if they can’t even receive enough data. Under such circumstance, getting people’s trust in sharing their personal data is the top priority. Otherwise, most hinderances would naturally fade away as data application industry becomes increasingly mature.