5 principles to maintain Digital Ethics and Privacy

Digital ethics landscape is evolving very rapidly. It has a very complex nature which is becoming even more complex with the involvement of artificial intelligence. Artificial intelligence enables a service provider to gather valuable insights and new information with very limited user interaction. Such data can be used for any purpose. It can be for good or it may also encroach upon the areas of privacy and security.

In cases where the issue of privacy is in question, a service provider must think beyond the traditional notion of consent. It should always be considered that when legally right one may still be ethically wrong. An example of this is using the user-generated data for unspecified propose for political and economic gains. Even when exclusive consent exists, influences exerted as such will always be considered in violation of the ethical standards.

It can not be expected from each and every private entity to actively protect the user trust in this area. Solution for this lies in public action only. Authorities must actively track how an organization deals with the local challenges involved with data and how their actions impact public privacy and security. They must have a response protocol ready for most cases for Swift action. It is a very good thing in this respect that these issues are being widely focused in public spaces and regulatory frameworks. In the long run, it will help in attaining maturity in terms of handling the data properly.

Recent controversies around multinational organizations like Facebook and Twitter questioning their methodologies in handling the huge user data have sensitized even common people about the threats looming because of the lapse in data privacy. The rigging of election results by way of systematically influencing the voters is a very strong example in this respect.

There are few strict principles which be adhered to for safeguarding data ethics.

Private data must remain private - privacy should not mean secrecy and every legal requirement of disclosure must be mandatorily fulfilled. Still, every data should not be sold or made available publicly because the consent for the same has been received. This data may not be exposed to other entities without the express approval of the same. Shared data is confidential - companies receiving data shared by the user for purposes like medical, financial or even locational must treat it as confidential. There must be transparency - customers should have a transparent view of how their data is being used No interference with human will - artificial intelligence analytics has the capacity to determine user behaviour. However, it should be ensured that they do not interfere with free will
No systematic biases- big data should not be utilized to institutionalize biases like the ones based upon race or gender.