Data Ethics in Research

Importance of The Ethical Issues

The automation of data collection and analysis procedures in conjunction with the expansion of data storage and the development of sophisticated equipment for analyzing and processing data is drastically changing. Data research offers significant opportunities that enhance individual and societal life. Data is also significant in environmental conservation since it provides alternative solutions to environmental management, including the institution of smart cities and the identification of causal factors of carbon emissions.  Unfortunately, these opportunities are coupled with noteworthy ethical challenges. The widespread use of data is associated with the gradual decline of human involvement, amplifying predispositions that exacerbate issues of economic and social justice, and limited data privacy (Floridi & Taddeo, 2016). Moreover, the increasing reliance on algorithms in assessment and decision-making processes, including artificial intelligence, robotics, and machine learning, poses critical concerns of respect for human rights and equality. Whereas the perceptions of data confidentiality, its availability and integrity remain pertinent, issues regarding its privacy in terms of whether it satisfies regulatory requirements should also be prioritized. Initially, digital threats were limited to cybersecurity risks, but currently, it must be realized that there are more risks linked to ethical practices.

These ethical challenges must be handled to foster the application and development of data ethics whilst asserting the respect of human rights and the preservation of values shaping pluralistic societies. Whereas maintaining synchronization of these elements will be demanding, the failure to advance these ethics will definitely result in unwanted consequences. Data ethics in research will ensure social acceptability and social preferability that will considerably impact individual rights protection. It will promote the preservation of confidential information, increase human involvement, and reduce incidences of social injustice. These changes could probably respond to technical transformations and have significant conceptual implications. Further, it will enable each individual who uses the data in comprehending its interactions with social dynamics and the environment. Data analysis will generally address issues dealing with professional responsibilities and consent. Individuals undertaking research will be able to proceed without the fear of their data being compromised. The management of data in an ethical manner necessitates important changes in how data is perceived.

 

 

Fig1.Increasing incidences of data breaches (Source: Marketwatch )

 

Addressing the Ethical Issues

Data ethics is becoming increasingly complex, and it requires an active, continuous learning cycle in which the outcomes of data practice are frequently observed. More information is collected for further ethical expertise and updated to enhance ethical practice. Nonetheless, data ethics in research can be addressed by ensuring that subjects are assured of the lack of harm and that the information they provide will be regarded. There are various kinds of harm that subjects may be exposed to, including psychological distress, physical harm, and breaches of one’s confidentiality or anonymity. To minimize such risks, ethical practices and operational practices have to employed. This may include seeking informed consent and ensuring the confidentiality of subjects. Researchers must be able to access applications that provide the protection of their data. For example, the use of passwords can be used to prevent malicious hackers from accessing the content. Currently, few developments are in place on how the ethical concerns of data are handled. This is because technical equipment is continually evolving (Kinder-Kurlanda & Zimmer, 2019). There is a need for more advancement in how data is privatized. It is essential that the functions of chains of responsibility are assured and that participants of a project ensure explicit ownership of the research’s ethical significance. Researchers should learn to ensure that their data ensures the confidentiality of its participants. They should be responsible for an ethically executed research project.  They should also ensure that they are accountable in case the data is compromised and should be able to offer explanations and solutions if any harm is caused.

Solution

While there are distinctive lines of research and ethical practices, it is proper to develop data ethics from macro perspectives that avoid limited approaches and instead focus on an extensive set of ethical implications of data in research within an inclusive framework. Data ethics should be regarded as an ethical area of enquiry that identifies the most relevant issues to address and the significant lines of research to be developed. The use of consent prior to accessing one’s research may aid in reducing unethical issues. Computers could be automated with features and collected data sets that accommodate more dynamic concepts of consent. The use of passwords and accounts can ensure data privacy. The privacy of individual research will depend on the relationship between the receiver and provider of the data and the context. Moreover, appropriately identifying and the regard of expectations of privacy on data should be emphasized. There should be more transparency and democratic control over the implementation of systems that analyze or store research (Whitman, Hsiang & Roark, 2018). The participatory approaches to the management and design of these systems across an extensive range of domains and contexts should be examined.

 

 

References

Floridi, L., & Taddeo, M. (2016). What is data ethics?. Retrieved 10 June 2020, from https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2016.0360

Kinder-Kurlanda, K., & Zimmer, M. (2019, June). Web Research Ethics: Confidentiality, Consent, Data Integrity & More. In Companion Publication of the 10th ACM Conference         on Web Science (pp. 21-22).

Whitman, M., Hsiang, C. Y., & Roark, K. (2018, August). Potential for participatory big data ethics and algorithm design: a scoping mapping review. In Proceedings of the 15^thParticipatory Design Conference: Short Papers, Situated Actions, Workshops and Tutorial-Volume 2 (pp. 1-6).