Maintaining Ethical Standards With Online Data Collection

The following is a guest post by Ainsley Lawrence

When it comes to online data collection, ethics are paramount. Maintaining ethical standards with online data collection helps you verify the integrity of the information. Plus, it enables you to do everything in your power to protect data and prevent it from falling into the wrong hands.

Ultimately, there are many ethical issues that crop up with online data collection. With a clear understanding of online data collection ethics, you’re well-equipped to retrieve high-quality data from across the web, without putting yourself or others in danger.

Online Data Collection Ethical Dilemmas: Here’s What You Need to Know

Researchers recently explored the ethics of online data collection and published their findings in an Ethics and Information Technology journal paper. They indicated there are five common ethical dilemmas that must be considered with data collection:

1. Consent

People must consent to the collection of their data. Yet it can be tough to determine if individuals actually understand when they approve an organization’s online data collection request. And it can be difficult to track consent if data is repurposed and used for myriad analyses, too.

Guidelines have been set up to manage online data collection consent. For instance, the EU General Data Protection Regulation (GDPR) requires a legal basis for data processing. Organizations must have a legal basis for online data collection. Moreover, organizations must request consent for data collection, and individuals must agree to it. Otherwise, if an organization does not comply with GDPR requirements, it risks costly violations. Also, this organization is susceptible to brand reputation damage and revenue losses.

With online data collection consent, be transparent. Let individuals know what information you want to collect and how you intend to use it. Leave no room for “gray area.” And if individuals have concerns or questions, encourage them to reach out.

2. Privacy and Confidentiality

For many people, privacy and confidentiality are interchangeable. But there are notable differences between the two. Whereas privacy is regulated by law, confidentiality is not. Confidentiality is an ethical obligation, and it must be treated as such.

Ultimately, it pays to prioritize data privacy and confidentiality. To do so, you first need to learn data privacy laws. For instance, if you are performing clinical research, you need to keep participants’ data private to comply with HIPAA. At the same time, you must notify participants about how you intend to store their data and utilize it now and in the future. Likewise, healthcare providers must maintain high data privacy standards even as technology advancements such as telehealth make data collection easier.

Verify data privacy and confidentiality systems are in place across your operations. Software is available that you can use to secure your data systems. This software should be evaluated and updated regularly.

3. Ownership

Data ownership concerns and questions persist for organizations around the world. In some instances, ownership is shared between an organization and anyone who provides data. However, an organization may claim it owns data once someone shares it. At this time, the organization may try to sell the data or use it in other ways, without consulting with the individual who originally provided it.

To alleviate ownership issues, let data ethics reign supreme. If you submit a request to collect data, explain who will own the information moving forward. Furthermore, if you will retain sole ownership, offer insights into how you plan to use someone’s data. This ensures an individual knows if he or she will retain ownership of their data. In addition, it enables him or her to make an informed decision about whether to share their data.

4. Governance and Custodianship

Data is commonly viewed as a commodity and research tool. Thus, researchers utilize data for surveys and other assessments. After these assessments, researchers can maintain a data repository. They may also explore opportunities to use the data again.

A people-first approach to data governance and custodianship is key. You can establish a framework and processes for data governance and custodianship. Then, you can share this information about them as you collect data. Keep your data governance framework and processes up to date. That way, you can consistently ensure they align with the needs of your organization and stakeholders.

5. Data-Sharing

Data-sharing standards are not one-size-fits-all. Rather, organizations develop varying guidelines for sharing data. Regardless, they must ensure people know these guidelines before they provide their data to another organization.

Provide details about whether you intend to share data. If so, explain how you plan to share data and who may be able to view it. Describe how you will ensure data is secured by you and anyone else who accesses it, too.

Take an Ethical Approach to Online Data Collection

Online data collection ensures you can quickly and easily retrieve data from individuals globally. On the other hand, data collection can raise ethical issues.

If you plan to collect data online, plan accordingly. Provide individuals with as much information as possible about your data collection methods and processes. Let people know if you use artificial intelligence (AI) or other technologies for data collection. And verify individuals know how you will store, manage, and secure their data.

The bottom line: Treat someone else’s data in the same way you’d want others to take care of your own information. This ensures you can establish and maintain an ethical approach to data collection that serves you well for many years to come. 

Frank

#DataScientist, #DataEngineer, Blogger, Vlogger, Podcaster at http://DataDriven.tv . Back @Microsoft to help customers leverage #AI Opinions mine. #武當派 fan. I blog to help you become a better data scientist/ML engineer Opinions are mine. All mine.

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