Ethical Considerations in Data Science

 Data Science is a branch enveloped in several concerns and considerations related to ethics and its associated ideologies and theories. It may be because the subject deals with significant information that can change or affect a particular organization, irrespective of its scale. 

In this article, let us look into a few ethical considerations in Data Science that all companies and businesses should make to avoid misusing data and its power.

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Privacy

Data Science has immense capabilities and power when it comes to information. Thus, data privacy has become one of the most significant concerns in the modern world. Misuse or hacking of sensitive reports, statistics, facts, and intelligence can put even the largest of organizations at risk, affecting the country in more ways than one. 

Thus, all businesses involved in Data Science must ensure data privacy and security. It should be powerful enough to protect an individual’s Personally Identifiable Information or PII, even if that person allows for its collection and analysis. It is possible by keeping the data in a secure and safe database and implementing various means to prevent it from getting breached. It can entail file encryption, password protection, and other security techniques. 

Thus, data scientists must protect sensitive data, no matter its nature. 

Data Ownership

All individuals have proprietorship of their distinctive and private data. It is one of the core ethical principles in Data Science. Thus, collecting and distributing others’ information is morally incorrect and illegal. 

Nonetheless, methods exist to request and access the information. It includes:

• Signed agreements

• Accepting cookies to allow websites to check an individual’s online activity

• Agreeing to an organization’s terms and conditions as part of online privacy statements

These methods to gain permission to collect a user’s data encompasses the latter’s agreement to access the information. Thus, they are legal and fall within ethical practices. 

Transparency

All clients have a right to know how companies or data scientists access, collect, apply, and store their personal information. Thus, the data-gathering process must remain transparent. It is unlawful, unethical, and dishonest to do so otherwise. 

Suppose an organization uses an algorithm to personalize their customers’ online experience depending on their website activity and purchasing patterns. In such cases, the former should create a policy stating how cookies would get used to monitor the user’s interests, gather information in secure databases, and applied to program the algorithm. Accordingly, the customers would accept or decline it. 

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Decision-Making

Decision-making practices and rights lie with customers when it concerns their personal information. Thus, an ethical consideration that data scientists and companies must make entails seeking their client’s permission before making judgments using the available data. 

Suppose a data scientist wants to represent their customer and act on their behalf for a specific project. Even so, the former should not make decisions for the latter. It remains true even if the judgments benefit the project and the client considerably. Thus, the decision-making skills should lie with the customer or the individual possessing the right to the data. 

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