Ethics in Data Science 

Data Science has so much influence on people’s lives. Data can be used to inform decisions and have a significant impact on a company or even the lifestyle of individuals. Data which is the main component of data science has seen a major increase in demand- whether it be clean or dirty. This useful resource does have some limitations and if we’re not actively addressing ethics in data science, data used incorrectly can also cause unintended harm.

Professional data scientists must be aware of the moral implications of the data they collect or use, the algorithms they apply, and the effects these have on people. Analysts, data scientists, and information technology professionals must be concerned about data science ethics. Anyone who works with data must be familiar with the basics.

Oxford professors and philosophers Luciano Floridi and Mariarosaria Taddeo state that:

“Data ethics is a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values).”

It is the responsibility of data scientists to protect personal information and utilize it ethically because of the frequent use of large data sets that are generated by people. There should also be an understanding of the underlying social and human systems so that data-driven technologies can more effectively incorporate human ideals like justice and equity. Because data science activities pose a threat to our understanding of what it means to be human, the need for a focus on data science ethics goes beyond the social impacts of automation, protection of personally identifiable data and implicit bias in automated decision-making.

Some ethical practices data professionals should keep in mind while using data are;

Data Ownership

The idea that each person has ownership over their data is one of the fundamental ethical principles in data science. Without their consent, it is illegal and immoral to collect someone’s personal information. As a result, permission is needed in order to obtain someone’s data.

Good intentions with Data

Data collection and analysis must be done with good intentions. Data experts need to be transparent about the purposes for which they utilize the data. For example, the goal is good if a team is gathering information on consumers’ spending patterns in order to create an app for budgeting.

Transparency

In addition to having a right to control their personal information, data subjects have a right to know how you intend to collect, store, and use it. When gathering data, transparency should be employed.

While data has helped people in many different ways, it is now crucial to understand why data is used. However, it first starts by taking into account how the use of data will affect people. This includes analyzing the influence on people and society and determining whether it might be beneficial, bad, or neutral. A better understanding of the ethics surrounding the collection and usage of data is what makes a data scientist a professional.

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#AI1000,#Analytics,#ArtificialIntelligence,#DataScience,#DeepLearning,#Education,#Ethics
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