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Data ethics is the study and practice of gathering, processing, sharing and using digital information with regard to morality and social values. In today’s digital age, there are abundant amounts of data available for organizations to use and maneuver to achieve their goals, which can easily become hazardous for customers and users. Data ethics guide data scientists, providing a framework for handling data responsibly. A data framework outlines the ethical use of data, algorithms (artificial intelligence, machine learning), coding and programming hacking—placing limitations on the way organizations can use information derived from technology.
Data ethics ensures that users consent to shared data and organizations adhere to compliances and privacy laws. Organizations are also held to task on using insights derived from data responsibly and legally with regard to social and economic justice—mitigating biases against certain groups and data sets. Data must also be used for the purpose it was gathered for and consented to.
Data ethics also gets involved in the data supply chain, ensuring responsible practices at every step—from aggregation to storage. This mitigates mishaps and potential data privacy risks before data is shared between trusted parties.
Handling data in an ethical way: