Ethical considerations in data science involve ensuring data privacy, addressing biases, promoting transparency, and accountability to uphold fairness and responsible data handling practices in the field. https://1stepgrow.com/advance-data-science-and-artificial-intelligence-course/

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Data Privacy:
Accountability:
Safeguard individuals' private
information and obtain informed
consent when collecting data.
Bias Mitigation:
Identify and address biases in
data to ensure fair and unbiased
algorithms.
Hold data scientists responsible
for their work and establish clear
guidelines for ethical conduct.
Data Security:
Protect data from unauthorized
access, breaches, and cyber
threats.
Data Ownership:
Define and respect data ownership
rights, including intellectual
property.
Continuous Learning:
Stay updated on ethical guidelines
and best practices in data science.
Ethical
Considerations in
Data Science