Learn to mitigate reputational and regulatory risks by understanding how to evaluate and critique the ethical dimensions of data projects.
This workshop is divided into three sections: the first discusses the ethical dimensions involved when using data, the second discusses the ethical dimensions when using and deploying algorithms, and the third looks at current trends and what is being done to tackle the many challenges in this space.
Introduce the latest legal and ethical frameworks for the protection and use of data.
Present the vast reach data ethics has in business today.
Introduce ethical dimensions of building machine learning models.
Identify areas of ethical considerations in the data product lifecycle.
Introduce the latest ethical frameworks.
Differentiate between legal and ethical approaches to data use.
Identify unscrupulous uses of data and define the responsible use of data.
Define ethical dimensions of machine learning models.
Flag ethical checkpoints in data product lifecycles (sourcing, modelling, deploying, maintaining).
Evaluate data projects for potential data bias and its impacts.
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