Conclusion - Algorithmic Governance
In these last few pages, I would like to conclude by considering how some of the key themes of this book pertain to the future of public-sector data science.
The most critical is the importance of evidenced-based decision-making in government. While the evidenced-based approach is now celebrated far and wide, most of its support comes from the program evaluation community. Evaluation is absolutely critical and can actually compliment prediction, but at times, some researchers get defensive at the role of machine learning in this movement.
Their beef typically reflects one of two concerns. First, that the data scientist with little domain expertise should not attempt meaningful policy prescriptions from hastily ...
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