Everything that is said by Andrew Ng is worth reading and thinking about. This is no exception.
In the dominant model-centric approach to AI, according to Ng, you collect all the data you can collect and develop a model good enough to deal with the noise in the data. The established process calls for holding the data fixed and iteratively improving the model until the desired results are achieved. In the nascent data-centric approach to AI, “consistency of data is paramount,” says Ng. To get to the right results, you hold the model or code fixed and iteratively improve the quality of the data.