For instance, the algorithm could exhibit biases and lead to discriminatory outcomes. Also, as with any data-dependent method, it is inherently backward-looking since it takes time to collect data and train the models. Furthermore, since many of the techniques are new, users often feel they are forced to use black boxes with very low explainability.
The question is whether these warnings should be supplemented by actions to inject uncertainty into policy pronouncements by saying less  than we can or into the economy by shifting our objectives away from seeking the best outcome for the economy over the intermediate term.