While algorithms are hardly a recent invention, they are nevertheless increasingly involved in systems used to support decision-making in society. These ADS (algorithmic decision systems) often rely on the analysis of large amounts of personal data to infer correlations or, more generally, to derive information deemed usefulto make decisions. Human intervention in the decision-making may vary, and may even be completely out of the loop in entirely automated systems. In many situations, the impact of the decision on people can be significant, such as access to credit, employment, medical treatment, judicial sentences, among other things. Entrusting ADS to make or to influence such decisions raises a variety of ethical, political, legal, or technicalissues,where great care must be taken to analyse and address them correctly. If they are neglected, the expected benefits of these systems may be negated by the variety of risks for individuals (discrimination, unfair practices, loss of autonomy, etc.), the economy (unfair practices, limited access to markets, etc.) and society as a whole (manipulation, threat to democracy, etc.). The purpose of this policy options briefing is to highlight the main challenges and suggested policy options to allow society to benefit from the tremendous possibilities of ADS while limiting the risks related to their use.