Regulatory bodies around the world increasingly recognize that they need to regulate how governments use machine learning algorithms when making high-stakes decisions. This is a welcome development, but current approaches fall short. As regulators develop policies, they must consider how human decisionmakers interact with algorithms. If they do not, regulations will provide a false sense of security in governments adopting algorithms. In recent years, researchers and journalists have exposed how algorithmic systems used by courts, police, education departments, welfare agencies and other government bodies are rife with errors and biases.

In the United Kingdom there's been some landmark AI news recently involving government use of the technology. First, use of facial recognition by South Wales Police was ruled unlawful by a Court of Appeal judge in part for violating privacy, human rights, and failure by police to verify the tech did not exhibit race or gender bias. How the U.K. treats facial recognition is important since London has more CCTV cameras than any major city outside of China. Then, U.K. government officials used an algorithm that ended up benefiting kids who go to private schools and downgrading students from disadvantaged backgrounds. Prime Minister Boris Johnson defended the algorithm grading results as "robust" and "dependable for employers."