Correlations made by big data are likely to reinforce negative bias. Because big data often relies on historical data or at least the status quo, it can easily reproduce discrimination against disadvantaged racial and ethnic minorities. The propensity models used in many algorithms can bake in a bias against someone who lived in the zip code of a low-income neighborhood at any point in his or her life. If an algorithm used by human resources companies queries your social graph and positively weighs candidates with the most existing connections to a workforce, it makes it more difficult to break in in the first place. In effect, these algorithms can hide bias behind a curtain of code.

[...] it is largely unregulated because we need it for economic growth and because efforts to try and regulate it have tended not to work; the technologies are too far-reaching and are not built to recognize the national boundaries of our world's 196 nation-states.

Yet would it be best to try to shut down these technologies entirely if we could? No. Big data simultaneously helps helps solve global challenges while creating an entirely new set of challenges. [...]