Eleanor M. Fox | NYU School of Law
The most recent decade featured a data revolution. The call for developing a legal, policy and ethical framework for using big data, artificial intelligence and algorithms sector has therefore reached unprecedented momentum. The report aims at helping a broad spectrum of stakeholders understand the impact of big data, algorithms and health data to provide them with information on key drivers, restraints, challenges, and opportunities for the pursuit of improvement of this new market innovation. Stateshuman and diplomats are invited to consider three major trends in the wake of the Artificial Intelligence (r)evolution: (1) Artificial Intelligence has gained citizenship as robots have become the first citizens:• With attributing quasi-human rights to AI, ethical questions arise of a stratified citizenship. • Robots and algorithms may only be citizens for their protection and upholding social norms towards human-like creatures • but may not have full citizen privileges such as voting, property rights of possession and holding a public office. (2) Big data and computational power hold unprecedented opportunities for:• Crowd understanding, trends prediction and healthcare control.• Risks include data breaches, privacy infringements, stigmatization and discrimination.• Data protection through technological advancement, self-determined privacy attention through education as well as discrimination alleviation through taxation of data transfer values are recommended. Taxation revenues will grant the fiscal space to offset losses and the social costs of market distortions caused by robots and algorithms taking over in the marketplace. (3) The European Union should consider a fifth trade freedom of data:• To bundle AI and big data gains large scale such as in the US and China. • Especially in the healthcare sector, the EU has a competitive advantage over the US and China as for a wealth of data.• Big data in the healthcare sector should only be used with caution to avoid discrimination. For instance, only anonymized data slices should be made available to the public in order to avoid stigmatization, gentrification and discrimination based on predictable prevalences.