Fundamental rights challenges associated with AI

Fundamental rights challenges associated with AI

Rome [ENA] Policymakers have highlighted the potential for Artificial intelligence (AI) and related technologies to develop efficiency and drive economic growth. Yet public authorities and international organisations have only recently reflected on the fundamental rights challenges associated with such technologies. Together with the emergent application and precision of AI systems, policymakers and public opinion turned

attention to whether and how to regulate their use. Artificial intelligence (AI) refers to systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals. Most of the discussion around, and the actual use of AI, involves installing machine learning technologies. These can be seen as a sub-domain of AI. There is also some confusion around the term “learning”, which implies that machines learn like humans. In reality, much of current machine learning is based on statistical learning methodologies. Machine learning uses statistical methods to find rules in the form of correlations that can help to predict certain outcomes.

This is different from traditional statistical analysis, because it does not involve detailed checks of how these predictions were produced (often referred to as ‘black boxes’). Traditional statistical analysis is based on specific theoretical assumptions about the data generation processes and the correlations used. Machine learning is geared towards producing accurate outcomes, and can be used for automating workflows or decisions, if an acceptable level of accuracy can be obtained. The usual example is an email spam filter, which uses statistical methods to predict if an email is spam. As it is not important to know why a certain email was blocked and because spam can be predicted with very high accuracy,

we do not really need to understand how the algorithm works (i.e. based on what rules emails get blocked). However, depending on the complexity of the task, prediction is not always possible with high accuracy. Furthermore, not understanding why certain outcomes are predicted is not acceptable for certain tasks. The area of machine learning includes several approaches. Most often, machine learning refers to finding rules that link data to a certain outcome based on a dataset that includes outcomes (supervised learning). Artificial intelligence already plays a role in deciding what unemployment benefits someone gets, where a burglary is likely to take place, whether someone is at risk of cancer and so on.

When machines do the kind of things that only people used to be able to do it is possible to speak of Artificial intelligence (AI). Today, AI is more present in our lives than we realise – and its use keeps growing. The possibilities seem endless. The potential implications for fundamental rights and the question whether and how those using AI are taking rights into account have to be discussed. It is more and more crucial to analyse how fundamental rights are taken into consideration when using or developing AI. One way to foster rights protection is to ensure that people can seek remedies when something goes not as it should be.

Organisations using AI need to be able to explain their AI systems and how they deliver decisions based on them. Those who develop and use AI also need to have the right tools to assess comprehensively its fundamental rights implications, many of which may not be immediately obvious. Accessible fundamental rights impact assessments can encourage such reflection and help ensure that AI uses comply with legal standards. At the European Union level, regulatory framework for AI seems to be firmly grounded in respect for human and fundamental rights.