Accounting For Diversity In Automated Gender Recognition Systems

Developments in AI entail incredible progress for many fields in the near future. AI is increasingly influencing the opinions and behaviour of people in everyday life, and it is no longer merely confined to industry but can be found in many other fields, such as healthcare, education and retail environments. Nevertheless, the introduction and implementation of AI in society raises a variety of ethical, legal and societal concerns, and within this context there are still many areas in which there is substantial room for improvement. A more specific practical example of such room for improvement can be found in the fact that algorithms, among which automated gender recognition systems, do not always account for diversity, and this may have a detrimental impact on the lives of individuals. From a legal perspective, a question that has often been raised within this context is how we can best account for diversity in such AI systems?