Machine learning will be used pervasively to personalise all kinds of services in the foreseeable future. It won’t just be smartphones or tablets serving as data input and output for machine learning systems, but all kinds of connected devices which are part of what is called the “Internet of Things”, such as wearables, home appliances, medical equipment or cars.
The more constantly surrounded we are by devices feeding into machine learning systems, the more unsettling it will be for users to be left in the dark about the functionality and processes, because it causes them to build their own theories around what providers do with their data, as we already see with other types of data today.
This thesis gives a very brief introduction to Artificial Intelligence and its history and an overview of technological, legal, societal and philosophical aspects which are relevant when humans are confronted with machine learning. It also discusses existing related work and phenomena in this field and finally comes to the conclusion that the problem presents itself in a way that it is not exclusively an engineering issue to solve, but a design issue.