Nowadays, there are massive amounts of heterogeneous electronic information available on the Web. People with disabilities, among other groups potentially in uenced by the digital gap, face great barriers when trying to access information. Sometimes their disability makes their interaction the ICT environment (eg., computers, mobile phones, multimedia players and other hardware devices) more dicult. Furthermore, the contents are delivered in such formats that cannot be accessed by people with disability and the elderly. The challenge for their complete integration in information society has to be analyzed from di erent technology approaches.
Recent developments in Machine Learning are improving the way people with disabilities access to digital information resources. From the hardware perspective, Machine Learning can be a core part for the correct design of accessible interaction systems of such users with computers (such as BCI). From the contents perspective, Machine Learning can provide tools to adapt contents (for instance changing the modality in which it is accessed) to users with special needs. From the users' perspective, Machine Learning can help constructing a good user modeling, as well as the particular context in which the information is accessed.