The last few years have seen a growing range of technologies deployed to assist humanitarian efforts, whether it's peacekeeping drones, crowdsourcing, or image analytics. The paper uses AI to predict the gender of pre-paid mobile phone users with a high degree of accuracy. Rescue teams already use mobile phone data to help track those in need of assistance, but this new approach aims to go even further by helping to identify their gender, and therefore identify vulnerable groups such as women and children. Whilst mobile phones are almost ubiquitous, in the developing world, many are pre-paid, meaning that data often lacks key demographic identifiers.
Qualities like natural language processing, voice recognition, automatic speech recognition, and question and intent analysis are components that will eventually lead to brands building smarter bots that can offer more sophisticated -- and human-like -- digital experiences for their customers. That said, like bots at the kindergarten level, these grade school bots don't have access to phone data beyond the information held in the specific application that houses the bot. To get to college level, bots need access to data beyond the app in which they live to understand user context. The search company recently purchased Api.ai, a startup focused on natural language processing, and it is also spearheading projects like DeepMind, which recently made significant headway in speech synthesis.