ACTION applied a citizen science approach to tackling pollution; one of the greatest threats to human health and wellbeing of our times, killing more people than smoking, hunger, natural disasters, war and infectious diseases such as HIV/AIDS and coronavirus.
The EU-funded MediaFutures project led by Prof Elena Simperl will address this challenge by reshaping the media value chain. It will set up a virtual European data innovation hub to support entrepreneurial and innovative projects.
ACTION was a three-year programme funded through the European Union’s Horizon 2020 framework, led by Prof Elena Simperl, King’s College London, dedicated to transforming the way we do citizen science (CS) today: from a mostly scientist-led process to a more participatory, inclusive, citizen-led one, which acknowledges the diversity of the CS landscape and of the challenges CS teams have to meet as their project evolves.
Robots are rapidly emerging in society and will soon enter our homes to collaborate and help us in daily life. Robots that provide social and physical assistance have huge potential to benefit society, especially for those who are frail and dependent. This was evident during the Covid-19 outbreak, where assistive robots could aid in the care of older adults at risk, in accessing contaminated areas, and providing social assistance to people in isolation.
For robots to build trustable interactions with users two aspects will be crucial during the next decade. First, the ability to produce explainable decisions combining reasons from all the levels of the robotic architecture from low to high level; and second, to be able to effectively communicate such decisions and re-plan according to new user inputs in real-time along with the execution.
Profs Maria Fox and Derek Long have built an AI planning tool for global energy company Schlumberger that makes drilling safer, faster and more environmentally friendly. The tool is proving a huge success – and is on its way to become a new global industry standard.
The goal of the THuMP project is to advance the state-of-the-art in trustworthy human-AI decision-support systems. The Trust in Human-Machine Partnership (THuMP) project will address the technical challenges involved in creating explainable AI (XAI) systems so that people using the system can understand the rationale behind and trust suggestions made by the AI.