This is the third in a series of three blogs on AI assurance, which explore the key concepts and practical challenges for developing an AI assurance ecosystem. The first blog focused on current confusion around AI assurance tools and the …
Data-driven technologies, such as artificial intelligence (AI), have the potential to bring about significant benefits for our economy and society. However, they also introduce risks that need to be managed. As these technologies are more widely adopted, there is an …
In our recently published review into bias in algorithmic decision-making, we explored the regulatory context in which algorithmic decisions take place, which includes equality law, human rights law, discrimination law and sector specific regulations. The main piece of legislation that …
The primary purpose of the majority of use-cases has been to support the local response and mitigate the effects of lockdown. However, we are starting to see examples of use-cases designed to build future resilience and aid the recovery; these have been particularly prominent in the transport sector. For example, the Commonplace Mapping Tool which allows users to highlight pinch points across Glasgow City Centre, where measures such as pavement widening and new cycle lanes could be introduced to help people maintain physical distancing.
Although the majority (70%) of the use-cases we have added over the last month are still related to health and social care, the focus has moved away from managing the immediate public health crisis and towards building future resilience.
What is the AI Barometer? The CDEI’s AI Barometer is a major analysis of the most pressing opportunities, risks, and governance challenges associated with AI and data use in the UK. The first iteration of the AI Barometer covers five …
Although there are a number of entirely new uses of data and AI, approximately half of our April database relates to extension or pivots of existing activity to a new context, or a new synthesis of existing data sources. We would expect to see an increase in novel use-cases as time goes on, after further development and testing time.
Financial companies are increasingly using complex algorithms to make decisions regarding loans or insurance - algorithms that look for patterns in data which are associated with risks of default or high insurance claims. This raises risks of bias and discrimination …
Recent reports suggest 9 out of 10 people are biased against women in some way. We wanted to mark International Women’s Day this year by talking about bias in a world of data-driven technology and artificial intelligence, and our forthcoming report on bias in algorithmic decision-making.
Who gets to decide where the boundary lies between national security concerns, and an individual's right to privacy? Are the right guidelines in place for policing's increasing use of technology and data? These were some of the issues discussed at this week's lecture hosted by RUSI.