1 May, 2024
4:00 pm - 5:00 am
Across frontline public services, there is a wealth of evidence that shifting our focus to prevention would reduce demand, improve outcomes for the public, and be cost-effective for public finances. The latest developments in Al provide new techniques to target prevention, in a time when constrained budgets mean we need to be hyper-focussed on where investment can achieve the greatest effect.
Across health, local government, education, criminal justice and the welfare system, Al and machine learning techniques can interpret patterns of complexity, and provide decision-makers with the best insights on where to intervene in the early stages of a citizens' interaction with the State - before their case becomes acute and harder to resolve.
However, building public services with the right data and data science capabilities to effectively use early intervention is challenging in that complex landscape. Particularly when the data required to train the right algorithms comes from many different departments and public services, and is often poor-quality. This discussion will focus on the practical steps required to overcome this - including technical, ethical and implementation questions about data governance - in order to realise Al's potential for prevention.
We are thrilled to be joined by Dr Laura Gilbert, Chief Analyst and Director of Data Science at 10 Downing Street, to explore how government can use Al to target preventative services.
This is a private roundtable which will be held under the Chatham House rule and is kindly supported by Newton Europe.