Generative AI

Discussion table

Learn from
Thusal Bennett
Thusal Bennett

Lead Data Scientist

Co-Host

Thusal contributes to Data Science implementation and strategy within the Office of the CTO in the Cabinet Office. He works on both Legacy infrastructure & Digital Transformation as well as translating state-of-the-art Artificial Intelligence tools to improve Governmental products and processes. 

 Thusal joined the Cabinet Office from a career in the private sector, providing Analytics consulting to the Retail, Finance, Legal & Real Estate sectors. He has led teams creating Artificial Intelligence systems to learn from unstructured, sparse & noisy datasets including Natural Language, Geospatial & Time Series data to solve a variety of business problems. 

Thusal has also utilised his skills to contribute to UK Government Covid response, leading a cross-functional team within the UK Health Security Agency developing performant epidemiological simulations that informed public policy at the highest levels.

Charlie Boundy
Charlie Boundy

Chief Data Officer

Co-Host

Deepak Shukla
Deepak Shukla

Head of Data and Analytics, AWS UKI public sector

Co-Host

Deepak leads AWS Data and Analytics business in UK and Ireland for Public Sector. He has over 16 years of management consulting experience leading and delivering digital transformation programmes enabled by cloud, data and analytics. He is passionate about transforming and enabling business value for his clients through adoption of advanced analytics use-cases, data products and modern AI/ML/Data-led platforms helping them become data driven.
About the session

The Generative AI revolution is picking up pace - with the technology allowing for the processing of large datasets to generate nuanced outputs that would take significant time and resources if performed manually. Studies are already showing dramatic improvements to white collar worker productivity - with the average time taken to complete tasks decreasing by 40%, and output quality rising by 18%.

These deep learning networks can synthesise data inputs to generate outputs that range from automated text, to digital images, to more complex system behaviours - automating report creation, forecasting policy impacts, enhancing creative projects in public communication. 

  1. Efficiency: How could your department use generative AI to automate tasks and streamline processes, and what are the potential barriers to its implementation?

  2. Policymaking: Generative AI models can create simulated scenarios based on existing data. How should government organisations leverage generative AI for policy forecasting?

  3. Data Requirements: Generative AI models often require large amounts of data for training. What challenges do departments face in collecting and curating high-quality datasets for training these models?