The UK tech sector is increasingly turning to synthetic data to address current challenges around data access and availability, privacy, and sharing.

Advocates of synthetic data argue that it is better for privacy preservation than ‘anonymised’ datasets that despite best efforts can, from time to time, be linked back with identifiers. It also removes the reliance on data sharing for the formation of the datasets and often times is more scalable. It is no wonder, then, that Gartner predicts that by 2024, 60% of data used for the development of AI and analytics projects will be synthetically generated. In fact, it is possible that AI models simply won’t be possible without the use of synthetic data.  

However, amongst the advocates and advantages of synthetic data, there are justifiable apprehensions about data generation techniques, transparency and explainability that could offset the potential benefits it  could bring. Furthermore, if existing barriers to unlocking the full value of non-synthetic or ‘real data’ were removed, it could be possible that the need of synthetic data would be reduced. There are also many other long-standing data challenges that exist which risk persisting in the context of synthetic data if not addressed, such as the data skills shortage. 

In this next iteration of techUK’s Future Vision Series, techUK will seek to answer some of the burning questions members have around the creation and use of synthetic data, where it could be revolutionary, and whether it will live up to its hype.  

In particular, this webinar will address: 

  • What are the common ways to create synthetic data, and what does the emerging synthetic data ecosystem look like? 

  • What is the connection between synthetic data and PET’s?  

  • Is synthetic data a plaster over larger data availability challenges, or a long term solution for businesses? 

  • How do we ensure decisions made based off synthetic data are rooted in reality, rather than what a machine imagines that reality to be? 

  • What are some of the key ethical considerations which should underpin the generation of synthetic data, and how important is public trust?

  • What does this mean for the future of data availability? 

Speakers include:

  • Dr. Martin O'reilly, Director of Research Engineering, The Alan Turing Institute
  • Jeremy Poulter, Business Development & Solutions Director, Defence and National Security, Microsoft UK
  • Alexandra Ebert, Chief Trust Officer, Mostly AI
  • Emanuele Haerens, Commercial Director, Hazy
  • Laura Foster, Head of Tech & Innovation, techUK

 

Laura Foster

Laura Foster

Head of Technology and Innovation, techUK

Laura is techUK’s Head of Programme for Technology and Innovation.

She supports the application and expansion of emerging technologies across business, including Geospatial Data, Quantum Computing, AR/VR/XR and Edge technologies.

Before joining techUK, Laura worked internationally in London, Singapore and across the United States as a conference researcher and producer covering enterprise adoption of emerging technologies. This included being part of the strategic team at London Tech Week.

Laura has a degree in History (BA Hons) from Durham University, focussing on regional social history. Outside of work she loves reading, travelling and supporting rugby team St. Helens, where she is from.

Email:
[email protected]
LinkedIn:
www.linkedin.com/in/lauraalicefoster

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Dani Dhiman

Dani Dhiman

Policy Manager, Data, techUK

Dani joined techUK in October 2021 as Policy Manager for Data.

She formerly worked in Vodafone Group's Public Policy & Public Affairs team as well as the Directorate’s Office, supporting the organisation’s response to the EU Recovery & Resilience facility, covering the allocation of funds and connectivity policy reforms. Dani has also previously worked as a researcher for Digital Catapult, looking at the AR/VR and creative industry.

Dani has a BA in Human, Social & Political Sciences from the University of Cambridge, focussing on Political Philosophy, the History of Political Thought and Gender studies.

Email:
[email protected]
LinkedIn:
https://www.linkedin.com/in/danidhiman

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