roundtable experimentalism image

The Open Data Institute (ODI)’s Public Policy team is undertaking an ambitious new international project, called ‘Experimentalism and the Fourth Industrial Revolution’. We are exploring how data policymakers and data practitioners can work in more innovative and experimental ways to adapt to, and leverage, the fast-moving societal and economic challenges and opportunities around new data availability and associated digital technologies.

The project runs in three parallel workstreams named after sci fi writers. This workstream is named after Isaac Asimov and focuses on experimentation and innovation opportunities and needs for the UK as it charts a post-Brexit future.

This is part 1, which focuses on drivers and needs around innovation and experimentation in data policy and practice.

Constructive exploration

Isaac Asimov commented that modern science gathers knowledge faster than society gathers wisdom. We can see this tension in the domain of data policy and practice, where unprecedented and increasing data availability is coupled with unprecedented and increasing questions about how to use that data well.

On 19 July 2021, the ODI in partnership with the Office for National Statistics (ONS) and the Behavioural Data Science Group at the Alan Turing Institute convened an online roundtable of international representatives from government, academia, business and civil society for candid and constructive exploration of practical opportunities around this frontier topic in the UK economy and public sector. We’re sharing some of the insights from the meeting here to open up the learnings and broaden the discussion as we prepare a more substantive report for the autumn.

Roundtable provocations

Provocation 1: Information vs wisdom - Dr Mahlet (“Milly”) Zimeta, Head of Public Policy, ODI

Some key questions:

  • Are the ways we did things under old paradigms still fit for purpose under new paradigms?
  • If new ways of doing things are needed, how will we develop them? And what do we need to address in order to do so?
  • What are the criteria for a good experiment, worth doing and done well?1

Provocation 2: Data futures - Dr Jeni Tennison OBE, Vice President and Chief Strategy Adviser, ODI

Some key questions:

  • How might data availability and data use change how different parts of our society and economy relate to each other?
  • How are contemporary uncertainties around data use different from uncertainties we might have had in the past?
  • How should policymakers engage with circumstances where there are few useful precedents?

Provocation 3: Estonia’s data transformation - Sigrit Siht, Director of Data Policy, Government of Estonia

Some key questions:

  • How can we adapt to adapting in data policy and data practice?
  • Could innovation in data policy help strengthen the relationship between people and their governments?
  • What helps create the conditions for experimentation to be met with optimism and trust?

Provocation 4: New data sources - Tom Smith, Managing Director of Data Science Campus, Office for National Statistics

Some key questions:

  • What is the difference between new sources of data, and existing data sources being used in new ways?
  • Why can’t this wait for a few more years until we have more evidence or more confidence about how to do it?
  • What is the kind of data you would most want access to, and how would you use it?

Provocation 5: New kinds of analysis - Professor Ganna Pogrebna, Lead for Behavioural Data Science, The Alan Turing Institute

Some key questions:

  • When does a kind of analysis stop becoming 'experimental' and start becoming 'established'?
  • What role can experimentalism play in navigating ‘decision problems’ and ‘unknown unknowns’?
  • What kind of analysis would you like to be able to do, and what challenges would you use it to address?

Provocation 6: New societal expectations - Hetan Shah, CEO, The British Academy

Some key questions:

  • Should the scope of the ambition be to experiment within the parameters we already have?  Or to test and change the parameters?
  • Who has the social licence to experiment?  And who has the power to experiment?
  • Do challenges to experimentalism apply to data policy and practice?  Can data policy or practice help address challenges to experimentalism in other areas?

Get involved

We’ve created a summary note with a distillation of the high-level themes and observations that emerged in discussion. It’s a ‘living document’ and we welcome and encourage reader comments on it, as part of a community of practice, and to inform how the project develops. A full report will follow in autumn.

The summary note also includes a Resource Guide that we hope you find useful, and that you can contribute to. If you would like to explore any of these ideas and opportunities further with any of the event partners, or in collaboration with us together, we’d be keen to hear from you.  Some immediate practical opportunities might be around ODI Research Fellowships, opportunities for experimentation training events with the Behavioural Data Science Group at the Alan Turing Institute, as well as training workshops there in behavioural and data science for practitioners and policy makers. We’d also be open to co-developing case studies, projects, or activities: there’s more about our relevant work in these areas in this Resource Guide. And if there are projects or resources that you’d find useful but that don’t seem to exist, do let us know in this document – we or others in this community of practice might be able to develop them.

There’s more about the project here where you can also sign up to the project mail-list for updates and opportunities, contact the team on [email protected], or look out for our news on Twitter: @ODIHQ

Asimov’s data revolution | roundtable summary note