Deploying algorithms in government

Image by Markus Spiske from Pixabay.
June 8, 2021
Digital & technology

Download Dr Vik Pant and Keith Stagner slides

Download Natalia Domagala slides

Download Stefaan Verhulst slides

Download Dr Mahlet (Milly) Zimeta slides

View T-Impact’s Robotic Process Automation Demo

The use of algorithms in government is not a new phenomenon. But with public sectors’ adoption of digital technologies, their use is becoming far more widespread and high-profile – creating the potential for both greater rewards, and bigger risks.

In the UK education system, for example, algorithms have been used for a decade to avoid ‘grade inflation’ by adjusting exam scores. Yet when last year the UK’s Department for Education approved the use of an algorithm to decide the grades of students whose exams had been cancelled in the pandemic, inequities in the results led to huge opposition and an abrupt retreat.

The lesson here is not to avoid using algorithms: well-designed systems can generate big efficiency savings, strengthen the evidence available to policymakers, and help target and improve the services received by citizens. Algorithms lie at the heart of technologies with huge potential value in government, from the high-volume, transaction-processing power of Robotic Process Automation (RPA) to the helpful insights and guidance generated by Machine Learning (ML) systems.

However, algorithms must be carefully designed, expertly commissioned and intelligently deployed. Civil service leaders and digital professionals need the skills to identify suitable use cases, understand how algorithms will affect the decisions and services received by citizens, and ensure that any risks to citizens’ wellbeing, rights or privacy are addressed. Focusing mainly on fixed, non-ML systems such as those used in RPA, this webinar explored how algorithms can help to improve efficiency and outcomes in government – and how civil service bodies can realise their potential while avoiding their dangers.


Webinar chair: Siobhan Benita, former UK senior civil servant

Siobhan Benita was a senior civil servant with over 15 years’ Whitehall experience. She worked in many of the major delivery departments, including Transport, Environment, Health and Local Government. She also had senior roles at the heart of Government in the Cabinet Office and HM Treasury, including supporting the then Cabinet Secretary, Lord O’Donnell to lead work on Civil Service reform and strategy. Siobhan left the Civil Service to run as an independent candidate in the Mayor of London election. She subsequently joined her alma mater, Warwick University as Chief Strategy Officer of Warwick in London and Co-Director of the Warwick Policy Lab.

Dr Mahlet (Milly) Zimeta, Head of Public Policy, Open Data Institute (ODI)

Dr Zimeta is Head of Public Policy at the Open Data Institute. Prior to joining the ODI in September 2020, Milly was Senior Policy Adviser at the Royal Society, the independent scientific academy of the UK, where she led the Society’s policy programme on Data and Digital Disruption including projects on data governance, data science skills, and privacy enhancing technologies.

Milly was previously Programme Manager at the Alan Turing Institute, Britain’s national institute for data science and AI, where she managed the Turing’s research partnership programmes in Health and in Finance/Economic Data Science. She has also worked at the Medical Research Council, and served on an Advisory Group at Chatham House. She holds degrees in philosophy from Oxford, Cambridge and York (UK).

Natalia Domagala, Head of Data Ethics, Central Digital and Data Office (CDDO), Cabinet Office, United Kingdom

Natalia leads on data ethics policy at the Central Digital and Data Office, Cabinet Office in the UK. She previously advised on open government and open data policies for the Department for Digital, Culture, Media and Sport in the UK, and implemented open data challenges for 360Giving. She has research experience in anthropology, gender, civic tech, and economic development, and she has recently co-edited a book: Situating Open Data: Global Trends in Local Contexts. Natalia is a Policy Fellow at the Centre for Science and Policy, University of Cambridge. She received her MSc in Local Economic Development from the London School of Economics and Political Science and her BA in Anthropology and Media from Goldsmiths, University of London.

Dr Vik Pant, Chief Scientist and Chief Science Advisor, Natural Resources Canada

Vik is responsible for providing strategic direction to build capacity within NRCan’s scientific community, promoting a departmental vision for S&T and assessment of future needs. This involves leadership in developing and advancing S&T priorities, providing strategic policy advice on horizontal science issues and opportunities to ensure strong linkages between science and policy communities, and promoting effective engagement of S&T activities. Vik is responsible for accelerating the creative application of innovative digital technologies including Artificial Intelligence, to enhance NRCan’s ability to conduct research and analysis, as well as provide evidence-based policy advice that is supported by advanced analytical techniques. Vik works with counterparts from other science-based organizations to ensure that the management of federal policy and research activities support and align with Government of Canada priorities.

Vik earned a doctorate from the Faculty of Information (iSchool) in the University of Toronto, a master’s degree in business administration with distinction from the University of London, and a master’s degree in information technology from Harvard University, where he received the Dean’s List Academic Achievement Award.

His research, featured in numerous peer-reviewed journals and refereed international conferences, focuses on the conceptual modelling of strategic coopetition in complex multi-agent systems. Vik joined NRCan from the MaRS Discovery District, a technology start-up accelerator in Toronto, where he was a Senior Technical Advisor of Applied Artificial Intelligence. Prior to that, he held progressively strategic positions in leading software enterprises including Oracle, SAP and Open Text.

Stefaan Verhulst, Co-Founder and Chief Research and Development Officer, The Governance Laboratory (The GovLab)

Stefaan G. Verhulst is Co-Founder and Chief Research and Development Officer of the Governance Laboratory (The GovLab) at New York University (NYU) – an action research center focused on improving governance using advances in science and technology – including data and collective intelligence. He is also, among other positions and affiliation, the Editor-in-Chief of Data & Policy, an open access journal by Cambridge University Press; the research director of the MacArthur Research Network on Opening Governance; Chair of the Data for Children Collaborative with Unicef; and a member of the High-Level Expert Group to the European Commission on Business-to-Government Data Sharing.

At The GovLab, Stefaan Verhulst has developed and leads a range of impactful research initiatives that contribute to an enhanced understanding and improved practice of using data, science, and technology for decision and policymaking.

Keith Stagner, CEO, T-Impact

Keith Stagner is the CEO of T-Impact Ltd, leading Digital Transformation programmes specialising in improving customer journeys using Lean Six Sigma and automating them using Intelligent Automation tools, such as Chatbots, Robotic Process Automation (RPA), Artificial Intelligence (AI) and Workflow.

Keith has more than 35 years of experience delivering innovation and creating value across Local Government, Central Government, NHS & Healthcare, not-for-profit organisations and the Private Sector (Banking, Telecoms, Retail, Legal, Logistics and Manufacturing). Keith has supported customer organisations as interim CIO/Director and can empathise with the challenges facing C-Level managers. He designed T-Impact’s benefit driven approach and knowledge transfer services to impart long-term value, while minimising operational disruption.