Jump to:

• Introduction
• Questions to Explore
• Common themes to guide but not limit submissions
• Submissions process
• Key dates (deadline for abstracts 30 July)

Visit the event webpage to learn more and submit your abstract.

Introduction

Advances in digital technologies are redefining opportunities around the world to develop new economic value, to govern and serve within more accessible societies, and to empower individuals. Legal recognition of identity, the ability to establish trust in who we are, is a foundational component of society, a powerful tool that confirms access to life-sustaining resources and services, alongside evolving opportunities: It is enshrined in the Universal Declaration of Human Rights. Digital innovations in identity bring new opportunities to create transparency, fairness, and better governed services. They also create the potential to distribute and interpret significant amounts of information about people and their communities.

The Alan Turing Institute (Turing) brings together leading UK universities and visiting fellows from international centres of academic excellence to develop pioneering work in data science and artificial intelligence, theoretical and applied mathematics.

The Turing’s work in trustworthy data systems is advancing applied research for data science, artificial intelligence, and privacy enhancing encryption that is delivering significant impact in the fields of healthcare, national security, finance, and criminal justice. Its Trustworthy Digital Infrastructure for Identity Systems project is further developing this impact with a transformative opportunity to mature collective appreciation for the design and development opportunities to be had, and the policy choices to be made in upholding trust as a systemic imperative for identity systems.

Understanding the different trust and security requirements is an essential step towards their appropriate, secure and independent use and functions. The ability to ensure trustworthy operations in users’ identity lifecycle management is often more than the narrow scope of security requirements and regulatory compliance, while technology in Identity management is evolving faster than regulatory and security requirements. Thus, the ability to design and develop appropriate risk-based approaches requires trust-related requirements embedded in the process.

This conference brings together prominent academics and key players in the field of digital identity from government and industry sectors to focus on opportunities in the assessment and development of trustworthy digital identity systems. Outlined themes and key questions cover the driving influences behind the development of these systems, alongside the characteristics that can attest to whether these systems are deserving of trust.  They also seek to reflect the social impact, cultural, societal and behavioural conventions that have a role to play in anticipating vulnerabilities for the people these systems are being set up to serve.

A special collection in Data & Policy - a peer-reviewed, open access journal published by Cambridge University Press - has been launched in tandem with this Turing conference.

The resulting collection of papers aims to bring together knowledge that will inform countries’ development of trustworthy identity systems, and positively influence the ecosystem of standards, the decisions of policy makers and the technologies that are taken forward.

Questions to Explore

• What is influencing the development of digital identity systems?
• What are the essential factors of success in terms of user acceptance and adoption?
• How are threats and risks evolving with the identity landscape?
• What are the key considerations for ensuring the credibility of data processing?
• How can or should the relative capacities of different systems architectures be assessed?
• What is the impact of SSI on the trustworthiness of the identity lifecycle?
• What are the considerations for openness, transparency and explainability of automated and AI-based identity management?
• How should cultural and socio-economic differences influence systems design?

Common themes to guide but not limit submissions

• Combating fraud
• Threats
• Inclusion and diversity
• Cross-border interoperability
• Governance, risk and compliance
• Identity and access management
• User consent / control
• Biometrics
• Ethical machine learning
• Privacy-preserving ML techniques
• PETs
• Decentralised identity
• Zero trust authentication and access management
• Zero knowledge proofs
• Differential privacy
• Secure multi-party computation techniques

Submissions Process

Conference submissions are to be made directly to The Alan Turing Institute. [1] The conference is open to both stand-alone presentations and submissions from authors interested in contributing to the Data & Policy Special issue to be published in 2022. Presentation-only submissions from authors published in other journals will also be considered. Submissions will be assessed for their relevance to the conference theme and contributions to the session debates on the day.

To participate in the Data & Policy Special Issue interested authors are asked to provide extended abstracts of between 800 - 1000 words, references excluded. Following the conference, selected authors will be invited to submit their full papers through the Data & Policy online peer-review system for the 15th December. 

Authors are also asked to indicate which type of submission they are interested in writing for the full paper for submission to Data & Policy. Data & Policy publishes:

• Research articles that use rigorous methods that demonstrate how data science can inform or impact policy by, for example, improving situation analysis, predictions, public service design, and/or the legitimacy and/or effectiveness of policy making. Published research articles are typically reviewed by three peer reviewers: two assessing the academic or methodological rigour of the paper; and one providing an interdisciplinary or policy-specific perspective. (Approx 8,000 words in length).
• Commentaries are shorter articles that discuss and/or problematize an issue relevant to the Data & Policy scope. Commentaries are typically reviewed by two peer reviewers. (Approx 4,000 words in length).
• Translational articles are contributions that show how data science principles, techniques and technologies are being used in practice in organisational settings to improve policy outcomes. They may present original findings but are less embedded in the scholarly literature as research articles. They are typically reviewed by two peer reviewers, who assess the rigour and policy significance of the paper. (Approx 8,000 words in length).

Interested authors are encouraged to familiarise themselves with the Data & Policy Instructions for Authors.

Note that the journal provides LaTeX and Word templates to assist authors with the structure of papers, asks all authors to provide a Data Availability Statement with the submission and encourages, but does not require, authors to make underlying data and replication materials available via an open repository.

Key dates

• July 30th -  Deadline for all conference abstracts
• September 13th - Turing conference held
• December 15th - Submission of full papers to Data & Policy
• May - Publication of special issue in Data & Policy

Visit the event webpage to learn more and submit your abstract.