This playbook provides government-wide guidance for planning, procuring, and managing digital, data, and technology (DDaT) projects with a focus on innovation, agile delivery, cybersecurity, sustainability, and commercial best practices.
Making your service more inclusive means designing government services so that everyone who needs to use them can do so with as few barriers as possible, by understanding legal duties, identifying and removing exclusion points, and considering a wide range of user needs throughout the design process.
A practical framework from the UK Infrastructure and Projects Authority that helps government leaders plan, lead, and deliver complex transformation programs.
The paper hopes to stimulate discussions towards an ethical protocol for better practice in BI experiments and provide a useful resource to those working on, or interested in, BI research.
The Technology Code of Practice is a set of government guidelines for designing, building, and buying digital services and technology to ensure they are efficient, accessible, and cost-effective in the UK.
A guidance page explaining how government teams should evaluate and use commercial-off-the-shelf (COTS) products and services when building digital public services.
PolicyEngine is a nonprofit that provides a free, open-source web app enabling users in the US and UK to estimate taxes and benefits at the household level, while also simulating the effects of policy changes. By combining tax and benefits data, PolicyEngine helps individuals and policymakers better understand the impacts of existing policies and proposed reforms, using microsimulation models built from legislation and enhanced survey data.
User research requires working as a team, since it necessitates running sessions with participants, observing and moderating research sessions, analyzing and synthesizing results, as well as communicating results effectively.
This report presents evidence on the use of algorithmic accountability policies in different contexts from the perspective of those implementing these tools, and explores the limits of legal and policy mechanisms in ensuring safe and accountable algorithmic systems.
