Glossary

A framework to help institutions better understand and reduce the risks associated with Automated Decision Systems and to provide the appropriate governance, oversight and reporting/audit requirements that best match the type of application being designed.

Software that automatically makes predictions, makes decisions and/or gives advice by using data analysis, statistics and/or self-learning logic.

Any systems, software, or process that use computation to aid or replace government decisions, judgments, and/or policy implementation that impact opportunities, access, liberties, rights, and/or safety.

“Bias” is a broad term used to describe “outcomes which are systematically less favorable to individuals within a particular group and where there is no relevant difference between groups that justifies such harms.” Source: https://www.brookings.edu/research/algorithmic-bias-detection-and-mitigation-best-practices-and-policies-to-reduce-consumer-harms/

Being able to explain on an individual level why an Algorithmic System leads to a particular decision or outcome. Unless the Parties expressly agree otherwise, this will in any event include a clear indication of the key factors that have led an Algorithmic System to a particular result and the changes to the input that must be made in order to arrive at a different result. Making an Algorithmic System Explainable includes the provision of all the technical and other information required in order to explain, in objection proceedings, appeal proceedings or other legal proceedings, how a Decision has come about and to offer the other party and any other interested parties the opportunity to assess the way in which a Decision has come about, so as to offer the other party realistic legal protection.

Procedural fairness is a guiding principle of governmental and quasi-judicial decision-making. The degree of procedural fairness that the law requires for any given decision-making process increases or decreases with the significance of that decision and its impact on rights and interests.

The provision of information on the purpose of the Algorithmic System and the process followed in the development and application of the Algorithmic System and the data used in that context, which should in any event be deemed to include the provision of an understanding of the choices and assumptions made, the categories of data used in the development of the Algorithmic System, the way in which human intervention is provided for in the Algorithmic System, the method used to identify risks, the risks identified, and the measures taken to mitigate the risks, as well as the parties that were involved in the development of the Algorithmic System and their roles.

Procurement is one of the most legislated and regulated fields of government, and yet it is not clearly defined through an agreed-upon framework, with government agencies often using the terms “purchasing,” “contracting,” or “acquisition,” interchangeably. Typically, public procurement activities are outlined in the procurement guidelines of the public agencies and organizations. The absence of a clear framework of public procurement can complicate the development accountability mechanisms that cut across organizations. For the purpose of this primer, we adopt the following definition of public procurement: Public procurement is the designated legal authority to advise, plan, obtain, deliver, and evaluate a government’s expenditures on goods and services that are used to fulfill stated objectives, obligations, and activities in pursuant of desired policy outcomes.

“Public Use Technology” refers to technological systems used by public agencies. Public use technology includes AI systems. Public use technology is slightly different from “public interest technology” (PIT). PIT is an emerging field in which technologists, designers, strategists, researchers, and policymakers leverage digital technologies to create more sustainable and inclusive economic and governance systems. This does not necessarily need to happen within public agencies, but can be driven by other organizations and actors.

Computer program in its original programming language, human readable, before translation into object code usually by a compiler or an interpreter. It consists of algorithms, computer instructions and may include developer's comments.

The provision of information enabling NAME OF ORGANIZATION to understand the technical operation of the Algorithmic System, which may in any event be deemed to include the disclosure of the source code of the Algorithmic System, the technical specifications used in developing the Algorithmic System, the data used in developing the Algorithmic System, technical information on how the data used in developing the Algorithmic System were obtained and edited, information on the method of development used and the development process undertaken, substantiation of the choice for a particular model and its parameters, and information on the performance of the Algorithmic System.