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Key Terms & Definitions
Algorithm Impact Assessment
“The Algorithm Impact Assessment (AIA) is a questionnaire designed to help you assess and mitigate the risks associated with deploying an automated decision system. The AIA also helps identify the impact level of your automated decision system. The questions are focused on your business processes, your data, and your system design decisions.” Source: https://canada-ca.github.io/digital-playbook-guide-numerique/views-vues/automated-decision-automatise/en/algorithmic-impact-assessment.html
Algorithm/AI/Machine Learning Model
“An algorithm is a set of instructions for how a computer should accomplish a particular task. … Algorithms are most often compared to recipes, which take a specific set of ingredients and transform them through a series of explainable steps into a predictable output. Combining calculation, processing, and reasoning, algorithms can be exceptionally complex, encoding for thousands of variables across millions of data points.” Source: https://datasociety.net/library/algorithmic-accountability-a-primer/
Algorithmic Auditing
“Algorithmic auditing is an effort to ensure that the context and purpose surrounding machine learning applications directly inform evaluations of their utility and fairness. By assessing the ways in which bias might emerge at each step in the development pipeline, it is possible to develop strategies for evaluating each aspect of a model for undue sources of influence. Further, because algorithmic audits encourage systematic engagement with the issue of bias throughout the model-building process, they can also facilitate an organization’s broader shift toward socially responsible data collection and use.” Source: https://www.businessofgovernment.org/sites/default/files/Algorithmic%20Auditing.pdf
Algorithmic Bias
“Algorithmic bias refers to certain attributes of an algorithm that cause it to create unfair or subjective outcomes. When it does this, it unfairly favors someone or something over another person or thing. Algorithmic bias can exist because of many factors. It could be the design of the algorithm – like when the way that the algorithm is written gives some data more importance than other data. It could be in the collection and selection of data – some things that should be computed by the algorithm are omitted, or data that shouldn’t be involved is.” Source: https://www.liberties.eu/en/stories/algorithmic-bias-17052021/43528
“Anonymization is a data processing technique that removes or modifies personally identifiable information; it results in anonymized data that cannot be associated with any one individual” Source: https://policies.google.com/technologies/anonymization
Automated Decision System
“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.” Source: https://www.amsterdam.nl/innovatie/algoritmen-ai/contractual-terms-for-algorithms/
“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/
“The California Consumer Privacy Act of 2018 (CCPA) gives consumers more control over the personal information that businesses collect about them and the CCPA regulations provide guidance on how to implement the law. This landmark law secures new privacy rights for California consumers, including: The right to know about the personal information a business collects about them and how it is used and shared; The right to delete personal information collected from them (with some exceptions); The right to opt-out of the sale of their personal information; and The right to non-discrimination for exercising their CCPA rights. Businesses are required to give consumers certain notices explaining their privacy practices. The CCPA applies to many businesses, including data brokers.” Source: https://oag.ca.gov/privacy/ccpa
Data Quality
“Data quality refers to the overall utility of a dataset(s) as a function of its ability to be easily processed and analyzed for other uses, usually by a database, data warehouse, or data analytics system.” Source: https://www.informatica.com/services-and-training/glossary-of-terms/data-quality-definition.html
Food and Drug Administration (FDA)
“The Food and Drug Administration is responsible for protecting the public health by ensuring the safety, efficacy, and security of human and veterinary drugs, biological products, and medical devices; and by ensuring the safety of our nation's food supply, cosmetics, and products that emit radiation. FDA also has responsibility for regulating the manufacturing, marketing, and distribution of tobacco products to protect the public health and to reduce tobacco use by minors. FDA is responsible for advancing the public health by helping to speed innovations that make medical products more effective, safer, and more affordable and by helping the public get the accurate, science-based information they need to use medical products and foods to maintain and improve their health. FDA also plays a significant role in the Nation's counterterrorism capability. FDA fulfills this responsibility by ensuring the security of the food supply and by fostering development of medical products to respond to deliberate and naturally emerging public health threats.” Source: https://www.fda.gov/about-fda/what-we-do
“Privacy is the right to be let alone, or freedom from interference or intrusion. Information privacy is the right to have some control over how your personal information is collected and used.” Source: https://iapp.org/about/what-is-privacy/
Public Procurement
“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. The absence of a clear framework of public procurement can complicate the development accountability mechanisms that cut across organizations. 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.” Source: https://archive.nyu.edu/bitstream/2451/62255/2/AI%20and%20Procurement%20Primer%20Summer%202021.pdf
Technical Explainability
“Being able to explain on an individual level why an Algorithmic System leads to a particular decision or outcome. This can 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.” Source: https://www.amsterdam.nl/innovatie/algoritmen-ai/contractual-terms-for-algorithms/
Technical Fairness
“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.” Source: https://www.amsterdam.nl/innovatie/algoritmen-ai/contractual-terms-for-algorithms/
Technical Transparency
“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.” Source: https://www.amsterdam.nl/innovatie/algoritmen-ai/contractual-terms-for-algorithms/
The Health Insurance Portability and Accountability Act (HIPAA)
“The Health Insurance Portability and Accountability Act of 1996 (HIPAA) is a federal law that required the creation of national standards to protect sensitive patient health information from being disclosed without the patient’s consent or knowledge. HIPAA Privacy Rule: “The Privacy Rule standards address the use and disclosure of individuals’ health information (known as “protected health information”) by entities subject to the Privacy Rule. These individuals and organizations are called “covered entities.” The Privacy Rule also contains standards for individuals’ rights to understand and control how their health information is used. A major goal of the Privacy Rule is to ensure that individuals’ health information is properly protected while allowing the flow of health information needed to provide and promote high quality health care and to protect the public’s health and well-being.” Source: https://www.cdc.gov/phlp/publications/topic/hipaa.html
Algorithm Impact Assessment
“The Algorithm Impact Assessment (AIA) is a questionnaire designed to help you assess and mitigate the risks associated with deploying an automated decision system. The AIA also helps identify the impact level of your automated decision system. The questions are focused on your business processes, your data, and your system design decisions.”
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