Understanding the strengths and weaknesses of the available low-code/no-code tools will help you pick the right tool for the job and balance their sometimes significant weaknesses with their tremendously valuable strengths.
This blog post discusses strategies that states can implement to make public assistance applications more accessible during the COVID-19 crisis, emphasizing the importance of flexibility in application processes to accommodate increased demand and social distancing measures.
Code for America’s Integrated Benefits Initiative has been working in partnership with the State of Colorado to demonstrate how user-centered approaches lead to measurably better delivery of safety net programs. This article describes their work with the state of Colorado in simplifying how clients report common life changes that can affect their eligibility.
This playbook is designed to help government and other key sectors use data sharing to illuminate who is not accessing benefits, connect under-enrolled populations to vital assistance, and make the benefits system more efficient for agencies and participants alike.
In this interview, Code for America staff members share how client success, data science, and qualitative research teams work together to consider the responsible deployment of artificial intelligence (AI) in responding to clients who seek assistance with three products.
This guidebook offers an introduction to the risks of discrimination when using automated decision-making systems. This report also includes helpful definitions related to automation.
The guidelines for bias-free language contain both general guidelines for writing about people without bias across a range of topics and specific guidelines that address the individual characteristics of age, disability, gender, participation in research, racial and ethnic identity, sexual orientation, socioeconomic status, and intersectionality.
Jennifer Pahlka, Deputy CTO in President Obama’s Administration and author, shares her new book, Recoding America on how government must be equipped for digital delivery in order to meet ambitious policy goals. This video was recorded at the Digital Benefits Conference (BenCon) at Georgetown University on June 14, 2023.
This report offers a critical framework for designing algorithmic impact assessments (AIAs) by drawing lessons from existing impact assessments in areas like environment, privacy, and human rights to ensure accountability and reduce algorithmic harms.
