├── LICENSE ├── .gitignore ├── book-list.md └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 Diego Arenas 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | 36 | # Installer logs 37 | pip-log.txt 38 | pip-delete-this-directory.txt 39 | 40 | # Unit test / coverage reports 41 | htmlcov/ 42 | .tox/ 43 | .nox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | *.py,cover 51 | .hypothesis/ 52 | .pytest_cache/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | target/ 76 | 77 | # Jupyter Notebook 78 | .ipynb_checkpoints 79 | 80 | # IPython 81 | profile_default/ 82 | ipython_config.py 83 | 84 | # pyenv 85 | .python-version 86 | 87 | # pipenv 88 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 89 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 90 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 91 | # install all needed dependencies. 92 | #Pipfile.lock 93 | 94 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 95 | __pypackages__/ 96 | 97 | # Celery stuff 98 | celerybeat-schedule 99 | celerybeat.pid 100 | 101 | # SageMath parsed files 102 | *.sage.py 103 | 104 | # Environments 105 | .env 106 | .venv 107 | env/ 108 | venv/ 109 | ENV/ 110 | env.bak/ 111 | venv.bak/ 112 | 113 | # Spyder project settings 114 | .spyderproject 115 | .spyproject 116 | 117 | # Rope project settings 118 | .ropeproject 119 | 120 | # mkdocs documentation 121 | /site 122 | 123 | # mypy 124 | .mypy_cache/ 125 | .dmypy.json 126 | dmypy.json 127 | 128 | # Pyre type checker 129 | .pyre/ 130 | -------------------------------------------------------------------------------- /book-list.md: -------------------------------------------------------------------------------- 1 | # Book list 2 | 3 | * [Algorithms of Oppression: How Search Engines Reinforce Racism](https://www.goodreads.com/book/show/34762552-algorithms-of-oppression). Safiya Umoja Noble (2018). 4 | * [Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence](https://www.goodreads.com/book/show/50131136-atlas-of-ai). Kate Crawford (2020). 5 | * [Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor](https://www.goodreads.com/book/show/34964830-automating-inequality). Virginia Eubanks (2018). 6 | * [Awkward Intelligence: Where AI Goes Wrong, Why It Matters, and What We Can Do about It](https://www.goodreads.com/book/show/60254404-awkward-intelligence). Katharina A Zweig, Noah Harley (Translator) (2022). 7 | * [Careless People: A Cautionary Tale of Power, Greed, and Lost Idealism](https://www.goodreads.com/book/show/223436601-careless-people). Sarah Wynn-Williams (2025). 8 | * [Code: And Other Laws of Cyberspace, Version 2.0](https://www.goodreads.com/book/show/44874.Code). Lawrence Lessig (2006). [💾](https://commons.wikimedia.org/wiki/File:Code_v2.pdf) 9 | * [Corruptible: Who Gets Power and How It Changes Us](https://www.goodreads.com/book/show/56898187-corruptible). Brian Klaas (2021). 10 | * [Data Driven Nonprofits](https://www.goodreads.com/book/show/31680472-data-driven-nonprofits). Steve MacLaughlin (2016). 11 | * [Data Feminism](https://www.goodreads.com/book/show/51777543-data-feminism). Catherine D’Ignazio, Lauren F. Klein (2020). 12 | * [Designing Freedom](https://www.goodreads.com/book/show/25891345-designing-freedom). Stafford Beer (1974). [🔈](https://www.cbc.ca/radio/ideas/the-1973-cbc-massey-lectures-designing-freedom-1.2946819) 13 | * [Differential Privacy](https://direct.mit.edu/books/book/5935/Differential-Privacy). Simson L. Garfinkel (2025). [💾](https://direct.mit.edu/books/book-pdf/2509392/book_9780262382168.pdf) 14 | * [Empire of AI: Inside the reckless race for total domination](https://www.goodreads.com/book/show/227601327-empire-of-ai). Karen Hao (2025). 15 | * [Factfulness: Ten Reasons We're Wrong About the World – and Why Things Are Better Than You Think](https://www.goodreads.com/book/show/34890015-factfulness). Hans Rosling, Ola Rosling, Anna Rosling Rönnlund (2018). 16 | * [Free Software, Free Society: Selected Essays](https://www.goodreads.com/book/show/942560.Free_Software_Free_Society). Richard M. Stallman, Lawrence Lessig, Joshua Gay (Editor) (2002). [💾](https://www.gnu.org/philosophy/fsfs/rms-essays.pdf) 17 | * [Giants: The Global Power Elite](https://www.goodreads.com/book/show/40923001-giants). Peter Phillips (2018). 18 | * [Hello World: How to be Human in the Age of the Machine](https://www.goodreads.com/book/show/39312982-hello-world). Hannah Fry (2018). 19 | * [How an Economy Grows and Why It Crashes](https://www.goodreads.com/book/show/7048818-how-an-economy-grows-and-why-it-crashes). Peter D. Schiff (2010). 20 | * [How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers](https://www.goodreads.com/book/show/201280067-how-to-make-the-world-add-up). Tim Harford (2020). 21 | * [Invisible Women: Data Bias in a World Designed for Men](https://www.goodreads.com/book/show/41104077-invisible-women). Caroline Criado Pérez (2019). 22 | * [Mindf*ck: Cambridge Analytica and the Plot to Break America](https://www.goodreads.com/book/show/52269471-mindf-ck). Christopher Wylie, Graham Halstead (Narrator) (2019). 23 | * [Not the End of the World: How We Can Be the First Generation to Build a Sustainable Planet](https://www.goodreads.com/book/show/145624737-not-the-end-of-the-world). Hannah Ritchie (2024). 24 | * [⿻ 數位 Plurality: The Future of Collaborative Technology and Democracy](https://www.goodreads.com/book/show/211810531-plurality?from_search=true&from_srp=true&qid=fP0ngmzFnu&rank=1). E. Glen Weyl, ⿻ Community (contributor), Audrey Tang (2024). [💾](https://www.plurality.net/chapters/) 25 | * [Poor Economics: A Radical Rethinking of the Way to Fight Global Poverty](https://www.goodreads.com/book/show/10245602-poor-economics). Abhijit V. Banerjee, Esther Duflo (2011). 26 | * [Programming Differential Privacy](https://programming-dp.com). Joseph P. Near and Chiké Abuah (2021). [💾](https://programming-dp.com/book.pdf) 27 | * [Race After Technology: Abolitionist Tools for the New Jim Code](https://www.goodreads.com/book/show/42527493-race-after-technology). Ruha Benjamin (2019). 28 | * [Skin in the Game: The Hidden Asymmetries in Daily Life](https://www.goodreads.com/book/show/36064445-skin-in-the-game). Nassim Nicholas Taleb (2018). 29 | * [The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power](https://www.goodreads.com/book/show/.26195941-the-age-of-surveillance-capitalism). Shoshana Zuboff (2020). 30 | * [The Black Box Society: The Secret Algorithms That Control Money and Information](https://www.goodreads.com/book/show/21878126-the-black-box-society). Frank Pasquale (2015). 31 | * [The Black Swan: The Impact of the Highly Improbable](https://www.goodreads.com/book/show/242472.The_Black_Swan). Nassim Nicholas Taleb (2007). 32 | * [The Boy Who Could Change the World: The Writings of Aaron Swartz](https://www.goodreads.com/book/show/23258925-the-boy-who-could-change-the-world). Aaron Swartz, Lawrence Lessig (Introduction) (2016). 33 | * [The Drunkard's Walk: How Randomness Rules Our Lives](https://www.goodreads.com/book/show/2272880.The_Drunkard_s_Walk). Leonard Mlodinow (2008). 34 | * [The Ethical Algorithm: The Science of Socially Aware Algorithm Design](https://www.goodreads.com/book/show/44244975-the-ethical-algorithm). Michael Kearns, Aaron Roth (2019). 35 | * [The Great Escape: Health, Wealth, and the Origins of Inequality](https://www.goodreads.com/book/show/17942017-the-great-escape). Angus Deaton (2013). 36 | * [The Hacker Ethic](https://www.goodreads.com/book/show/2052871.The_Hacker_Ethic). Pekka Himanen, Linus Torvalds (Contributor), Manuel Castells (Epilogue) (1999). 37 | * [The New Empire of AI: The Future of Global Inequality](https://www.goodreads.com/book/show/214944941-the-new-empire-of-ai). Rachel Adams (2025). 38 | * [The Open Revolution: Rewriting the rules of the information age](https://www.goodreads.com/book/show/40515943-the-open-revolution). Rufus Pollock (2018). [💾](https://openrevolution.net/media/open-revolution.pdf) 39 | * [The Tech Coup: How to Save Democracy from Silicon Valley](https://www.goodreads.com/book/show/208187020-the-tech-coup). Marietje Schaake (2024). 40 | * [Think Stats: Exploratory Data Analysis, 3rd edition](https://www.goodreads.com/book/show/231074472-think-stats). Allen Downey (2025). [💾](https://allendowney.github.io/ThinkStats/index.html) 41 | * [Thinking, Fast and Slow](https://www.goodreads.com/book/show/11468377-thinking-fast-and-slow). Daniel Kahneman (2011). 42 | * [Treasure Islands: Uncovering the Damage of Offshore Banking and Tax Havens](https://www.goodreads.com/book/show/10197857-treasure-islands). Nicholas Shaxson (2011). 43 | * [Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy](https://www.goodreads.com/book/show/28186015-weapons-of-math-destruction). Cathy O'Neil (2016). 44 | * [Who Owns the Future?](https://www.goodreads.com/book/show/15802693-who-owns-the-future). Jaron Lanier (2013). 45 | 46 | > Note 1: There are downloadable ebooks marked with the 💾 icon and audiobooks with the 🔈 icon, but please consider buying the book from the author. 47 | 48 | > Note 2: This is a personal list of books that I think can be relevant in your journey into Data for Good and the local and global issues. 49 | 50 | > Note 3: Please send me your book recommendations creating a [new issue](https://github.com/darenasc/awesome-data-for-good/issues/new). 51 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome Data for Good 2 | 3 | Curated list of resources about Data for Good, Data Science for Good, Data Science for Social Good, Data Science for Public Good, Data for Humanity. 4 | 5 | [![Awesome](https://awesome.re/badge.svg)](https://awesome.re) 6 | ![](https://img.shields.io/github/last-commit/darenasc/awesome-data-for-good/main) 7 | ![](https://img.shields.io/github/stars/darenasc/awesome-data-for-good?style=social) 8 | 9 | ## Table of Contents 10 | - [Books](#books) 11 | - [Courses](#courses) 12 | - [Data Science for Social Good Summer Programs](#data-science-for-social-good-summer-programs) 13 | - [Ethics](#ethics) 14 | - [Events](#events) 15 | - [Funding](#funding) 16 | - [Global projects](#global-projects) 17 | - [Organisations](#organisations) 18 | - [Readings](#readings) 19 | - [Research](#research) 20 | - [Workshops](#workshops) 21 | - [Resources](#resources) 22 | - [Frameworks, Guidelines, and Standards](#frameworks-guidelines-and-standards) 23 | - [Other awesome awesome repositories](#other-awesome-awesome-repositories) 24 | 25 | ## [Books](book-list.md) 26 | 27 | ## Courses 28 | 29 | * [Data for Social Impact course](https://trainingspi.wustl.edu/courses/data-science-for-social-impact--4f8b9d53-2d3e-42f4-88fd-9f07ebabbdee/salespage) by the Social Policy Institute (SPI) at Washington University in St. Louis. 30 | * [Foundations of Humane Technology](https://www.humanetech.com/course). A free, self-paced online course for professionals shaping tomorrow's technology 31 | 32 | ## Data Science for Social Good Summer Programs 33 | 34 | * [Data Science for Social Good summer at eScience Institute, University of Washington, US](https://escience.washington.edu/using-data-science/data-science-for-social-good/). [(Projects 2022)](https://escience.washington.edu/2022-data-science-for-social-good-projects/) 35 | * [Data Science for Social Good at Warwick University, UK](https://warwick.ac.uk/research/data-science/warwick-data/dssgx/). 36 | * [Data Science for Social Good Fellowship at DFKI, Germany](https://sebastian.vollmer.ms/dssg/). 37 | * [Data Science for Social Good, Munich 2023, Germany](https://sites.google.com/view/dssgx-munich-2023/startseite?authuser=0). 38 | * [Data Science for Social Good Summer Fellowship at Carnegie Mellon University, US](https://www.dssgfellowship.org). 39 | * [Data Science for Social Good at Data Science Institute, University of British Columbia, US](https://dsi.ubc.ca/data-science-social-good). 40 | * [Data Science for Social Good Summer Program at Stanford University, US](https://datascience.stanford.edu/programs/data-science-social-good-summer-program). 41 | * [Data Science for the Common Good at Center for Data Science, University of Massachussetts Ahmherst, US](https://ds.cs.umass.edu/industry/data-science-common-good). 42 | * [Data Science for the Public Good, Biocomplexity Institute, University of Virginia, US](https://biocomplexity.virginia.edu/institute/divisions/social-and-decision-analytics/dspg). 43 | * [Data Science for the Public Good Young Scholars Program, Iowa State University, US](https://dspg.iastate.edu). 44 | * [Florida Data Science for Social Good (FL-DSSG) Program, US](https://dssg.unf.edu). 45 | 46 | ## Ethics 47 | 48 | * [deon](https://deon.drivendata.org). An ethics checklist for data scientists. 49 | * [Ethical OS Toolkit](https://ethicalos.org). a guide to anticipating the future impact of today’s technology. 50 | * [Ethically Aligned Design v2](https://standards.ieee.org/wp-content/uploads/import/documents/other/ead_v2.pdf). A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems. 51 | * The Markkula Center's [An Ethical Toolkit for Engineering/Design Practice](https://www.scu.edu/ethics-in-technology-practice/ethical-toolkit/) ([pdf](https://www.scu.edu/media/ethics-center/technology-ethics/Ethics-Toolkit.pdf)) 52 | * [Practical Data Ethics course](https://ethics.fast.ai). 53 | * [Practitioner's Guide Data Ethics Toolkits v1.0](https://datakind-ai-ethics.netlify.app/#/). Within this handbook, we attempt to analyze and critique some key tools, packages and software for fairness and explainability of algorithms, in order to assist you when developing techniques around data. 54 | 55 | ## Events 56 | 57 | * [AI for Good Global Summit](https://aiforgood.itu.int). AI for Good is a year-round digital platform where AI innovators and problem owners learn, build and connect to identify practical AI solutions to advance the UN SDGs. 58 | * [Geo for Good Summit 2024](https://earthoutreachonair.withgoogle.com/events/geoforgood24-dublin), [2023](https://earthoutreachonair.withgoogle.com/events/geoforgood23), [2022](https://earthoutreachonair.withgoogle.com/events/geoforgood22), [2021](https://earthoutreachonair.withgoogle.com/events/geoforgood21), [2020](https://earthoutreachonair.withgoogle.com/events/geoforgood20). The Summit is intended for nonprofit, academic, public sector, private sector, and Indigenous peoples and local communities who are using (or want to learn to use) our mapping tools (such as Google Earth, Earth Engine, Environmental Insights Explorer, and My Maps) for planetary sustainability and human resilience around the world. 59 | * [Good Tech Fest](https://www.goodtechfest.com). Driving Impact with Emerging Technologies. 60 | 61 | ## Funding 62 | 63 | * [Google.org Impact Challenge: Tech for Social Good](https://impactchallenge.withgoogle.com/techforsocialgood). Get up to six months of full-time support from a team of Google.org Fellows and up to €3M funding for ‘Tech for Social Good’ projects. 64 | * [Skoll Foundation](https://skoll.org). We invest in social entrepreneurs and other social innovators who offer a compelling vision, creative solutions, and proven approaches. 65 | * [X-Prize Foundation](https://www.xprize.org). A trusted, proven platform for impact that leverages the power of competition to catalyze innovation and accelerate a more hopeful future by incentivizing radical breakthroughs for the benefit of humanity. 66 | 67 | ## Global projects 68 | 69 | * [UN Sustainable Development Goals](https://sdgs.un.org/goals) 70 | * [Global Index on Responsible AI](https://www.responsibleaiindex.org) 71 | 72 | ## Organisations 73 | 74 | * [AI in Africa](https://aiinafrica.org). AI in Africa is a platform which delivers forward-thinking initiatives that equip the next generation of leaders with the skills and mindset to succeed tomorrow’s world. 75 | * [AINow Institute](https://ainowinstitute.org). The AI Now Institute aims to produce interdisciplinary research and public engagement to help ensure that AI systems are accountable to the communities and contexts in which they’re applied. 76 | * [Correlaid](https://correlaid.org/en/). CorrelAid is a non-partisan non-profit network of data science enthusiasts who want to change the world through data science. 77 | * [Data2x](https://data2x.org). We drive solutions to fill gender data gaps. 78 | * [Data for Development Network (D4D.net)](https://www.d4d.net). Advancing the ethical and responsible use of data to address critical development challenges both globally and locally. 79 | * [Data for Good Canada](https://dataforgood.ca). We are a collective of passionate socially minded people who are empowering social change makers to be better by allowing their data to speak to them. 80 | * [Data For Good France](https://dataforgood.fr). Accélérateur citoyen d'intérêt général. 81 | * [Data for Good Madrid](https://www.dataforgoodmad.com). Somos una comunidad de Data Scientists para crear impacto. 82 | * [Data for Good Netherlands](https://data-for-good.com/#). Empowering People to Overcome the Global Challenges our Planet Faces Together. 83 | * [DataForGoodBCN](http://dataforgoodbcn.com). Un colectivo de personas voluntarias que usamos nuestras habilidades para ayudar a ONGs y entidades sociales a aprovechar el poder de sus datos. 84 | * [DataDotOrg](https://data.org): Democratizing data, for good. data.org is a platform for partnerships to build the field of data science for social impact. We work with organizations from all over the world to increase the use of data science in order to improve the lives of millions of people. 85 | * [DataKind](https://www.datakind.org). Our mission is to transform the impact of social change organisations through data science capacity building, for the benefit of the people of the UK and other parts of the world. 86 | * [DataKindUK](https://datakind.org.uk). Our mission is to transform the impact of social change organisations through data science capacity building, for the benefit of the people of the UK and other parts of the world. 87 | * [Data Science for Social Good Foundation](http://www.datascienceforsocialgood.org). We create and sustain communities, programs, and solutions that enhance the use of responsible data science and AI for equitable social good. 88 | * [Data Science for Social Good Portugal](https://www.dssg.pt/en/home/). We help non-profit, non-governmental and governmental organizations harness the power of their data to improve its impact on the community. 89 | * [DSSG Berlin](https://dssg-berlin.org/en/). We help NGOs to make use of their data by connecting them with volunteer data scientists and analysts. 90 | * [DrivenData](https://www.drivendata.org): Data science competitions to build a better world. 91 | * [EAAMO (Equity and Access in Algorithms, Mechanisms, and Optimization) ](https://www.eaamo.org). A global community of researchers working towards equity and access. 92 | * [GIZ Data-lab](https://www.blog-datalab.com). Brings together practitioners and creatives to promote the effective, fair, and responsible use of digital data for sustainable development. 93 | * [Humanitarian OpenStreetMap Team](https://www.hotosm.org). An international team dedicated to humanitarian action and community development through open mapping. 94 | * [IEEE Humanitarian Technologies](https://ieeeht.org). The IEEE Humanitarian Technologies mission is to support impactful and ethically informed volunteer-led initiatives, programs and projects. 95 | * [Institute for Accountability in the Digital Age (I4ADA)](https://i4ada.org). The mission is to ensure that those issues and concerns do not undermine the Internet’s potential for increasing access to knowledge, spreading global tolerance and understanding, and promoting sustainable prosperity. 96 | * [Mechanism Design for Social Good (MD4SG)](https://www.md4sg.com). A multi-institutional initiative using techniques from algorithms, optimization, and mechanism design, along with insights from other disciplines, to improve access to opportunity for historically underserved and disadvantaged communities. 97 | * [Nesta](https://www.nesta.org.uk). The UK's innovation agency for social good. 98 | * [Partnership on AI (PAI)](https://partnershiponai.org). Non-profit partnership of academic, civil society, industry, and media organizations creating solutions so that AI advances positive outcomes for people and society. 99 | * [OECD AI Policy Observatory](https://oecd.ai/en/). We provide data and multi-disciplinary analysis on artificial intelligence. Our diverse global community of partners makes this platform a unique source of information and dialogue on AI. 100 | * [SoGooD²ata](https://sogooddata.org/). Spanish NGO which aims at solving social issues applying data science techniques. 101 | * [UN Global Pulse](https://www.unglobalpulse.org). Brings together governments, UN entities and partners from academia and the private sector to design, co-create and scale innovations. 102 | * [Viz for social good](https://www.vizforsocialgood.com). Connecting data enthusiasts with mission-driven organizations. 103 | * [ThinkTech NGO](https://www.thinktech.ngo). ThinkTech is a politically neutral non-governmental organisation. We are committed to the independence and autonomy of ThinkTech’s projects and do not accept funding that is conditioned upon conducting research in a particular manner, achieving a particular result, or taking a predetermined position. 104 | 105 | ## Readings 106 | 107 | * [AI for Good: Applications in Sustainability, Humanitarian Action, and Health](https://www.wiley.com/en-us/AI+for+Good%3A+Applications+in+Sustainability%2C+Humanitarian+Action%2C+and+Health-p-9781394235889). Discover how AI leaders and researchers are using AI to transform the world for the better. January 2024, 432 Pages. 108 | * [AI for Social Good, Using Artificial Intelligence to Save the World](https://www.wiley-vch.de/en/areas-interest/finance-economics-law/business-management-13ba/general-introductory-business-management-13ba0/business-technology-13ba03/ai-for-social-good-978-1-394-20578-3). Understand the real power of AI and and its ability to shape the future for the better. March 2024, 336 Pages. 109 | * [Responsible Data Handbooks](https://the-engine-room.github.io/responsible-data-handbook/). Being, a Complete, Illustrated Guide to Responsible Data Usage, Manners, and General Deportment. The Engine Room, 2021. 110 | * [The Data for Good Growth Map](https://escience.washington.edu/wp-content/uploads/2021/11/Data4Good_GrowthMap.pdf), whitepaper. Decision Points for Designing a University-Based Data for Good Program (November 2021). eScience Institute, University of Washington, US. 111 | * [The Open Data Handbook](http://opendatahandbook.org/guide/en/). This handbook discusses the legal, social and technical aspects of open data. It can be used by anyone but is especially designed for those seeking to **open up** data. It discusses the **why, what and how** of open data – why to go open, what open is, and the how to ‘open’ data. 112 | 113 | ## Research 114 | 115 | * [ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization](https://eaamo.org). 116 | * [ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)](https://facctconference.org/). 117 | * [ACM GOODIT 2024](https://blogs.uni-bremen.de/goodit2024/). ACM 4th International Conference on Information Technology for Social Good. 4-6 September 2024, Bremen, Germany. 118 | * [Artificial Intelligence, Ethics, and Society Conference (AAAI/ACM)](https://www.aies-conference.com/2024/). 119 | * [Data for Social Good](https://link.springer.com/book/10.1007/978-981-19-5554-9) open access book (2023). Non-Profit Sector Data Projects. 120 | * [Journal of Computational Social Science](https://www.springer.com/journal/42001). 121 | * [Fairness, Accountability, and Transparency in Machine Learning (FATML)](https://www.fatml.org). 122 | * [Meta's Data for Good](https://dataforgood.facebook.com/dfg/about). 123 | * [Microsoft's AI For Good Research Lab](https://www.microsoft.com/en-us/research/group/ai-for-good-research-lab/). 124 | * [The Eurpoean Phisical Journal (EPJ) Data Science](https://epjdatascience.springeropen.com) 125 | * [The International Peace Information Service (IPIS)](https://ipisresearch.be). An independent research institute providing tailored information, analysis and capacity enhancement to support those actors who want to realize a vision of durable peace, sustainable development and the fulfillment of human rights. 126 | * [Stanford Social Innovation Review](https://ssir.org/). 127 | 128 | ### Workshops 129 | * [NeurIPS2018 AI For Social Good Workshop (AISG)](https://aiforsocialgood.github.io/2018/). 130 | * [ICLR2019 AI For Social Good Workshop (AISG)](https://aiforsocialgood.github.io/iclr2019/) 131 | * [ICML2019 AI For Social Good Workshop (AISG)](https://aiforsocialgood.github.io/icml2019/) 132 | * [NeurIPS2019 Joint Workshop on AI for Social Good (AISG)](https://aiforsocialgood.github.io/neurips2019/index.htm). 133 | 134 | ## Resources 135 | 136 | * [ATLAS of Sustainable Development Goals 2023](https://datatopics.worldbank.org/sdgatlas/). Presents interactive storytelling and data visualizations about the 17 Sustainable Development Goals. 137 | * [Correlaid documentation for Data for Good projects](https://docs.correlaid.org). 138 | * [Correlaid's Projects Database](https://www.correlaid.org/en/using-data/project-database/) 139 | * [Data for Good Organisations Map](https://epsilon.cs.ucy.ac.cy/index.php/sample-page/european-map/). 140 | * [Data Science for the Public Sector](https://github.com/DS4PS/). Courses and tools to create capacity and attract talent in the public and nonprofit sectors 141 | * [Data to the People](https://www.datatothepeople.org). Data To The People is a global leader in data literacy assessment and development. 142 | * [Decision Tree for the Responsible Application of AI](https://www.aaas.org/ai2/projects/decision-tree-practitioners). A guide to operationalizing a broad set of principles that AAAS has identified as core components of an ethical approach to developing and implementing artificial intelligence. 143 | * [DFx Viz Tool](https://data.undp.org/tools/viz-tool). This UNDP tool lets you transform numbers into compelling visual stories with ease and precision. 144 | * [fAIr: AI-assisted Mapping](https://github.com/hotosm/fAIr). Open AI-assisted mapping service developed by the [Humanitarian OpenStreetMap Team (HOT)](https://www.hotosm.org/) that aims to improve the efficiency and accuracy of mapping efforts for humanitarian purposes. 145 | * [GapMinder](https://www.gapminder.org). Gapminder identifies systematic misconceptions about important global trends and proportions and uses reliable data to develop easy to understand teaching materials to rid people of their misconceptions. 146 | * [GeoHub](https://geohub.data.undp.org). UNDP GeoHub is a centralised ecosystem of geospatial services to support staff and development policy makers in the context of SDGs. 147 | * [Global Index on Responsible AI](https://www.responsibleaiindex.org). Measuring progress on the responsible use of AI in over 120 countries around the world. 148 | * [Global Partnership for Sustainable Development Goals](https://www.data4sdgs.org). A global network using data to achieve the Sustainable Development Goals—improving lives, fighting inequality, and promoting environmental sustainability. 149 | * [Open Source for Social Sector Organizations](https://socialimpact.github.com/developers//intro-to-open-source/). A guide on how to implement open source for organizations who are driving social impact. 150 | * [Our World in Data](https://ourworldindata.org). Research and data to make progress against the world’s largest problems. 151 | * [UN AI Resource Hub](https://unaihub.aiforgood.itu.int). Explore and share AI-related activities from across the UN system, access resources, foster collaboration, and build on existing initiatives effectively.. 152 | * [UN Global Platform](https://unstats.un.org/bigdata/un-global-platform.cshtml). Data For the World. A global collaboration to harness the power of data for better lives. 153 | * [SDG Data Availability Monitor (beta)](https://sdg-monitor.ethz.ch). 154 | * [The Humanitarian Data Exchange](https://data.humdata.org). Find, share and use humanitarian data all in one place. 155 | * [THE TECH WORKER HANDBOOK](https://techworkerhandbook.org). The Tech Worker Handbook is a collection of resources for tech workers who are looking to make more informed decisions about whether to speak out on issues that are in the public interest. 156 | 157 | ## Frameworks, Guidelines, and Standards 158 | 159 | * [Data maturity framework for the not-for-profit sector](https://static1.squarespace.com/static/5d514d1775e9c90001345670/t/620b8207ec052e35eb5d713c/1644921354014/Data_Orchard_Data_Maturity_Framework_v2.1+2022-14-02.pdf). Version 2.1 © Data Orchard CIC January 2022, replacing version 2 published October 2019 and version 1 created in partnership with DataKind UK in January 2017. 160 | * [Digital Public Goods Standard](https://digitalpublicgoods.net/standard/). The Digital Public Goods Standard is a set of specifications and guidelines designed to maximise consensus about whether a digital solution conforms to the definition of a digital public good. 161 | * [Principles for Digital Development](https://digitalprinciples.org). The Principles for Digital Development are nine living guidelines that are designed to help integrate best practices into technology-enabled programs and are intended to be updated and refined over time. 162 | * [The Montréal Declaration for a Responsible Development of Artificial Intelligence](https://montrealdeclaration-responsibleai.com/the-declaration/). 163 | 164 | ## Other awesome awesome repositories 165 | 166 | * [Awesome AI Guidelines](https://github.com/EthicalML/awesome-artificial-intelligence-guidelines) 167 | * [Awesome GIS](https://github.com/sshuair/awesome-gis) 168 | * [Awesome Public Datasets](https://github.com/awesomedata/awesome-public-datasets) 169 | * [Awesome Production Machine Learning](https://github.com/EthicalML/awesome-production-machine-learning) 170 | * [Public APIs](https://github.com/public-apis/public-apis) 171 | --------------------------------------------------------------------------------