ABOUT THIS BOOK
The book is divided into three parts. Part I, “Understanding and Using Artificial Intelligence,” focuses on the leadership needed to use smart tech well, the history of smart tech, and key issues for using it that organizations need to be prepared for: the need to stay deeply human-centered in planning and use of smart tech, the enormous amounts of clean data necessary to power the systems, and the ethical concerns and considerations necessary to ensure bias is mitigated.
Part II, “The Smart Nonprofit: Use-Case Examples and Management,” focuses on the applications of smart tech within organizations. It begins with a chapter to carefully and thoughtfully select a specific application of smart tech. Chapters on the use of smart tech for program delivery, fundraising, back-office operations, and philanthropy follow.
Part III, “Where We Go from Here,” concludes with a look about the probable future of nonprofits and social change in an automated world.
CONCLUSION
We wrote this book to help organizations prepare to benefit from automation and avoid mistakes. Smart tech can help nonprofits become more efficient and use that dividend of time to build better relationships with stakeholders inside and outside of the organization. Smart tech can better leverage data to better understand program impact. We want nonprofits to harness this technology for good, which requires organizational leaders to understand the limitations of smart tech and apply it strategically, ethically, and with responsibility.
Ultimately, the purpose of using smart tech shouldn't be to make organizations go faster but to make your organization better at solving problems and taking care of people inside and outside in more humane ways. This will only happen when everyone in the organization has the information, tools, and opportunity to shape their own lives and futures. That's the true mark of success for a smart nonprofit and what we will share in the rest of the book.
ENDNOTES
1 1. Sydney Brownstone, “This data tool helps homeless people get housing. If you're white, your chances are even better,” The Seattle Times (October 29, 2019), https://www.seattletimes.com/seattle-news/homeless/this-data-tool-helps-homeless-people-get-housing-if-youre-white-your-chances-are-even-better/.
2 2. Leah Post, author email interview on July 9, 2021.
3 3. Heather L. McCauley, ScD; Taylor Reid, BA, Michigan State University, “Assessing Vulnerability, Prioritizing Risk: The Limitations of the VI-SPDAT for Survivors of Domestic & Sexual Violence” (July 20, 2020), https://dcadv.org/file_download/inline/b1bb3b28-8039-4590-aa1d-daaef5fb6546.
4 4. Iain De Jong, author interview on June 25, 2021.
5 5. Jake Maguire, author interview on June 30, 2021.
6 6. Steve MacLaughlin, “The Impact of AI on Philanthropy” Engage Podcast Series (October 20, 2020), https://nofilternonprofit.blackbaud.com/raise-engage-podcast-series/episode-167-the-impact-of-ai-on-philanthropy.
7 7. Chris Arsenault, “Using AI, Canadian city predicts who might become homeless,” Reuters (October 15, 2020), https://www.reuters.com/article/us-canada-homelessness-tech-idCAKBN27013Y.
8 8. Heejae Lim, author interview on August 4, 2021.
9 9. Google AI Impact Challenge (https://ai.google/social-good/impact-challenge/).
10 10. TalkingPoints website, https://talkingpts.org/talkingpoints-increases-parent-engagement-for-student-success/415/.
11 11. Nicholas Carr, The Glass Cage (New York: W. W. Norton & Company; September 8, 2015).
12 12. Cathy O'Neill, Naked Capitalism Blog, August 26, 2027, https://www.nakedcapitalism.com/2017/08/data-scientist-cathy-oneil-algorithms-opinions-embedded-code.html.
13 13. Nancy Smyth, author interview on May 25, 2021.
14 14. Ruha Benjamin, Race After Technology (New York: Wiley; June 17, 2019).
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