Phil­an­thropy meets Arti­fi­cial Intel­li­gence: Driving Ethi­cal Innovation

To address the oppor­tu­ni­ties and ethi­cal chal­lenges AI pres­ents, the Geneva Centre for Phil­an­thropy (GCP), in part­ner­ship with the Botnar Foun­da­tion, laun­ched a project explo­ring AI’s impact on phil­an­thropy and vice versa. Ancho­red by an inter­na­tio­nal confe­rence and the Rout­ledge Hand­book of Arti­fi­cial Intel­li­gence and Phil­an­thropy this initia­tive lays the foun­da­tion for meaningful dialog and innovation.

Geneva Conven­tion: Explo­ring the Inter­sec­tion of AI and Philanthropy

The inter­na­tio­nal confe­rence in Geneva high­ligh­ted the multi­ple facets of the dual rela­ti­onship between AI and phil­an­thropy. It show­ca­sed appli­ca­ti­ons such as AI-driven tools for envi­ron­men­tal moni­to­ring, health inter­ven­ti­ons in under­ser­ved areas, and opti­mi­zed phil­an­thro­pic decis­ion-making through machine learning.

Using AI Responsibly

AI’s inte­gra­tion within phil­an­thropy pres­ents both signi­fi­cant oppor­tu­ni­ties and risks. The confe­rence explo­red seve­ral impactful AI appli­ca­ti­ons within civil society, inclu­ding AI-driven mapping tools to combat envi­ron­men­tal abuses, AI in health inter­ven­ti­ons for remote areas, and machine lear­ning to enhance phil­an­thro­pic decis­ion-making. Howe­ver, spea­k­ers high­ligh­ted signi­fi­cant chal­lenges to address, inclu­ding bias, lack of trans­pa­rency, and cyber­se­cu­rity risks, parti­cu­larly for smal­ler orga­niza­ti­ons strugg­ling with data breaches.

Experts empha­si­zed that simply adop­ting AI is not enough. To truly bene­fit, POs must rethink their struc­tures and busi­ness models to fully leverage AI. While AI’s effi­ci­ency and cost-saving poten­tial can bene­fit phil­an­thropy, its adop­tion should prio­ri­tize public good over effi­ci­ency, addres­sing risks like privacy viola­ti­ons and bias.

The Role of Phil­an­thropy in Shaping Ethi­cal AI

Phil­an­thropy is not just an adop­ter of AI; it is a pivo­tal player in shaping an ethi­cal and inclu­sive AI land­scape, a sever­ely under-discus­sed topic. Posi­tio­ned between the private and public sectors, POs can advo­cate for AI frame­works that uphold trust, iden­tity, and social justice.

AI’s influence goes beyond intel­li­gence – it impacts decis­ion-making proces­ses that carry ethi­cal impli­ca­ti­ons for commu­ni­ties and the envi­ron­ment. Phil­an­thropy can cham­pion just and fair regu­la­tory frame­works while empowe­ring civil society to play an active role in AI deve­lo­p­ment, imple­men­ta­tion, and regu­la­tion. This happens through support­ing rese­arch, enga­ging with poli­cy­ma­kers, and foste­ring dialog on trust and iden­tity in the digi­tal age. Moreo­ver, as AI resha­pes work, phil­an­thropy may need to adapt to support socie­ties tran­si­tio­ning toward new econo­mic reali­ties in a poten­tial post-work future.

A Compre­hen­sive Resource: The Rout­ledge Hand­book of Arti­fi­cial Intel­li­gence and Philanthropy

Expan­ding on the Conference’s know­ledge co-crea­tion process, The Hand­book, published in 2024, offers a multi-disci­pli­nary perspec­tive on the dyna­mic rela­ti­onship between AI and phil­an­thropy. Divi­ded into four sections, it provi­des a robust foun­da­tion for acade­mics and prac­ti­tio­ners alike.

1. AI Trans­forming Philanthropy:

This section exami­nes how AI is revo­lu­tio­ni­zing the phil­an­thro­pic sector by enhan­cing opera­tio­nal effi­ci­ency, impro­ving impact measu­re­ment, and foste­ring inno­va­tion across various domains such as fund­rai­sing, outreach, gover­nance, and donor enga­ge­ment. It explo­res diverse AI appli­ca­ti­ons, from lever­aging large language models for draf­ting and moni­to­ring to using machine lear­ning for finan­cial analy­sis and immersive tech­no­lo­gies like meta­ver­ses to deepen donor connections.

In a contri­bu­ting chap­ter, Stefan Schöbi, CEO of StiftungSchweiz, empha­si­zes the urgency of fast-track­ing AI adop­tion in phil­an­thropy. He outlines how tech­no­lo­gies like LLMs can enhance fund­rai­sing and grant allo­ca­tion while provi­ding a frame­work for asses­sing AI readi­ness. The chap­ter offers blue­prints for key use cases, such as iden­ti­fy­ing funders, perso­na­li­zing propo­sals, and auto­ma­ting appli­ca­tion pre-selec­tion, addres­sing concerns and oppor­tu­ni­ties through surveys and interviews.

2. Global Perspec­ti­ves and Challenges:

Secondly, the Hand­book analy­zes the inter­sec­tion of AI and phil­an­thropy across diffe­rent geogra­phies. From the United States and China to Switz­er­land and the Balkans, these case studies comple­ment and enrich the volume’s theo­re­ti­cal perspec­ti­ves, provi­ding a global perspec­tive on the field.

3. Phil­an­thropy Shaping AI:

Section 3 explo­res philanthropy’s criti­cal role in advan­cing ethi­cal AI. Topics include Data Phil­an­thropy, the use of AI in bridging global divi­des and in advo­ca­ting for demo­cra­tic decis­ion-making in AI gover­nance. The authors also propose stra­te­gies for robust regu­la­ti­ons to address risks and offer recom­men­da­ti­ons for crea­ting a more inclu­sive and respon­si­ble AI future.

4. Ethics and Values in AI:

The conclu­ding section empha­si­zes inclu­si­vity, fair­ness, and trans­pa­rency as guiding prin­ci­ples for AI use and deve­lo­p­ment within phil­an­thropy. It explo­res the ethi­cal impli­ca­ti­ons of AI-driven donor decis­i­ons, stra­te­gies for alig­ning AI with phil­an­thro­pic values, and the role of phil­an­thropy in advo­ca­ting for open-source, inclu­sive AI approaches.

A Call for Ongo­ing Dialog

Over­all, acting as a cata­lyst for the discus­sions on AI and phil­an­thropy, the confe­rence as well as the Hand­book provide a neces­sary over­view of the inter­ac­tion between these two sectors. One, howe­ver, that is in no way defi­ni­tive. Rese­arch in the field of AI and phil­an­thropy, parti­cu­larly in areas such as cyber­se­cu­rity and enhan­ced colla­bo­ra­tion in phil­an­thropy regar­ding AI, requi­res further exami­na­tion. It is the objec­tive of these project outco­mes to lay the ground­work to inspire, inform and call for further rese­arch into this fasci­na­ting inter­ac­tion whose poten­tial, as well as its dangers, should not be over­loo­ked. By foste­ring part­ner­ships and advan­cing rese­arch, the GCP’s initia­tive provi­des a blue­print for ensu­ring AI serves huma­nity – while still reflec­ting the core values of philanthropy.

Boot­camp: Arti­fi­cial intel­li­gence (AI) for nonpro­fits and funders

Arti­fi­cial intel­li­gence (AI) is proving to be a double-edged sword: the signi­fi­cant simpli­fi­ca­tion and assis­tance in day-to-day work is clou­ded by ques­ti­ons about relia­bi­lity, power consump­tion or ethi­cal concerns. Our boot­camp builds on the findings of the Lear­ning Jour­ney, provi­des a compact intro­duc­tion to the topic and high­lights the oppor­tu­ni­ties and risks of using AI. We examine how nonpro­fits can submit funding appli­ca­ti­ons more effec­tively and how funders can evaluate them more precis­ely thanks to AI. We demons­trate how to increase acces­si­bi­lity and focus on the essen­tial ques­ti­ons — whilst also explo­ring the limits of respon­si­ble AI use and what AI means from a data protec­tion perspec­tive.

Next event: 09.05.2025, 9–15h, on site in Basel or via live­stream
Price: CHF 690 for funders, CHF 490 for nonpro­fits
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