Fundraising.AI

A Framework toward Responsible and Beneficial AI for Fundraising

Working together for Fundraising.AI that supports a vibrant philanthropic sector.

While many Responsible and Beneficial AI frameworks exist within the for-profit and nonprofit sectors, there are no existing frameworks that address the fundraising profession, which represents almost $500 billion annually in the United States, helping to support millions of charitable missions worldwide.

We aim to change that.

About The Framework

Collaborative Initiative Driving Ethical Innovation and Trust in the Nonprofit Sector

The Fundraising.AI collaborative is a member-driven initiative supporting those working within the fundraising profession with the opportunity to collectively learn about Responsible and Beneficial AI, demonstrate their leadership around the subject, support best practices of Responsible and Beneficial AI applications, and support building a thriving charitable giving sector. The Framework for Responsible and Beneficial AI for Fundraising is intended to maximize the benefits of AI for fundraising purposes while minimizing the risk of damage to the hard-fought public trust of the nonprofit sector.

Framework toward
Responsible and Beneficial AI for Fundraising

The Framework below should be incorporated into ethical standards, business, and hiring practices and built into the overall design of AI ecosystems.

Fundraising AI Actors must protect personal and sensitive data by following robust security standards within our respective roles, maintaining compliance with relevant data protection regulations, and respecting the privacy of donors, beneficiaries, and stakeholders.

These principles should be part of all phases of the AI system lifecycle, including;

1. Consent,
2. Control over the use of data,
3. Ability to restrict data processing,
4. Right to rectification,
5. Right to erasure,
6. Adherence to privacy laws.

Commit to ethical data collection standards, including, analysis and usage practices, ensuring that the data used is accurate, relevant, and collected with proper consent. 

Actively address biases and disparities throughout the entire AI system lifecycle, by developing a framework to monitor, evaluate and design the AI systems through principles including;

1. Non-discrimination and prevention of bias,
2.  Representative and
high quality data,
3. Fairness,
4. Equality,
5. Inclusiveness in impact,
6. Inclusiveness in design.
 

Share accountability with Fundraising AI Actors for the AI applications that we develop, deploy, or utilize in the fundraising profession, ensuring that they align with our organization's or client's mission, values, and ethical principles that are;

1. Verifiable and replicable,
2. Auditable,
3. Appealable,
4. Remediable,
5. Liable.
 

Within reasonable efforts to safeguard corporate IP, will be transparent in the development, deployment, and utilization of AI technologies, providing, requiring or requesting clear explanations of AI methodologies, results, reporting, measurement, and potential impacts on participants. In addition, we will provide adequate visibility to consumers of our AI ecosystems outputs when autonomous AI has been utilized.

Commit to the responsible use of tested and untested resources while staying informed about the latest developments in Responsible and Beneficial AI, incorporating best practices into my work within the fundraising profession, and to share the responsibility of helping educate the broader fundraising community on Responsible and Beneficial AI best-practices. 

Actively engage with and learn from my peers in Fundraising.AI, sharing my experiences, challenges, and successes in Responsible and Beneficial AI for fundraising. 

Commit to being aware of, and abiding by, applicable laws, regulations, and best practices concerning AI development and operations pertaining to fundraising, data protection, and AI systems. 

Strive to maximize the positive social impact of AI in fundraising while minimizing any potential harm by focusing on the needs of beneficiaries and communities.

Commit to considering the long-term sustainability and environmental impact of AI technologies and advocate for sustainable AI practices within my organization and the broader fundraising community. 

Name
Kevin Andrews
Tazio Carrirolo
Jean-Luc Mommaerts
Kristen Theisen
Melody Watson
Dayna Stock
Sofía Alemán
Bevan Alloys
erik cooke
Zoe Lewis
Adal Fraile
Nate Nordstrom
Alisa Smallwood
Sergio Camilo Durán
George kodipo
ATANDELE BUAZU
Mattia Dell'Era
nicklas vibæk
Meredith Begin
Moses Sanumala
Kelli King-Jackson
Zachary Bailey
Karl Cline
George kodipo
Meredith Begin
Sooji Rhodes Rhodes
JANVIER NZAYIKORERA
Dave Sternberg
Hussein Hussein
Christina Development

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