Some interesting trends have emerged in 2023, which hint at AI’s potential while also raising significant ethical and information security considerations. A recent Forbes Advisor survey reports that:
Accordingly, Elevate is treading optimistically – yet cautiously – when it comes to AI! While we are exploring how AI can create efficiencies in our work, we are also committed to maintaining the highest quality and privacy standards for our clients.
I recently spoke with a handful of my most forward-thinking and tech-savvy Elevate colleagues, who offered their thoughts on what AI applications are and aren’t helpful in aspects of their work advising nonprofit clients. We share their insights here for your consideration as we all navigate this brave new world.
Because many of the questions Elevate receives about AI are about ChatGPT specifically, we begin with the 411 on this tool.
Even if you haven’t yet used it yourself, you’ve undoubtedly heard the buzz about ChatGPT. ChatGPT is a free, natural language processing tool that can answer questions and support users with tasks such as composing emails, essays, and code. It can spew out responses in a matter of seconds. It does this by analyzing your question or prompt, then – using the dataset it was trained on – predicting the next word or series of words based on what you’ve entered.
But is it savvy enough to write sophisticated, nuanced, and winning grants?
Our colleagues were unequivocal in their response: Not even close.
This is because ChatGPT lacks the context, experience and judgment to handle such complex work. Even when I asked ChatGPT “What are the Pros and Cons of Using ChatGPT for grant writing?” it didn’t disagree! While ChatGPT praised its speed and ability to maintain consistency in “tone, language, and messaging” across various sections of a grant proposal and to polish language, it cautioned that it may not fully appreciate the “nuances” of grant guidelines, that it has limitations in understanding the context of an organization’s work and history, and that it could also produce plagiarizing text.
The text that ChatGPT generates in response to a question or prompt might not even be factual – there are absolutely no assurances that the information is accurate or true.
What’s more, because ChatGPT and other AI models draw upon existing content, AI can reflect underlying societal biases, perpetuating stereotypes and white supremacist notions. At Elevate, we know that historically marginalized communities are not “vulnerable” objects of charity, but agents and partners of the social change that they desire to see. This level of social context is far too complex for an AI-powered language model to appropriately reflect.
So, what are the appropriate uses of ChatGPT?
If you do want to experiment with ChatGPT in your writing tasks, we suggest using it for simpler, less analytical tasks, such as condensing word count, identifying alternative phrasing to avoid repetition, or summarizing the main points of your research into more readable language.
ChatGPT also has the potential to provide administrative support for your work, and can be harnessed to:
I know what you are thinking: It’s no surprise that a grant writing firm is telling me not to use an AI tool to write grants! But we are not just saying this because we want to be your grant writers. (Though we DO want to be your grant writers!)
At Elevate, we firmly believe that good grant writing is a thoughtful, strategic exercise that requires skill, nuance, and informed decision making. ChatGPT – like other AI tools – is neither thoughtful nor strategic. It lacks discernment of nuance, and is incapable of making reasoned choices about how to present an organization’s work to a funding partner.
Simply producing large volumes of content – that may or may not be factual! – is NOT the point of grant writing. And this is truly all that ChatGPT is doing: generating text.
At Elevate, some of our staff are experimenting with the use of AI-powered tools such as Simon Says AI and Fathom Notetaker to capture meeting notes and provide summaries of important conversations that they need to refer back to later or share with colleagues who couldn’t attend meetings. By using AI tools for more administrative tasks, you can free up some of your own time and energy for tasks that require thought and strategy – something AI can’t do!
As a tool developed by Google, Bard can interface with Google Workspace tools, if you choose to connect these. This means, you can ask Bard to find dates, taks, or other information in gmail, or to summarize a report a colleague shared via Google docs.
Interested in exploring more options for what you can do with AI tools? Check out FutureTools.io, which aggregates AI tools suited for different purposes.
If you take only one thing away from this article, I hope it is this: get informed about the privacy of the information you share with AI tools, and take precautions to protect your information.
When using any cloud-based technology platform, it is imperative that consideration be given to the way these tools use, store, and share information. Depending on your privacy settings, information you share with tools like Bard and ChatGPT may be used to improve its own language model. This means your data may not only be available to its creators (OpenAI), but also to others who use the platform.
For instance, when first accessing Bard, users are notified that Google will collect conversations and other information like the user’s location, store this data for a period of time, and use it to refine the tool. Furthermore, users are informed that “human reviewers read, annotate, and process your Bard conversations,” and they are warned to not share confidential information.
For these reasons, think carefully about what information you share with AI tools. Remember that a grant application may include information about your organization, programs, staff, and future plans that might be considered private. A good rule of thumb is, if you wouldn’t want a piece of data or information on your public website for anyone to find, you should not share that information with an AI tool.
How is your organization using AI powered tools, and what have you found useful, scary, hopeful, or exciting about these tools? We invite you to share!
Are you still feeling overwhelmed, or do you want to learn more? Here are a few sources the team at Elevate is using to stay informed:
Diversified revenues are crucial for just about any organization, creating sustainability and resilience when a funding source runs dry. While human services organizations may have a substantial public funding portfolio, and many government grants require a private funding match, this does not mean that other sources of revenue – including earned income and philanthropic funds – should take a back seat in your funding strategy. In fact, I encourage you to think differently about philanthropy and its role in supporting human services providers.
Imagine you’re on the leadership team of a service provider that implements a highly effective program for returning citizens; clients successfully maintain housing and jobs, and avoid further justice-system involvement. A contract with the state Department of Justice makes up the majority of the program budget, with the balance coming from a Master Leasing initiative and one wealthy individual donor who gives annually. For the most part, the program is meeting the needs of the population it currently reaches, but there is zero capacity for expansion, innovation, or outreach.
The Board and leadership team is concerned with the long-term sustainability for the program, and next steps involve developing a strategy to diversify revenues for the organization. A discussion ensues around pursuing foundation grants as a key tactic for diversification. The leadership team considers which aspects of the program may be well-suited to private grant opportunities. Should you seek grant opportunities for direct program expenses like rent and food assistance? Or are foundations more likely to support a new outreach component focused on engaging those who are incarcerated before their release? Perhaps you should seek General Operating Support?
If invited to that debate, I would argue that public funds can and should be used for direct programmatic expenses, whereas there may be a unique role for private foundations to provide the funding needed to build capacity, test new ideas, and establish the evidence for what works.
My advice to the leadership and development teams at human services organizations: Do not primarily think of private foundation grants and other philanthropic contributions as a budget gap-filler. Consider where public funds can and should be used, and where private philanthropy can have a unique impact.
For example, social services organizations might focus philanthropic asks on:
Above all, the grant request most likely to be funded is the one that is aligned with the foundation’s own priorities, adheres to its proposal guidelines, and for which you have the encouragement of foundation program officers, Board members, or other decision makers to apply.
Is your organization ready to establish (or grow) a private grants program? The team at Elevate can help! Reach out to us at firstname.lastname@example.org to learn more about our work with nonprofits throughout the U.S. to build smart and strategic grants programs.
March 1, 2018
Logic models are tools that help you understand how effective programs are designed.
The Kellogg Foundation defines a logic model as, “a systematic and visual way to present and share your understanding of the relationships among the resources you have to operate your program, the activities you plan, and the changes or results you hope to achieve.”
At Elevate, we typically incorporate a theory of change in our logic models, to show how Activities and Changes directly relate to each other. We’ll talk more about what that means a little later in this post.
To help you get started, you can download Elevate’s Logic Model template below:
When putting together your own logic model, you can use either forward logic or reverse logic.
With forward logic:
With reverse logic:
These are your resources; what you have. Examples might include: time, money, reputation, board, expertise. These are resources you will always have, regardless of the specifics of your programs.
These are the key elements of your program, what you do and how you do it. So, for a mentoring program this might be that students meet with their mentor once a week, talk with their mentor twice a week and come to an entire org event once a month. It is what defines your program, the things you do!
This is the quantitative evidence of your program and the activities you implement. So, for a mentoring program this might be that the organization has 20 mentees, 25 mentors and 5 whole organization activities. These are quantitative and detail what are actually doing.
The theory of change is not necessarily part of your logic model – though we think incorporating the ideas behind a theory of change can help strengthen the content of your logic model.
Put simply, a theory of change is a researched-based, tested explanation for how your inputs lead to your outputs. How your program design will lead to the change you want. An effective theory of change relies on tested assumptions and an effective strategy.
The reason we added theory of change in our logic model is because it gives you a clear representation of where theory of change happens. Specifically, it occurs right on that line that divides Outputs from Outcomes; here, you’re illustrating your belief that your activities and outputs will lead to the outcomes (change) you want to see.
As explained by the Catholic relief services, “When theories of change are well captured in logical or results frameworks, program managers can use them to articulate what programs are trying to achieve and what they think needs to happen to get there.” Laying your logic model out using this framework this really explains how your program is designed to work. It also makes it very easy to change if something isn’t working. If you don’t achieve the outcomes you want, you need to understand if your theory of change is flawed or if you lack fidelity to your model.
Ideally, your theory of change is based on evidence that your activities will lead to the results you want. For example, if mentoring a student, you could have the mentor meet with the student once a month or once a week. To decide you would have to research the best practices to achieve the greatest results. This of course comes from a lot of research! You need to stay up to date about your issue area and the best practices in the field.
Finally, this section illustrates the change that comes about because of your work. It is what you achieve. It is really important that these are measurable. If they aren’t, there is no way to prove your impact.
Outcomes are split into three different levels.
First are short-term outcomes that are changes in knowledge, attitude or skills. For a mentoring organization an example of this would be 75% of students increase their reading scores by 2 points (as measured by the reading scores provided by the school).
Second are mid-term outcomes, which are changes in behavior or actions. For a mentoring organization an example of this would be 75% of students showing increased promotion and graduation rates relative to peers; improved self-efficacy (as measured by General Self-Efficacy Inventory).
Third and finally are long-term outcomes, which are changes in quality of life. For a mentoring organization an example of this would be 50% college enrollment or post-graduate training.
Now that we’ve reviewed all the parts of a logic model, you can use a logic model as a tool to improve and fine-tune your program design, and highlight these changes in your grant proposals!
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