Welcome to this module covering the application of generative AI tools to your grant-seeking work.
In this module, we will explore the use of generative AI in grant-seeking and its potential benefits and drawbacks. We will delve into the different kinds of generative AI technologies that can be applied to the grant-seeking process, and how they can be used for more efficient and effective grant-seeking.
Throughout this module, we will present various strategies and techniques for responsibly incorporating generative AI into your organization's grant-seeking process. We will discuss the limitations of generative AI and the areas where human expertise and oversight is still necessary.
By the end of this module, you will not only understand the potential impact of generative AI on the grant-seeking landscape, but also be able to identify potential future developments in generative AI that could impact grant-seeking.
Assess the pros and cons of AI for grant writing
Describe the benefits and drawbacks of using generative AI in grant-seeking.
Compare and contrast different AI grant writing tools
Compare and contrast different generative AI technologies and their potential applications in grant-seeking.
Strategize for responsible AI use
Develop a strategy for responsibly incorporating generative AI into your organization's grant-seeking process.
Recognize the limits of AI tools in grant-seeking
Understand the limitations of generative AI in grant-seeking and identify areas where human expertise is still necessary.
Envision the future of AI and philanthropic work
Explain the potential impact of generative AI on the grant-seeking landscape and identify potential future developments in generative AI that could impact grant-seeking.
Use this section like flashcards
When generative AI systems produce outputs that are illogical, nonsensical, or even offensive due to the limitations of the software
Software applications that use AI technology to assist with various tasks, such as generating content or analyzing data
The process of searching for and applying to grant opportunities to secure funding for an organization or project
Supervision or careful management of a process or situation
AI safety and responsibility frameworks
Guidelines and principles for the ethical and responsible development and use of AI technology
AI technology that is capable of generating text, images, or other content
Large language models (LLMs)
AI models trained on large datasets of text to learn patterns and relationships between words and phrases
The ability of a tool to handle increased performance demands to meet the needs of an organization as it grows
Have you encountered a term you'd like to see here?
Get in touch to submit a term you think should be added
The use of generative AI in grant writing can offer a wide range of benefits, including increased efficiency and the ability to generate a larger volume of grant proposals. By automating certain aspects of the process, such as generating the initial draft of a proposal or identifying potential funding sources, grant seekers can save valuable time and resources that can be allocated elsewhere.
However, there are also potential drawbacks to using AI in this process. One potential risk is that the proposals generated by AI may be too formulaic or lacking in creativity, which could decrease the chances of securing funding. Additionally, AI-generated proposals may not be able to capture the nuances of the grant seeker's organization or project, which could make the proposal less compelling to funders. To overcome these risks, it is extremely important to choose the right AI tools and to exercise careful oversight when deploying them.
How can AI grant writing increase efficiency?
When an organization is ready to apply for grant funding, and they have found a high-quality opportunity to pursue, the work of producing a grant application can begin. The most efficient organizations build upon existing work by repurposing language from recent proposals to produce new grant applications more quickly. Generative AI tools can supercharge this process by leveraging the incredible abilities of large language models to help locate and reformat grant proposal content in fractions of a second.
You're working on a grant application and you come across a question that you know you've answered before. The problem is that you can't recall which of the dozens of recent grant proposals in your content library contains the previous answer. You proceed to check file after file, searching through shared drives and inboxes looking for keywords and clues to help you locate what you’re looking for. Finally, after a few minutes, or in the worst cases, several hours or days, you locate the passage, which you copy and paste into your new draft.
If you are working on a grant application and need to find a previously answered question, consider using Grantable, a generative AI grant writing software. Grantable can instantly search through all the content in your library and retrieve meaningful excerpts that you may wish to reuse. This saves you from having to go through each document and folder individually. You can search your entire library at once and either select excerpts yourself or allow the AI to recommend resources. The entire process usually takes only a few seconds.
When crafting a grant proposal, it's common to reuse text from previous proposals. However, this can result in excess material that needs to be trimmed, updated, and adjusted to fit the new application question. Meeting vastly different length limits imposed by different application formats can be a significant challenge. For example, your source material may come from a proposal with a much longer format, requiring considerable effort to condense the text while preserving important information to meet a shorter word limit. The time required for this process can range from a few minutes to many hours, depending on the situation.
Grantable, a generative AI grant writing software, and other applications like ChatGPT excel at taking source material you provide and quickly reformatting it to address the various points in a grant application question and meet specific formatting requirements. These AI can also help revise and reformat the text to change details, perspective, tone, and more. Each of these processes takes only seconds, giving grant professionals more time and opportunities to curate and refine the overall proposal.
The bottom line
According to the 2023 State of Grantseeking Report produced by GrantStation, the top challenge reported by grant-seekers was insufficient time and capacity to pursue grant funding. Generative AI tools like Grantable can significantly reduce the time and energy required to produce high-quality grant applications, enabling organizations to apply for all the opportunities they may qualify for.
While there is no way to guarantee a successful funding outcome, grant-ready organizations that pursue well-aligned grant opportunities and submit as many qualified applications as possible are more likely to see success over time. By using generative AI tools like Grantable to store grant proposal content in a centralized and intelligent library, and leveraging generative AI writing features to reduce the amount of staff capacity per application, organizations can increase their chances of successful award outcomes.
Instantly search and retrieve excerpts
Takes only a few seconds
Need right keywords
Locates content based on meaning and context
Copy and paste
Select excerpts with a few clicks
Quickly reformat and revise text in seconds
Manual document search
Comparing different AI grant writing tools
In recent years, generative AI has gained more attention with the release of various tools like GPT-3 and ChatGPT. These tools have made it easier for people to experience the power of generative AI firsthand. The use of generative AI in grant writing is a relatively new field of exploration, and there are a few different tools available that are specifically designed for this purpose. In this section, we will compare some of the most popular AI grant writing tools and discuss their relative strengths and weaknesses.
ChatGPT is a free platform, which makes it accessible to all kinds of organizations. When you use ChatGPT, you will need to create an account on the platform's website. The sign-up process typically involves providing basic information such as name, email address, and password. Once you have created an account, you can log in and begin using the tool.
To create content using ChatGPT, you will need to provide a prompt or starting point for the AI to work with. This could be a question, a topic, or a general idea. ChatGPT will then generate a response based on the prompt, which you can review and edit as needed. The AI can also provide suggestions for related content or additional ideas to help you expand on your initial prompt.
Overall, the user experience of ChatGPT is designed to be simple and intuitive, with a user-friendly interface and helpful features to guide you through the content creation process.
To use ChatGPT as a grant writing tool, follow these steps:
Begin by prompting ChatGPT to act as a grant writer
Example prompt: “Act as a helpful grant writing assistant”
Next, provide the chatbot with source material you’d like it to use to help you draft grant proposal content
Example prompt: “The following is grant proposal content I’d like you to use for the purposes of helping me: [PASTE CONTENT]
Tip: Keep length limits in mind and share specific excerpts of your material, rather than large un-curated selections
Finally, prompt ChatGPT to draft content for you
Example prompt: “Using the content I’ve provided, please draft a response to the following grant application question: [PASTE GRANT APPLICATION QUESTION]
Optional: Once the chatbot has drafted a response, you have the option of asking it to revise and reformat the text
Example prompt: “Please revise your last answer to be 100 words or less, and use a more conversational tone.”
Many people will use ChatGPT to bring the grant narrative to a certain level of completion at which point they will copy and paste the text to another word processor to finalize
To use ChatGPT as a strategic tool, follow these steps:
Repeat steps 1 and 2 from above
Prompt ChatGPT to offer strategic advice to give you ideas of how best to construct your grant application
Example prompt: “Please share 10 examples of ways food banks play a vital role in the community”
Tip: Use the outputs to help you generate ideas for how best to convey the impact of the organization’s work
Example prompt: “Please suggest ways to respond to the following grant application prompt strategically, thoroughly, and in a compelling way: [PASTE GRANT PROPOSAL QUESTION]
Tip: Keep the outputs nearby as you work, to help you stay on track
Tip: Consider feeding these recommendations back into ChatGPT when requesting the chatbot’s help to write
Overall, ChatGPT is an incredibly powerful tool that can be a useful addition to anyone's toolkit. It is free, easy to use on both desktop and mobile devices, and extremely flexible in terms of its capabilities.
The biggest drawback of using ChatGPT for grant-seeking is the labor-intensive and repetitive process of providing context to the model before asking for outputs. ChatGPT is intended as a general-purpose interface to assist hundreds of millions of people worldwide with a wide range of queries and is therefore not optimized for understanding a specific organization or workflow. Feeding it context can significantly improve the focus and outputs of the tool, but it may still require searching through multiple files and folders to find the right content.
ChatGPT stores your interactions as chat threads, similar to text message conversations, which are excellent for managing conversations but inefficient for storing document information, such as grant proposals. Currently, there is no way to organize your different conversations with ChatGPT, which can make organization a challenge, especially if you're dealing with very complex grant-seeking programs.
As a chatbot, the interface is designed for people and ChatGPT to engage in back-and-forth dialogue. It is not structured for writing long-form documents, like grant proposals. There is no ability to edit or format like in a word processor, and it can be difficult to review a grant proposal when it has been rendered in the format of a conversation, rather than as a document with sections, prompts, and responses.
ChatGPT for grant writing pros and cons
Powerful and flexible tool
Requires labor-intensive and repetitive process of providing context
Free and easy to use on desktop and mobile
Not optimized for understanding a specific organization or workflow
Can be a useful addition to anyone's toolkit
Searching through multiple files and folders to find the right content
Excellent for managing conversations
Inefficient for storing document information, such as grant proposals
Can generate helpful outputs and suggestions
No way to organize different conversations with ChatGPT
Not structured for writing long-form documents, like grant proposals
Difficult to review grant proposals in conversation format
Grantable is a generative AI software designed specifically for grant-seeking. Similar to ChatGPT, it utilizes the latest large language models to provide comprehension and writing abilities. Additionally, it comes with a smart content library and a user-friendly word processing interface that simplifies grant content production.
To use Grantable, you must create an account using a valid email address. Many people start with a free account and upgrade later if they find the tool useful. Users must upload writing samples to their account, preferably a recently completed grant proposal, which Grantable processes as source material.
To begin working on a new grant proposal, create a new file in Grantable as you would in a typical word processor. Grantable's AI assistant can draft content at any point in the document and provide suggested source material snippets to respond to prompts. You can edit anything on the page, including the outputs of the Grantable assistant, and ask for revisions as well.
Grantable continuously updates all the content uploaded and created in an account, enabling it to locate the best source materials for a given task. With more content created, the system becomes better at drafting responses.
To use Grantable as a grant writing tool, follow these steps:
Create an account on the Grantable website using a valid email address
Grantable offers a free trial, and users can upgrade to a paid plan to continue using the tool after the trial runs out
Upload writing samples to your account, preferably a recently completed grant proposal, which Grantable processes as source material
Create a new file in Grantable as you would in a typical word processor
To prompt Grantable to generate content, select a text area in the document and engage the AI assistant
Locate and designate source materials from your library for the AI to use, or have the AI suggest source materials
Grantable's AI assistant will generate a response based on the prompt and source materials, which you can review and edit as needed.
Edit anything on the page, including the outputs of the Grantable assistant, and ask for revisions as well.
Once you have completed your grant proposal, you can export it as a PDF or Word document for submission.
Grantable continuously updates all the content uploaded and created in an account, enabling it to locate the best source materials for a given task. With more content created, the system becomes better at drafting responses.
While both Grantable and ChatGPT are generative AI tools that can be used for grant writing, there are significant differences between the two.
One of the biggest advantages of Grantable is that it is specifically designed for grant-seeking, while ChatGPT is a general-purpose AI tool. This means that Grantable is optimized for particular work and information cycles in the grant-seeking process. As a result, Grantable is more likely to generate high-quality, coherent grant proposals that are tailored to the needs of the specific grant opportunity.
Another advantage of Grantable is its smart content library. Unlike ChatGPT, which requires users to search through multiple files and folders to find the right content, Grantable continuously updates all the content uploaded and created in an account, enabling it to locate the best source materials for a given task. With more content created, the system becomes better at drafting responses.
Finally, Grantable provides a user-friendly word processing interface that simplifies grant content production. This makes it easier for users to manage grant proposals and make edits to their content as needed, something that is not possible with ChatGPT.
While ChatGPT can be a useful addition to anyone's toolkit, its general-purpose nature means that it may not be the best choice for grant writing. If you are serious about grant-seeking and want to maximize your chances of success, using a purpose-built tool like Grantable is the way to go.
ChatGPT vs. Grantable
It's really important to understand the difference between expert and generative AI systems, and if you don't understand this distinction, you could run into some serious problems. Here’s a real life example of this happening to a nonprofit organization, which I wrote about in this article.
Can generate helpful outputs and suggestions
Can draft high quality written outputs
Optimized for grant-seeking
Smart content library
Ability to locate and reformat grant proposal content
Ability to edit and format
Stores context between uses
Designed for word processing
Ability to organize grant proposal content
Adding AI to your organization
If you're considering incorporating generative AI into your grant-seeking process, there are several important factors to consider. Here are some key steps to take to ensure that you are making the best use of generative AI in your organization:
Identify the areas of your grant-seeking process where generative AI can be most helpful, such as content creation and review, proposal formatting, and content management.
Research the different generative AI technologies available and their potential applications in grant-seeking.
Choose the right generative AI tool for your organization's needs and budget.
Train your team on how to use the generative AI tool effectively and responsibly. It's important to ensure that everyone understands the limitations of the tool and that it should be used as a supplement to, not a replacement for, human expertise.
Identify the areas of your grant-seeking process where AI can help
Problem: Everyone experiences writer's block at some point. This can be especially difficult for grant-seekers who are just starting out and struggling to know what to write, or for highly experienced individuals who are fatigued or lacking inspiration.
Solution: Generative AI tools can be useful for grant-seekers in brainstorming and strategic planning. By providing prompts or starting points, these tools can generate ideas and suggestions that can help guide the grant-seeker's thought process and provide new perspectives on the problem at hand. For example, ChatGPT can provide strategic advice to give grant-seekers ideas of how best to construct a response in grant applications.
Problem: Good writing generally requires a substantial amount of time to produce. Even if you know the material, it can take a while to get the words onto the page, and more time to edit them into final form.
Solution: Generative AI can be used for content creation in grant proposal writing. By automating certain aspects of the process, such as generating the initial draft of a proposal, grant-seekers can save valuable time and resources that can be allocated elsewhere.
Problem: Every funder has different application formats and requirements, even if they’re requesting the same information. It can be a huge time-waster and hassle to reformat your content to meet these different situations.
Solution: Generative AI can help format grant proposals to meet different application requirements. It can recognize specific formatting requirements, such as tone and length limits, and adjust the proposal accordingly. This can save time and ensure that the proposal meets the specific needs of the funding opportunity.
Problem: Organizations and the tools we use are constantly evolving. Over time, written content tends to end up strewn all over different laptops, inboxes, and shared drives. This makes finding a particular document, page, paragraph, or sentence a time-consuming activity.
Solution: Generative AI systems that come equipped with a smart content library, like Grantable, leverage the power of large language models to search across vast data sets. This means that you don’t need to do as much organizing to keep track of everything.
Problem: For large organizations with many tracks of grant-seeking or professional grants consultants who work with many organizations to apply for grants, keeping content organized and separate across all of these workspaces can be problematic and quickly get out of hand.
Solution: Generative AI systems like Grantable allow you to create workspaces that separate content, which are easily navigable.
Researching different AI tools
Keeping in mind the needs identified above (brainstorming, composition, formatting, content management and program/client management), consider using the follow resources periodically to learn about the latest AI tools for each situation.
Use your the search engine of your choice (Google, Bing, etc.) to find tools to try by searching terms such as “generative AI tool for [INSERT YOUR NEED]”.
This website continually aggregates new AI tools and categorizes them by use. Search for the kind of tool or help you need and review the results.
Study the websites you find and consider important factors such as:
Functionality: Does the tool provide the functionality you need to achieve your goals? Are there any key features missing that would be critical to your organization?
Ease of use: Is the tool intuitive and user-friendly? Will your team be able to use it without requiring extensive training?
Integration: Can the tool be easily integrated with other tools and systems that your organization uses?
Customization: Does the tool allow for customization to meet your organization's unique needs?
Scalability: Can the tool scale to meet your organization's needs as it grows?
Security: Does the tool have appropriate security measures in place to protect sensitive data?
Support: Does the tool provide adequate support resources, such as documentation and customer service, to ensure that your team can use it effectively?
Cost: Is the tool affordable for your organization, and does it provide good value for the cost?
Follow technology journalism
We recommend the following podcasts as fun ways to stay up to date on the latest and most important discussions and trends in technology. This is a great way to hear about new tools and hone your ability to critique them.
When working with generative AI tools like Grantable, it's important to use them responsibly and collaboratively. Ensure that everyone on your team understands the limitations of the tool and how it should be used as a supplement to, not a replacement for, human expertise.
The Fundraising.AI collaborative is a member-driven initiative supporting those working within the fundraising profession with the opportunity to collectively learn about Responsible AI, demonstrate their leadership around the subject, support best practices of Responsible AI applications, and support building a thriving charitable giving sector. The Framework for Responsible 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.
There are many different AI safety and responsibility frameworks being proposed, and we’ve chosen to share this one because it is specifically adapted for fundraising. Here is the framework:
Privacy and Security
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;
Control over the use of data,
Ability to restrict data processing,
Right to rectification,
Right to erasure,
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;
Non-discrimination and prevention of bias,
Representative and high quality data
Inclusiveness in impact
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;
Verifiable and replicable
Transparency and Explainability
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 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 AI best-practices.
Actively engage with and learn from my peers in Fundraising.AI, sharing my experiences, challenges, and successes in Responsible 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.
Responsible AI for Fundraising Checklist
Share this list with other folks
Using this technology responsibly and ethically needs to be a community-wide effort
When using AI for generating ideas and content, it's important to remember that it has its limitations. For instance, AI cannot replace the expertise and knowledge of a human researcher, and it is not a good research tool. Additionally, while the speed of content creation with AI can be useful, it can also create new opportunities to make mistakes, as the technology can generate large amounts of content quickly, but may not catch errors or inconsistencies. Furthermore, keep in mind that AI has no grasp of real-world context, which can lead to inaccuracies or irrelevant content. Finally, AI has no understanding of truthfulness or factuality, meaning that the content it generates may not always be accurate or trustworthy. As a result, it's important to use AI as a supplement to, rather than a replacement for, human expertise and judgment.
There are four limitations to keep in mind when using AI for grant writing:
Generative AI is not a good research tool
The speed of content creation creates new opportunities to make mistakes
Generative AI has no grasp of real world context
Generative AI has no understanding of truthfulness or factuality
Why isn’t AI a good research tool?
When you use generative AI to generate text, it's important to understand what's really happening behind the scenes. Essentially, the generative AI is making complex predictions based on probabilities. Large language models analyze enormous datasets to learn patterns and relationships between words and phrases. They then use this knowledge to generate new text that is similar to the input data. The models are trained on huge datasets and use complex algorithms to predict what words or phrases are likely to come next in a given context. The model generates output by choosing words or phrases that are likely to follow the input, based on statistical probabilities.
It's important to keep in mind that the outputs created by generative AI are not based on actual understanding or comprehension of the content, but rather on patterns and relationships learned from the large dataset. While this can be useful for generating new ideas or content quickly, it's not a good substitute for in-depth research or analysis. Generative AI lacks the ability to critically evaluate sources, synthesize information, or draw conclusions based on a nuanced understanding of the subject matter. Additionally, generative AI may not be able to recognize biases or inaccuracies in the data it is trained on, leading to outputs that perpetuate these issues. As a result, it's important to use generative AI as a supplement to, rather than a replacement for, your own expertise and judgment when it comes to research.
💡 It's important to keep in mind that the outputs created by the AI are not based on actual understanding or comprehension of the content, but rather on patterns and relationships learned from the large dataset.
Search and Research Software
Finding and organizing information
Creating new content
List of relevant results
Content generated based on probability
High with high quality sources
Unknown without verification
Analysis and synthesis
Fact checking and editing
How does the speed of generative AI tools create new opportunities for mistakes?
Generative AI systems can produce pages of credible-sounding text in a matter of seconds. This is faster than most people can read, and a large quantity of AI-generated content requiring human approval can quickly pile up. Even those who initially review AI outputs vigilantly can be lulled into a false sense of security after a few minutes or hours of error-free products. It's crucial to remember that generative AI systems can inadvertently generate problematic content at any time.
A good way to think about writing with and without AI is to compare it to sewing by hand with a needle and thread versus using a sewing machine. When we write without AI assistance, we proceed only as quickly as the words come to us and we can type them. Similarly, with a needle and thread, we can only sew stitch by stitch, leaving us with plenty of time to guide the work.
Writing with AI assistance increases the speed of output exponentially, just like a sewing machine. You are now guiding a machine that moves much more quickly than a person can. The advantage, of course, is that you can complete a project much more quickly using a machine to assist, while the hazard is that even momentary lapses in focus can immediately create larger problems or lead you further away from the goal of your work.
AI seems so smart, what do you mean it doesn’t understand the real world?
Despite their impressive abilities to comprehend and respond to a wide range of queries and prompts, generative AI systems have no grasp of the realities they're writing about. Don't be fooled by skillful references to relatively current events or insightful analyses of complex issues — these are all the result of complex mathematics behind the scenes.
Generative AI systems have processed unimaginably large data sets of text, from which they've discovered patterns of probabilities that connect words, phrases, concepts, and structures of the writing they've ingested. When you prompt one of these systems, it breaks your query down into numbers and probabilities and predicts each word that comes next.
At no time is the model checking with any validated sources of information to ensure it is pulling correct information for you. It's not pulling information at all; it's just predicting the next most likely word in a sequence.
At the same time, it is not trying to understand your query in the way another person tries to process the meaning of your words and what actions should follow. Generative AI models are simply turning your words into numbers and predicting which ones should come next.
What is an AI ‘hallucination’? Why does generative AI hallucinate?
AI hallucination refers to when a generative AI system produces outputs that are illogical, nonsensical, or even offensive due to the limitations of the software. Real-life examples may include entirely fictional people, places, events, and source materials.
When producing these hallucinations, the AI will sound every bit as confident as when the information is factual and correct. It is incredibly important that human users remain vigilant for such hallucinations when relying on AI-generated content in their work.
💡 Grantable is far less likely to hallucinate because the AI model is limited to using an organization's existing writing samples as source material to guide its writing.
A hallucination is not a malfunction; the AI system is performing exactly as it has been programmed to do. It has simply made a text prediction that we experience as being nonsensical or false. To the AI model, the text it has generated comes from a correct calculation of the probability that this sequence of words is an appropriate continuation of the human user's input query.
A view of the future of AI and philanthropic work
On November 30, 2022, OpenAI released ChatGPT, a research prototype aimed at studying user engagement with its large language models (LLMs). Within five days, ChatGPT attracted over one million users (15X faster than Instagram) and surpassed 100 million users in two months. The chatbot was able to generate remarkable responses to complex textual input, leaving the world captivated, amazed, and unnerved.
Computing advances, investments, competition between tech giants, and global awareness of LLMs are driving the fastest technological revolution in human history. Bill Gates, co-founder of Microsoft, compared this moment to the introduction of the graphical user interface, which made computing accessible to everyone. Sundar Pichai, the CEO of Google parent company Alphabet, has called this technology "more profound than fire or electricity."
LLMs can approximate the work of highly skilled knowledge workers and creatives in a matter of seconds and at a cost approaching zero. They are becoming more capable by the hour, and the quality of their outputs is improving just as quickly.
It is impossible to fully imagine how these systems will transform the world, and predictions range from armageddon to utopia. In a 2021 essay titled, "Moore's Law for Everything," OpenAI's CEO, Sam Altman, envisions a positive post-AI future, writing "As AI produces most of the world's basic goods and services, people will be freed up to spend more time with people they care about, care for people, appreciate art and nature, or work toward social good."
While we can't clearly envision many specifics about this new era in technology, we can reasonably assume that change will come more quickly than in the past. This is because the world is increasingly digitally connected, the speed of innovation is accelerating, as more people, resources, and prior breakthroughs compound, and AI dominance is becoming a major economic and geopolitical goal for man.
Artificial intelligence, like the systems we've been studying in this course, and even more powerful systems with artificial general intelligence (AGI), which can exceed human intelligence and capabilities, are being developed. Such technology creates the possibility of reaching unimaginably positive and/or terrifyingly dire outcomes depending on how humanity builds and regulates the use of these systems.
The nonprofit sector, or as I like to call it, the purpose-driven sector, must play a leading role in helping to embed human, planet, and justice-centered values in the technology itself and infusing policymaking with the wisdom of the sector that has long sought to remedy the brokenness of existing socioeconomic systems.
In day-to-day work, nonprofit sector professionals should stay engaged with AI tools and discussions both to further the mission at hand and to be fluent in conversations about creating responsible and ethical norms and governance for AI.
This short quiz is only meant to help you check your understanding of these materials. Your score is not recorded, so please write it down if you want to keep track for your own records.