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By Sajit Joseph
Approximately 32 million acres of natural forest — an area nearly equal to the size of Florida — is lost to deforestation each year. Illegal logging accounts for much of this loss. Protecting the world’s forests is essential to slowing climate change and decreasing the risk of zoonotic diseases spreading to humans. Illegal deforestation is a complex and difficult problem to solve.
Leaders at the Rainforest Connection, a nonprofit in Katy, Texas, decided to develop a creative solution harnessing the power of sound and artificial intelligence (AI) to address this problem. They use small recorders powered by solar panels that continuously record the forest’s soundscape and transmit the audio to the cloud. They built an AI model in the cloud that analyzes the sound, goes beyond detecting logging in progress to predicting illegal logging before it can commence, and sends real-time alerts to a local agent on the ground.
They can predict with a 96% accuracy up to five days in advance where illegal loggers will strike. This is a game-changer. It’s predicted by experts that a solution like this can help reduce illegal logging by 35% worldwide.
There are many other high-impact uses of AI for social good. The Nature Conservancy has used cameras and AI for invasive species prevention. The American Red Cross has been using AI and satellite imagery to provide overall assessments of damage to infrastructure after a disaster. The IFAD (International Fund for Agricultural Development) uses AI, to get better insights, and improve the targeting of the vulnerable communities they serve.
The AI industry is evolving at a pace that is faster than all technology developments of the past. Nonprofits have a huge opportunity to use AI responsibly to maximize impact and fundraising.
The use of AI in the nonprofit sector is very limited right now. Google for Nonprofits surveyed 4,600 nonprofit staffers to identify the use of Generative AI (one of the AI technologies). The responses showed that four in five nonprofits managers think generative AI might apply to their work, but two-thirds of them thought a lack of familiarity with generative AI was their biggest barrier to adoption. The survey data also showed that individuals use Generative AI for some of their tasks but not broadly across the organization.
The path to AI implementation might be easier for large nonprofits. The path is not as challenging as it might appear for smaller nonprofits. There are two ways an organization’s staff can leverage the power of AI.
- Use software-as-a-service (SaaS) AI-powered solutions that can optimize specific functions.
- Build custom AI solutions like the examples listed above to maximize impact
Using Software-as-a-Service AI
The market is now full of AI-powered solutions that help with discrete needs. Nonprofit managers can start the organizational journey by using these products for internal or external needs. AI-powered software can be leveraged as a service solution to enhance operations without needing extensive technical expertise or large budgets. Here are a few ideas.
* Tools such as HubSpot and Salesforce offer AI-powered constituent relationship management (CRM) solutions that can help manage donor relationships, automate fundraising campaigns, and personalize communications, thus increasing donor engagement and retention.
* AI-driven platforms such as Jasper AI, Write Sonic, and Surfer SEO can assist in content creation and supporting marketing needs, to create high-impact communications for all channels with minimal effort.
* Solutions such as Notion, Otter, Coda, and Taskade provide productivity-enhancing tools that can help improve efficiency across multiple areas, thereby reducing mundane and manual tasks.
* AI-powered solutions like Slack and Microsoft Teams can help improve collaboration and engagement.
* AI-infused project management tools like Asana and Trello can help execute initiatives.
* For creative material creation, tools like Canva and Adobe Firefly can be used for design assets, and tools like Runway, and Pictory AI can be used for video asset creation.
* Generative AI platforms such as ChatGPT, Microsoft CoPilot, Google Gemini, Meta AI, and Claude from Anthropic offer chat interfaces to sophisticated large language models that could serve as a personal AI assistant and help employees perform their day-to-day functions.
By using these accessible and user-friendly AI tools, staff members at smaller nonprofits can streamline operations, maximize their resources, and amplify their impact in serving their communities. Remember that ample training and change management would be needed while rolling out these solutions so that employees who are not tech-savvy can use these tools to their maximum potential.
Building Custom AI To Maximize Impact
This is when the organization’s staff tries to leverage the true potential of AI and uses this technology to transform mission delivery and maximize its impact. Solutions would be similar to the examples listed above. They might require custom AI solutions or building an ecosystem that integrates AI products into the nonprofit context using customizations. The potential impact of these solutions could be quite significant.
There are many technologies in the AI landscape. Generative AI, machine learning, and deep learning are probably the three AI technologies that might impact nonprofits the most. It will be helpful for nonprofit leaders to have a non-technical understanding of these technologies and examples of potential outcomes using them.
- Creative Problem Definition: The process starts with problem definition. Identifying the right use case enables staff members to uncover the most impactful and innovative AI applications. By thinking creatively about the problems that they face, staff members can move beyond conventional approaches and identify unique opportunities where AI can provide significant value.
It’s important to step back and be unshackled by the current ways of delivering the mission. In many cases, AI allows redefining how a function could work in the future. The importance of this step as the potential of impact is directly proportional to the creativity in rethinking existing functions can’t be stressed enough.
After dreaming big and applying creative problem definition, the staff members might come up with a list of potential use cases. Some use cases might be smaller and easier to solve, and some might be complex. This is where starting small and experimentation becomes critical.
- Experimentation: Building a culture of experimentation is a critical skill, even if it’s not focused on AI use cases. This mindset enables staff members to validate concepts by building proof of concepts which will take a fraction of the effort of the full end-to-end solution.
This iterative process helps in identifying the most effective AI solutions, optimizing performance, and refining algorithms based on empirical data. By experimenting with different approaches, insights can be uncovered about data, also understanding the nuances of AI applications and mitigating risks associated with implementation. Experimentation fosters a culture of innovation, enabling organizations to adapt to changing conditions and continually improve their AI capabilities?. Now that a proof of concept has been identified, it’s time to onboard technology resources.
- Onboarding Technical Resources: Smaller nonprofits might not be able to hire data scientists, generative AI engineers, or AI consultants, making the path to building AI solutions difficult. However, other avenues are uniquely available:
- Volunteers: Managers could either use the existing volunteer program or start a new one to onboard AI technology volunteers. These volunteers could use their skills in the AI space to help solve the defined use case.
- College Students: College programs offer many avenues for onboarding students to help with AI solutions. Managers could engage a group of students via capstone projects, onboard interns, or engage a college career-focused club that likes to take on real-world projects.
- Tech Firms: Some tech firms are willing and keen to help nonprofits solve problems by devoting some time from their staff on a pro bono basis. The nonprofit can onboard such pro bono teams if they are convinced that the tech firm will not be biased in their recommendations or use this project to sell a product they own.
- Hackathons: These are often used at conferences and other avenues to gamify solution development. It’s a great forum to build a proof-of-concept solution and perhaps identify volunteers who can help complete the solution.
A clear definition of the scope of the proof of concept will help set expectations and align with the team. Most AI solutions require access to data, so please ensure that you have enough data available before onboarding technology resources for building an AI solution.
The above approaches will help start on the AI journey. However, before embarking, the managers should work on defining the responsible use of AI within the organization. Having a responsible AI policy can ensure that the power of AI is harnessed in a way that is ethical, transparent, and aligned with its mission.
Responsible AI & Policy: Larger organizations might start with a comprehensive policy, but most organizations start with leaders defining the boundaries of what is acceptable use and how it will be governed.
The policy should include various dimensions, encompassing ethical and responsible use of technology within the organization, adherence to regulatory mandates, safeguarding data privacy and security, and effective risk management. Establishing such a policy also facilitates employee education and awareness initiatives, enlightening them on ethical considerations, guidelines, and optimal practices linked with AI, thereby minimizing the chances of unintended misuse.
The specifics of the policy hinge significantly on risk appetite, regulatory requirements, and prevailing culture. An organization where leaders are inclined toward caution might adopt a conservative approach to AI deployment, unlike one with a greater risk appetite or a culture inclined towards innovation. The policy might also distinguish between permitting more experimentation in certain business domains while being more risk-averse in other areas.
In essence, the policy serves as a mechanism to mitigate risks, ensure regulatory compliance, and foster the ethical and transparent integration of AI technologies into the organization’s functions.
Other Considerations
As an organization matures in its AI journey, change management, and human factor engineering should be considered in the development and implementation of AI solutions.
When it comes to change management, a solution is successful when it’s used regularly and delivers the desired outcomes. Managing change is essential to achieve this goal. Due to potential skepticism toward their outcomes, change management efforts are especially crucial for AI solutions.
Introducing AI solutions requires procedures and adjustments to job responsibilities, which might encounter resistance if not handled effectively. Successful change management tackles these challenges by offering employees transparent communication, training, and assistance, empowering them to comprehend and adopt the new solution.
Human-factored engineering is essential in building AI solutions because it ensures that these technologies are designed with the end-user in mind, promoting usability, accessibility, and ethical considerations. For example, while building workforce-focused AI solutions, one best practice is to think of AI solutions as a decision-making augmentation tool. The user can choose to override the recommendation, accept the recommendation, or adjust the recommendation based on situational context.
Involving human perspectives in the development process helps align AI solutions with real-world needs and ethical standards, fostering trust and acceptance among users.
In conclusion, nonprofits can significantly benefit from leveraging AI to enhance operational efficiency and amplify impact. As AI technology continues to evolve, it offers immense potential for nonprofits to achieve greater effectiveness and sustainability in serving their communities. Embracing these technologies can help level the playing field, allowing smaller organizations to drive meaningful change and maximize their social impact.
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Sajit Joseph is an award-winning technology and operations executive, currently the chief digital and transformation officer at Tides Network in San Francisco, California.
