AI in IDD
Here is a little bout how I am using AI in IDD. Our licensed Co-Pilot, has proven to be incredibly productive and time-saving, especially in reviewing documents for errors against regulations, identifying discrepancies between various care plans for the same individual, analyzing and summarizing documents for relevant information in investigations (reducing the closure time from 90 days to 7), suggesting corrective actions for internal/external audits, trending data sets (such as surveys, assessments, and audits), and proposing opportunities and solutions in light of the regulations. AI can audit documents, policies, and procedures with extreme accuracy against 6400 and 6100 regulations (PA regs). We have recently implemented this solution to streamline and audit our Medicaid billing process prior to submission. It enables us to identify billing errors, uncover unbilled days we should be billing for, and flag days we should not be billing - significantly reducing the time required for this process from 30 hours to 4 for a months' worth of billing. For systems that are not directly compatible with AI integration, we leverage AI to develop macros that process raw data exports. This allows us to extract precisely the information we need in seconds, rather than spending hours on manual analysis.Understanding the Fundamentals of AI Concepts for Nonprofits
Artificial Intelligence (AI) has become a cornerstone of modern technology, driving innovation across various sectors. Nonprofits, too, can harness the power of AI to enhance their operations and amplify their impact. In this blog, we'll explore fundamental AI concepts, common AI workloads, Microsoft's Responsible AI policies, and the tools and services available through Azure AI, all tailored for the nonprofit sector. Understanding AI Workloads AI workloads refer to the different types of tasks that AI systems can perform. Here are some common AI workloads relevant to nonprofits: Machine Learning: This involves training a computer model to make predictions and draw conclusions from data. Nonprofits can use machine learning to predict donor behavior, optimize fundraising strategies, and analyze program outcomes. Computer Vision: This capability allows software to interpret the world visually through cameras, video, and images. Applications include identifying and tracking wildlife for conservation efforts or analyzing images to assess disaster damage. Natural Language Processing (NLP): NLP enables computers to understand and respond to human language. Nonprofits can use NLP for sentiment analysis of social media posts, language translation for multilingual communities, and developing conversational AI like chatbots for donor engagement. Anomaly Detection: This involves automatically detecting errors or unusual activity. It is useful for fraud detection in financial transactions, monitoring network security, and ensuring data integrity. Conversational AI: This refers to the capability of a software agent to engage in conversations with humans. Examples include chatbots and virtual assistants that can answer questions, provide recommendations, and perform tasks, enhancing donor and beneficiary interactions. Responsible AI Practices As AI technology continues to evolve, it is crucial to ensure it is developed and used responsibly. Microsoft's Responsible AI policies emphasize the importance of fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability in AI systems. These principles guide the development and deployment of AI solutions to ensure they benefit everyone and do not cause harm. To learn more about Microsoft Responsible AI Practices click here: Empowering responsible AI practices | Microsoft AI Azure AI Services for Nonprofits Microsoft Azure offers a suite of AI services that enable nonprofits to build intelligent applications. Some key services include: Azure Machine Learning: A comprehensive platform for building, training, and deploying machine learning models. It supports a wide range of machine learning frameworks and tools, helping nonprofits analyze data and make informed decisions. To learn more or get started with Azure Machine Learning click here: Azure Machine Learning - ML as a Service | Microsoft Azure Azure AI Bot Service: A service for building conversational AI applications. It provides tools for creating, testing, and deploying chatbots that can interact with users through various channels, improving donor engagement and support services. To learn more or get started with Azure AI Bot Service click here: Azure AI Bot Service | Microsoft Azure Azure Cognitive Services: A collection of APIs that enable developers to add AI capabilities to their applications. These services include vision, speech, language, and decision-making APIs, which can be used for tasks like image recognition, language translation, and sentiment analysis. To learn more about the various Cognitive Service please click here: Azure AI Services – Using AI for Intelligent Apps | Microsoft Azure Conclusion AI has the potential to transform the nonprofit sector by enhancing efficiency, driving innovation, and providing valuable insights. By understanding AI workloads, adhering to responsible AI practices, and leveraging Azure AI services, nonprofits can unlock the full potential of AI to better serve their communities and achieve their missions. Embrace the power of AI to take your nonprofit organization to new heights and make a greater impact. For a deeper dive into the fundamental concepts of AI, please visit the module Fundamental AI Concepts. This resource will provide you with essential insights and a solid foundation to enhance your knowledge in the ever-evolving field of artificial intelligence.
Discontinuation of M365 Business Premium Grant Deeply Disappointing,Harmful to Small Nonprofits
As a Microsoft CSP partner supporting multiple nonprofit organizations, I am extremely disappointed by the decision to discontinue the Microsoft 365 Business Premium grant. This change disproportionately affects small nonprofits that rely on these tools to fulfill their missions with limited resources. The justification that this is about “alignment” or “sustainability” is disingenuous. Let’s be honest—this is a revenue-driven decision that undermines Microsoft’s long-standing commitment to empowering nonprofits. Removing access to essential tools like Office desktop apps and Intune from the grant program forces small organizations into paid plans they cannot afford, jeopardizing their operations and security. Microsoft has built goodwill in the nonprofit sector over the years. This move erodes that trust. I urge you to reconsider this decision or at least provide a longer transition period and more flexible options for small nonprofits. Please do better. The nonprofit sector deserves more than a corporate cost-cutting maneuver disguised as a strategic realignment.Let's Connect - Share Your LinkedIn Profile
Hello all and welcome. Someone suggested on the kick-off webinar that it would be great to have a place for folks to share their LinkedIn profiles if they were willing to do so. I suggested starting a thread on here. 😀 I suggest just adding a comment below to add yours and I'll share a link to this thread in the follow up email (if you're here you likely already received the email. 😁). I'll start - here is my profile link: https://www.linkedin.com/in/petraeimiller/Harmonizing Creativity: AI-Powered Music Making with Copilot and Suno
In the ever-evolving world of music production, technology has opened doors that once seemed closed. The future is now, and it’s powered by AI tools that make the songwriting and melody-making process more accessible, innovative, and, let’s be honest, a whole lot of fun! Two such groundbreaking tools—Copilot and Suno AI—are revolutionizing the way we create music. Whether you’re a seasoned musician or just dipping your toes into songwriting, these tools are about to change the game for you. The Power of AI in Songwriting Songwriting can sometimes feel like a battle with your own brain—chasing after that perfect phrase, that killer melody, only to find yourself stuck in a loop of frustration. Here’s where AI steps in. Copilot and Suno AI aren’t just about automating tasks—they are about enhancing your creativity, helping you tap into new sources of inspiration, and pushing your music to places you might never have gone on your own. Copilot: The Lyric Writing Partner You’ve Been Waiting For Copilot is a tool that acts like an extension of your creative mind. Think of it like a songwriting buddy who never runs out of ideas, can offer fresh perspectives, and isn’t afraid to suggest bold ideas. Whether you're stuck on the first line of a song or looking for a catchy chorus, Copilot can help. Here’s how it works: Brainstorming Ideas: If you're looking to write lyrics about a specific theme or emotion, just input a few keywords, and Copilot will help generate lyrical suggestions. It’s like having a starting point when you’re feeling creatively dry. Building Structure: Sometimes, knowing how to start is half the battle. Copilot can suggest various song structures, from verses to choruses, bridges to intros. Need a fresh perspective on how to build your song? Copilot has you covered. Wordplay and Rhymes: For the wordsmiths out there, Copilot’s ability to play with words and rhyme schemes is an invaluable tool. You can experiment with different lyrics and find the perfect word combinations you wouldn’t have thought of yourself. The magic of Copilot isn’t that it just writes lyrics for you—it pushes you in new directions, offering suggestions that fuel your own creativity, letting you fine-tune and shape your ideas in real-time. Suno AI (Third-Party Tool): The Melody Maker While Copilot handles your lyrics, Suno AI is your musical partner, capable of crafting melodies that align with your lyrics, setting the perfect mood for your song. Suno specializes in melody generation, so if you're stuck at the piano or guitar, unsure how to bring your lyrics to life, Suno can suggest harmonic progressions and melodic lines that enhance the emotional weight of your song. Imagine trying to write a soulful ballad but feeling disconnected from the right melody. With Suno AI, you input your lyrics and the emotional tone you want to convey, and it generates musical ideas that match that vibe. Whether you're aiming for a catchy pop hook, a somber indie tune, or something experimental, Suno adapts to your needs. Suno AI also allows for customization. You can refine the generated melody, adjusting it to fit the mood you’re trying to create. The beauty of Suno lies in how it bridges the gap between theoretical music knowledge and practical creation, offering melody ideas that might take a human composer hours to create. How Copilot and Suno Work Together: The Dream Team Now, imagine combining Copilot and Suno AI in one seamless workflow. You start by crafting your lyrics with Copilot, brainstorming themes or digging into emotional topics. Once you have the lyrics, you turn to Suno AI, inputting the mood and vibe you want for the melody. Here’s an example: You’ve written lyrics about love, inspired by a joyful moment you shared with someone special. Copilot has helped you perfect the words, but something’s still missing. You need a melody that captures the excitement and warmth in your lyrics. You turn to Suno, telling it you want an upbeat, cheerful melody. In an instant, Suno creates a bright, lively piano progression that fills your lyrics with energy and joy, bringing the words to life with an infectious sense of happiness. The result? A fully formed song that feels both emotionally authentic and musically cohesive, all thanks to the synergy between AI tools. How to Get Started: To start with the lyrics: Go to copilot.microsoft.com Choose the experience you are looking for: Work or Personal. Type in your prompt. For example, “Write me a rap song about using M365. Adding a melody to the song: After you have generated and are happy with the lyrics, go to www.suno.com. Sign in if you have an existing account or create a free account by clicking on either "Create" or "Library" on the left-hand tab. 3. Once in Suno, toggle the "Custom" button and add your lyrics from Copilot in the "Write with Suno" box. Next, select your style of music, from pianist to female vocalist to country—they've got it all. Give your song a title and click “Create.” Suno will create two versions of your song in your song's library. 7. Example songs I created about M365: https://suno.com/song/853d0113-b36f-407a-b533-18b8ab27d681?sh=yn9LWYlho00RILtt https://suno.com/song/c4584819-ae68-4812-860b-897eb2d0367d?sh=Ewzn7SJ03VCYnuSm So, there you have it! With Copilot and Suno AI by your side, the world of music creation is at your fingertips. Whether you're crafting heartfelt lyrics or composing captivating melodies, these AI tools are here to elevate your creativity and make the process a breeze. So, grab your mic, fire up your laptop, and let Copilot and Suno AI help you create your next hit. Happy songwriting! For additional tips and resources, be sure to follow our Nonprofit Community | Microsoft Community Hub for blogs, updates, and expert advice on maximizing your nonprofit tools.We Want to Hear From You!
As we build this community together, we’d love to hear from you—what topics are you most interested in exploring? Are there specific challenges, technologies, or ideas you'd like us to focus on in future sessions or roundtable discussions? Let us know what you’d like to see and who you’d like to hear from, and we’ll work to bring in the right voices and insights.Welcome to the AI Consortium!
The AI Consortium for Healthcare-Focused Non-Profits brings together like-minded non-profit organizations to drive responsible AI and collaborate on addressing shared challenges through the power of artificial intelligence (AI). This initiative fosters a community of learning, innovation, and action, enabling healthcare-focused non-profits to overcome barriers and unlock the potential of AI to achieve greater mission impact. The consortium aims to: Build a Thriving Community: Create a connected ecosystem of healthcare-focused non-profits for ongoing engagement, knowledge sharing, and resource collaboration. Tackle Shared Challenges: Address common obstacles such as AI governance, data integration, resource constraints, and operational inefficiencies through collaborative learning and shared solutions. Empower Non-Profits with AI Knowledge: Provide education, training, and practical tools to help organizations evaluate and implement AI effectively and ethically. Drive Mission-Driven Outcomes: Leverage AI to improve healthcare delivery, enhance operational efficiency, and promote equity in underserved communities. Deliver Measurable Impact: Support participating organizations in achieving tangible results through scalable AI solutions tailored to their unique challenges.Scaling AI: Strategies for Transforming Your Nonprofit
Scaling AI in a nonprofit context involves integrating AI technologies across various functions to maximize benefits such as improved decision-making, increased productivity, and enhanced service delivery. This can help nonprofits better serve their communities and achieve their missions more effectively. Key Strategies for Scaling AI in Nonprofits 1. Develop a Clear AI Strategy: Align the AI strategy with the nonprofit's mission and goals. Identify specific AI use cases that can drive value, such as automating administrative tasks, improving donor management, or enhancing service delivery. Create a roadmap for implementation, detailing resources, timelines, and milestones. Microsoft Tools that can help: Azure AI: Helps in developing and implementing AI strategies aligned with organizational goals. Power BI: Assists in identifying and visualizing AI use cases and creating implementation roadmaps. 2. Invest in AI Infrastructure: Utilize scalable cloud platforms like Azure to support data processing, storage, and analysis. Leverage tools like Azure Machine Learning to develop and deploy AI models efficiently. Microsoft Tools that can help: Azure: Provides scalable cloud infrastructure for data processing and storage. Azure Machine Learning: Facilitates the development and deployment of AI models. 3. Foster a Data-Driven Culture: Promote data literacy within the organization and encourage staff to use data in decision-making processes. Provide training and resources on AI and data analytics to build a data-driven culture. Microsoft Tools that can help: Microsoft Learn: Offers training resources on AI and data analytics. Power BI: Enhances data literacy by providing tools for data visualization and analysis. 4. Leverage Pre-Built AI Solutions: Use pre-built AI solutions and services to accelerate the scaling process. For example, Azure Cognitive Services offers APIs for vision, speech, language, and decision-making that can be integrated into nonprofit applications without building models from scratch. Microsoft Tool that can help: Azure AI Services: Provides pre-built AI solutions for vision, speech, language, and decision-making. 5. Implement Governance and Ethical Guidelines: Establish governance and ethical guidelines to ensure responsible and transparent use of AI. Address concerns related to bias, privacy, and accountability by following frameworks like Microsoft's Responsible AI principles. Microsoft Tool that can help: Microsoft Responsible AI: Offers frameworks and guidelines for ethical AI use. Real-World Examples of Scaling AI in Nonprofits: Disaster Response: AI can improve efficiency in disaster response by automating data collection and analysis, enabling faster and more accurate decision-making. Education: Nonprofits focused on education can use AI to provide personalized support to students, such as automating responses to common inquiries and offering tailored learning resources. Fundraising: AI can enhance fundraising efforts by analyzing donor data to identify potential major donors and optimize fundraising campaigns. Conclusion Scaling AI in a nonprofit organization requires a strategic approach, robust infrastructure, and a data-driven culture. By developing a clear AI strategy, investing in the right tools and technologies, and fostering an environment that embraces data and AI, nonprofits can unlock the full potential of AI and drive significant impact. Embrace the power of AI to take your nonprofit organization to new heights and better serve your community. For more detailed information and a comprehensive guide on scaling AI in your organization, you can explore the Scale AI in your organization module on Microsoft Learn.Empowering Nonprofits with Azure AI Vision: Enhancing Operations and Achieving Missions
Azure AI Vision is a powerful tool that enables organizations to analyze images and extract meaningful descriptions. Nonprofits can leverage AI Vision in various impactful ways to enhance their operations and achieve their missions more effectively. Here are some practical applications: Smart Stores Nonprofits operating retail stores can implement "smart store" solutions using AI Vision. By analyzing images from store cameras, they can identify customers needing assistance and direct employees to help them, improving customer service and operational efficiency. Event Management AI Vision can analyze images and videos from events to monitor attendance, track engagement, and gather insights on participant behavior. This data can help nonprofits improve future events and tailor their programs to better meet the needs of their audience. Security and Safety AI Vision can be used for security purposes, such as monitoring premises, detecting unauthorized access, and ensuring the safety of staff and beneficiaries. This technology can also identify potential hazards and prevent accidents. Now that we understand what Azure AI Vision is and some practical use cases, let's analyze a few images. Creating a Project in Azure AI Foundry Portal Pre-req: You will need to have an Azure account Navigate to Azure AI Foundry: Open a browser tab and go to the Azure AI Foundry portal. Sign In: Use your account credentials to sign in. 3. Create a Project: On the home page, select "Create a project." Projects in Azure AI Foundry help organize your work. 4. Configure Project and Hub: You will see a generated project name. Depending on your previous hub creations, you will either see new Azure resources to be created or a drop-down list of existing hubs. Select "Create new hub," name your hub, and proceed. 5. Customize Location: Select a location for your Azure AI services resource (East US, France Central, Korea Central, West Europe, or West US) and create the project. Resources Created Take note of the resources that are created: Azure AI services Azure AI hub Azure AI project Storage account Key vault Resource group After the resources are created, you will be brought to your project’s Overview page. Using AI Services Access AI Services: On your project's Overview page, select "AI Services" from the left-hand menu. Select Vision + Document: On the AI Services page, choose the Vision + Document tile to explore Azure AI Vision capabilities. Generating Captions for Images Image Captioning: On the Vision + Document page, select "Image" under "View all other vision capabilities," then choose the Image captioning tile. Upload Image: Upload an image by dragging it to the Drag and drop files here box, or by browsing to it on your file system. For demo purposes I used a provided sample file. Observe Captions: The Caption functionality generates a single, human-readable sentence describing the image's content. Dense Captioning Dense Captions: Return to the Vision + Document page, select the Image tab, and choose the Dense captioning tile. Upload Image: Upload an image by dragging it to the Drag and drop files here box, or by browsing to it on your file system. For demo purposes I used a provided sample file. Multiple Captions: Dense Captions provide multiple human-readable captions for an image, each describing essential objects detected in the picture. Tagging Images Extract Tags: On the Vision + Document page, select the Image tab and choose the Common tag extraction tile. Upload Image: Upload an image by dragging it to the Drag and drop files here box, or by browsing to it on your file system. For demo purposes I used a provided sample file. Review Tags: Extracted tags include objects and actions, with confidence scores indicating the likelihood of accurate descriptions. Conclusion Azure AI Vision is a transformative tool that nonprofits can leverage to enhance their operations and achieve their missions more effectively. By implementing smart store solutions, nonprofits can improve customer service and operational efficiency. Event management can be optimized by analyzing images and videos to monitor attendance and track engagement. Security and safety measures can be strengthened by using AI Vision to monitor premises and detect potential hazards. As we have explored the practical applications of Azure AI Vision, it's clear that this technology offers significant benefits for nonprofits. By integrating AI Vision into their operations, nonprofits can make data-driven decisions, improve their services, and ultimately better serve their communities. To learn more about Computer Vision and analyzing images, please visit: Fundamentals of Computer Vision - Training | Microsoft Learn.Empower Your Nonprofit with Azure AI: Building a Smart Knowledge Base
In today's digital age, providing quick and accurate answers to customer queries is essential for any business. Azure AI Language Studio offers powerful question answering capabilities that enable organizations to create and train a knowledge base of questions and answers. Creating a knowledge base with Azure AI Language Studio can be incredibly beneficial for a nonprofit organization. Here are some compelling reasons why you might want to consider it: Enhancing Customer Support: A knowledge base allows you to provide quick and accurate answers to common questions from your supporters, volunteers, and beneficiaries. This can significantly improve customer support by reducing response times and ensuring that inquiries are handled efficiently. Streamlining Operations: By automating the process of answering frequently asked questions, you can free up your staff to focus on more strategic tasks. This can lead to increased productivity and better use of resources, which is crucial for nonprofits operating with limited budgets. Improving Accessibility: A well-structured knowledge base can make information more accessible to everyone, including individuals with disabilities. Azure AI Language Studio's natural language processing capabilities ensure that users can find the information they need easily, regardless of how they phrase their questions. Enhancing Engagement: Providing timely and accurate information can enhance engagement with your supporters and beneficiaries. When people feel that their questions are answered promptly, they are more likely to stay involved and support your cause. Data-Driven Insights: Azure AI Language Studio can provide valuable insights into the types of questions being asked and the information that is most sought after. This data can help you understand the needs and concerns of your community better and tailor your programs and services accordingly. Cost-Effective Solution: Creating a knowledge base with Azure AI Language Studio is a cost-effective solution for managing inquiries. It reduces the need for extensive human intervention and can be scaled easily as your organization grows. Now that we understand the importance, let's build our first knowledge base! Creating a Language Resource To get started, you need to create a Language resource in the Azure portal: Open the Azure portal at https://portal.azure.com/?azure-portal=true and sign in with your Microsoft account. Click the "Create a resource." Search for "Language service." Select "Create a language service plan" and configure the following settings: Default features: Keep the default features. Custom features: Select custom question answering. On the Create Language page, specify the following settings: Subscription: Your Azure subscription. Resource group: Select an existing resource group or create a new one. Region: Select a region (e.g., East US 2). Name: A unique name for your language resource. Pricing tier: Select a pricing tier. Azure search region: Any available location. Azure search pricing tier: Select your Azure search pricing tier. 6. Review and create the resource and wait for the deployment to complete. Creating a New Project Next, you'll create a new project in Language Studio: Open the Language Studio portal at Language Studio - Microsoft Azure and sign in with your Microsoft account. If prompted, select your Azure directory, subscription, and Language resource. In the Create new menu, select "Custom question answering." On the Choose language setting for resource page, select "I want to select the language when I create a project in this resource" and click Next. Enter the following details on the Enter basic information page: Language resource: Choose your Language resource. Azure search resource: Choose your Azure search resource. Name: Choose a name Description: A simple knowledge base Source language: English Default answer when no answer is returned: No answer found Review and create the project. Adding Content to the Knowledge Base Now, you'll add content to your knowledge base from your appropriate document. From demo purposes I will be added the Q&A from our public NTA Landing Page. On the Manage sources page, select "Add source" and choose "URLs." In the Add URLs box, enter the following details: URL name: Enter URL name, for demo purposes I used NTA. URL: Enter URL, for demo purposes I use the NTA Landing Page Classify file structure: Auto-detect Select "Add all" to add the URL to your knowledge base. Editing the Knowledge Base You can customize your knowledge base by adding custom question-and-answer pairs: Expand the left panel and select "Edit knowledge base." Select "+" to add a new question pair. In the Add a new question answer pair dialog box, enter your question as the answer, then select "Done." Save your knowledge base. Training and Testing the Knowledge Base Once your knowledge base is set up, you can train and test it: Select "Test" at the top of the Question answer pairs pane. In the test pane, enter one of your questions to see the response. Try other questions as well. Deploying the Knowledge Base Finally, you can deploy your knowledge base as a client application: In the left panel, select "Deploy knowledge base." Select "Deploy" at the top of the page and confirm the deployment. 3. Next step will be creating your bot. https://aka.ms/qna-create-bot By following these steps, you can create a robust knowledge base using Azure AI Language Studio, providing quick and accurate answers to your customers' questions. This not only enhances customer satisfaction but also streamlines your support processes. To learn more about language services, please visit: Fundamentals of question answering with the Language Service - Training | Microsoft Learn
