Nonprofit Innovator Podcast

This week we’ve got a special episode, the first of a three-part series on Feeding America and their new hunger awareness campaign, called the Face of Hunger. The campaign uses artificial intelligence in a couple of unique ways to help, literally, generate and animate the face of hunger in America. It’s pretty clever stuff and I think you’ll find it really interesting. To get things started, this week we talk with Catherine Davis, who has dual roles at Feeding America, she is the Chief Marketing and Cheif Communications Officer at the national organization, based in Chicago. We talk with Catherine about the origins of the campaign - why this and why now? - and dig into the essentials about this big PSA initiative. Catherine also talks about how AI is being used at the organization - both from a programs and service perspective and in the marketing function. With a ton of experience on the agency side and working within some pretty high profile companies in marketing roles, Catherine brings a well-rounded and highly informed perspective to the discussion about nonprofits, marketing, and AI.  Over the next several weeks, we will present Part 2 and Part 3 of this mini-series about Feeding America’s campaign. Next week we talk with Leo Burnett, the advertising agency that partnered with Feeding America to develop the concept and campaign. We’ll hear from the executive lead at the agency and his lead creative person - who provide a lot more detail about the role of AI in advertising these days, and the low-down on this campaign. In a couple of weeks, we talk with the Mill, the visual special effects and creative content studio that worked with Leo Burnett to craft the dynamic, AI-powered face of hunger for the campaign. It’s a fascinating look at how the clever images used in the Feeding America campaign were developed. So with that, sit back and enjoy this week’s episode, and don’t forget to subscribe to the podcast so you get the follow-on episodes in this mini-series delivered automatically to your phone.

This week we’re talking about Behavioral Economics in Individual Giving. It’s a term coined by AI fundraising company Arjuna Solutions that describes how the  AI models work that power their solution for gift array optimization. We get more into the definition, the product, and the real value and benefit for nonprofit individual giving programs in this episode. Our guests for this week's podcast including Michael Gorriarán, President at Arjuna Solutions, and Loree Lipsteen, Founder, Principal of Thread Strategies. Michael shares more details about the product while Loree - her fundraising agency works with small organization (<$5 million per year in annual budget) - walks us through the reasons the AI tool from Arjuna works so well for these smaller groups: the ease of implementation, pay-as-you-go pricing, and the rapid payback period.  So smaller nonprofits take note - we finally have a new, valuable technology that improves fundraising revenue and that is just as viable for small groups as large national organizations. As always, drop us a line if you have questions or comments - contact me at jeff.patrick@cohort3.com. Enjoy this week's episode. - Jeff Patrick, The Host of the Nonprofit Innovators in AI Podcast

This week we’re talking about Behavior Economics in Individual Giving. It’s a term coined by AI fundraising company Arjuna Solutions that describes how the  AI models work that power their solution for gift array optimization. We get more into the definition, the product, and the real value and benefit for nonprofit individual giving programs in this episode. Our guests for this week's podcast including Michael Gorriarán, President at Arjuna Solutions, and Loree Lipsteen, Founder, Principal of Thread Strategies. Michael shares more details about the product while Loree - her fundraising agency works with small organization (<$5 million per year in annual budget) - walks us through the reasons the AI tool from Arjuna works so well for these smaller groups: the ease of implementation, pay-as-you-go pricing, and the rapid payback period.  So smaller nonprofits take note - we finally have a new, valuable technology that improves fundraising revenue and that is just as viable for small groups as large national organizations. As always, drop us a line if you have questions or comments - contact me at jeff.patrick@cohort3.com. Enjoy this week's episode. - Jeff Patrick, The Host of the Nonprofit Innovators in AI Podcast

This week we’re talking about Behavioral Economics in Individual Giving. It’s a term coined by AI fundraising company Arjuna Solutions that describes how the  AI models work that power their solution for gift array optimization. We get more into the definition, the product, and the real value and benefit for nonprofit individual giving programs in this episode. Our guests for this week's podcast including Michael Gorriarán, President at Arjuna Solutions, and Loree Lipsteen, Founder, Principal of Thread Strategies. Michael shares more details about the product while Loree - her fundraising agency works with small organization (<$5 million per year in annual budget) - walks us through the reasons the AI tool from Arjuna works so well for these smaller groups: the ease of implementation, pay-as-you-go pricing, and the rapid payback period.  So smaller nonprofits take note - we finally have a new, valuable technology that improves fundraising revenue and that is just as viable for small groups as large national organizations. As always, drop us a line if you have questions or comments - contact me at jeff.patrick@cohort3.com. Enjoy this week's episode. - Jeff Patrick, The Host of the Nonprofit Innovators in AI Podcast

 In this week’s Nonprofit Innovators in AI podcast my podcast partner Taylor Shanklin joins me for a practical sidebar into the question - Is AI real or hype?  It turns out that plenty of people are making lots of noise about AI in the nonprofit sector. By noise, I mean pitching new products, announcing new applications, getting funding for all of that, and some nonprofits are standing up and saying … we did this with AI and it worked. Those various things are normal parts of the technology maturation process and generally, make one believe that there is a there there for AI and nonprofits. But, many of you - listeners - are making or at least are being asked to make strategic decisions about whether and what your organization should invest in when it comes to AI. And we get it, that can be a pretty tough question, particularly because AI is pretty complex and for many of us it hasn’t been around for very long. So there isn’t much in the way of common knowledge about it in and around the industry, case studies demonstrating that it works, and more generally, proof. Plain and simple, the question that we get most typically from our listeners is - does it really work? So, that’s the topic we cover in today’s episode. And we do that by answering four key questions about the technology - Where did AI technology come from? What types of problems is it good at solving? How do I know if it is working? And where is it going from here? With those answers, we hope that you’ll be better prepared when the inevitable questions surface in your organization about AI. Now you’ll be equipped to cut through the hype and find the best use of this technology for your group. Enjoy this week’s episode.

 In this week’s Nonprofit Innovators in AI podcast my podcast partner Taylor Shanklin joins me for a practical sidebar into the question - Is AI real or hype?  It turns out that plenty of people are making lots of noise about AI in the nonprofit sector. By noise, I mean pitching new products, announcing new applications, getting funding for all of that, and some nonprofits are standing up and saying … we did this with AI and it worked. Those various things are normal parts of the technology maturation process and generally, make one believe that there is a there there for AI and nonprofits. But, many of you - listeners - are making or at least are being asked to make strategic decisions about whether and what your organization should invest in when it comes to AI. And we get it, that can be a pretty tough question, particularly because AI is pretty complex and for many of us it hasn’t been around for very long. So there isn’t much in the way of common knowledge about it in and around the industry, case studies demonstrating that it works, and more generally, proof. Plain and simple, the question that we get most typically from our listeners is - does it really work? So, that’s the topic we cover in today’s episode. And we do that by answering four key questions about the technology - Where did AI technology come from? What types of problems is it good at solving? How do I know if it is working? And where is it going from here? With those answers, we hope that you’ll be better prepared when the inevitable questions surface in your organization about AI. Now you’ll be equipped to cut through the hype and find the best use of this technology for your group. Enjoy this week’s episode.

 In this week’s Nonprofit Innovators in AI podcast my podcast partner Taylor Shanklin joins me for a practical sidebar into the question - Is AI real or hype?  It turns out that plenty of people are making lots of noise about AI in the nonprofit sector. By noise, I mean pitching new products, announcing new applications, getting funding for all of that, and some nonprofits are standing up and saying … we did this with AI and it worked. Those various things are normal parts of the technology maturation process and generally, make one believe that there is a there there for AI and nonprofits. But, many of you - listeners - are making or at least are being asked to make strategic decisions about whether and what your organization should invest in when it comes to AI. And we get it, that can be a pretty tough question, particularly because AI is pretty complex and for many of us it hasn’t been around for very long. So there isn’t much in the way of common knowledge about it in and around the industry, case studies demonstrating that it works, and more generally, proof. Plain and simple, the question that we get most typically from our listeners is - does it really work? So, that’s the topic we cover in today’s episode. And we do that by answering four key questions about the technology - Where did AI technology come from? What types of problems is it good at solving? How do I know if it is working? And where is it going from here? With those answers, we hope that you’ll be better prepared when the inevitable questions surface in your organization about AI. Now you’ll be equipped to cut through the hype and find the best use of this technology for your group. Enjoy this week’s episode.

In this week’s episode, we have two segments that delve into deepfake technology. This special edition looks first at two pieces of news that surfaced last week about a scam using deepfake audio that resulted in a UK energy company mistakenly transferring $243,000 to bad guys before it realized that they’d been fooled by a deepfake bot that sounded like the CEO from its company. Confused? Don’t worry, we sort it all out and talk about the significance of this first of its kind deepfake crime in the business sector. Also in our first segment - the revelation of the week - the Chinese mobile app called Zao that uses deepfake video technology to place a user’s face on the face of celebrity actors from clips of famous movie scenes. The app immediately went viral even as Chinese citizens, the Chinese government, and western media cried foul. We look at the technology and the social, legal, and ethical ramifications of this new deepfake-powered app. In our second segment, I answer a listener question about deepfake technology - namely, why has deepfake technology gotten such a bad rap in the media? Isn’t it just another type of AI, after all? So, kick back and check out this week’s special edition of the Nonprofit Innovators in AI podcast where we take a deep dive on deepfake AI.

In this week’s episode, we have two segments that delve into deepfake technology. This special edition looks first at two pieces of news that surfaced last week about a scam using deepfake audio that resulted in a UK energy company mistakenly transferring $243,000 to bad guys before it realized that they’d been fooled by a deepfake bot that sounded like the CEO from its company. Confused? Don’t worry, we sort it all out and talk about the significance of this first of its kind deepfake crime in the business sector. Also in our first segment - the revelation of the week - the Chinese mobile app called Zao that uses deepfake video technology to place a user’s face on the face of celebrity actors from clips of famous movie scenes. The app immediately went viral even as Chinese citizens, the Chinese government, and western media cried foul. We look at the technology and the social, legal, and ethical ramifications of this new deepfake-powered app. In our second segment, I answer a listener question about deepfake technology - namely, why has deepfake technology gotten such a bad rap in the media? Isn’t it just another type of AI, after all? So, kick back and check out this week’s special edition of the Nonprofit Innovators in AI podcast where we take a deep dive on deepfake AI.

This week we take a virtual trip to Chicago where we have a chat with a company called Narrative Science. Their AI-powered software is pretty clever - it ingests data - think financial data or marketing/fundraising performance data - and it automatically generates stories about the data. In effect, it looks at the data and identifies useful trends, observations, or projections from the chart. It uses AI in the form of natural language generation to craft the text stories about what it sees in the data. The whole idea is that for most humans its easier to “get” what a chart is presenting if there is a simple explanation alongside it to point out the key insights. So a line graph showing how fundraising revenue is changing over time might have several stories that accompany it - where revenue started and ended in the period. The peak periods ex. End of year fundraising, and the predicated revenue for the next year which the software extrapolates from the data and graph. The key is that it makes the ~80% of data that is collected and unused, become actionable. Actionable here means the organization adapts its plan or strategy based on conclusions from the data they collect and analyze.  It’s pretty powerful stuff and definitely could be useful for nonprofit finance, fundraising,  marketing, and communications teams. And perhaps other departments. Narrative Science has created a Storytelling for Good program where they are providing their software, support, and training to nonprofits for free. So its a great opportunity to try on the software. So give this episode a listen. We provide more details on the product and its applications and share the details on how your nonprofit can get involved in  Storytelling for Good free program. As always, if you have feedback or questions, reach out to me directly at jeff.patrick@cohort3.com. With that, enjoy this week's episode.

This week we take a virtual trip to Chicago where we have a chat with a company called Narrative Science. Their AI-powered software is pretty clever - it ingests data - think financial data or marketing/fundraising performance data - and it automatically generates stories about the data. In effect, it looks at the data and identifies useful trends, observations, or projections from the chart. It uses AI in the form of natural language generation to craft the text stories about what it sees in the data. The whole idea is that for most humans its easier to “get” what a chart is presenting if there is a simple explanation alongside it to point out the key insights. So a line graph showing how fundraising revenue is changing over time might have several stories that accompany it - where revenue started and ended in the period. The peak periods ex. End of year fundraising, and the predicated revenue for the next year which the software extrapolates from the data and graph. The key is that it makes the ~80% of data that is collected and unused, become actionable. Actionable here means the organization adapts its plan or strategy based on conclusions from the data they collect and analyze.  It’s pretty powerful stuff and definitely could be useful for nonprofit finance, fundraising,  marketing, and communications teams. And perhaps other departments. Narrative Science has created a Storytelling for Good program where they are providing their software, support, and training to nonprofits for free. So its a great opportunity to try on the software. So give this episode a listen. We provide more details on the product and its applications and share the details on how your nonprofit can get involved in  Storytelling for Good free program. As always, if you have feedback or questions, reach out to me directly at jeff.patrick@cohort3.com. With that, enjoy this week's episode.

This week we talk with the NGO Direct Relief about the AI-powered Facebook Messenger chatbot they successfully fielded for customer service during disaster response events.  During a natural disaster like Hurricane Maria they field thousands of calls from people with needs ranging from emergency clean water and food to those who want to volunteer, donate, or simply learn more about the organization. Call volume goes up exponentially during these periods and with just three staff in the communications team call response times were extending out to 24 to 48 hours.  In this episode, we hear from Direct Relief's President and CEO Thomas Tighe and Communications Director Tony Morain about their smart approach to developing and fielding their customer service chatbot - literally during a natural disaster - and their next steps in building out the bot after it proved valuable in the field test. P.S. The bot helped reduce inquiry response times to under a minute. Nick Julia, founder and CEO at Mind Heroes - the agency that helped Direct Relief professionalize and expand their chatbot - explains the technology behind the bot and the best practices for successfully building and deploying a bot. Direct Relief's approach to putting this automation technology to use is a great example of how to rapidly design, develop, and deploy a pilot and then let the marketplace determine if it's viable. It's a cost-effective, fast, smart approach that flies in the face of more traditional methodologies that call for extensive, detailed and expensive due diligence and rollout. There's a great lesson here for any organization deploying AI, chatbots, or more broadly a marketing automation project.

This week we talk with the NGO Direct Relief about the AI-powered Facebook Messenger chatbot they successfully fielded for customer service during disaster response events.  During a natural disaster like Hurricane Maria they field thousands of calls from people with needs ranging from emergency clean water and food to those who want to volunteer, donate, or simply learn more about the organization. Call volume goes up exponentially during these periods and with just three staff in the communications team call response times were extending out to 24 to 48 hours.  In this episode, we hear from Direct Relief's President and CEO Thomas Tighe and Communications Director Tony Morain about their smart approach to developing and fielding their customer service chatbot - literally during a natural disaster - and their next steps in building out the bot after it proved valuable in the field test. P.S. The bot helped reduce inquiry response times to under a minute. Nick Julia, founder and CEO at Mind Heroes - the agency that helped Direct Relief professionalize and expand their chatbot - explains the technology behind the bot and the best practices for successfully building and deploying a bot. Direct Relief's approach to putting this automation technology to use is a great example of how to rapidly design, develop, and deploy a pilot and then let the marketplace determine if it's viable. It's a cost-effective, fast, smart approach that flies in the face of more traditional methodologies that call for extensive, detailed and expensive due diligence and rollout. There's a great lesson here for any organization deploying AI, chatbots, or more broadly a marketing automation project.

This week we talk with Bill Tedesco, CEO at DonorSearch and Nathan Chappell, President at Futurus Group about the product partnership they announced recently. Of course, Bill and DonorSearch are well-known in the industry for their donor prospecting tool incorporating the nation's largest philanthropic database and serving 1,000's of nonprofit, higher ed, and foundation organizations.  Futurus Group, a startup focused on deploying AI for major donor prospecting invented the Gratitude Score - a measure of a prospect's gratitude or affinity for an organization. The technology uses the machine learning technique called deep learning to evaluate the prospect's history of interactions with the organization and determine if they are likely to give. The Futurus+Donor Search brings their products together to provide fundraisers with valuable guidance on which donors are likely to give; i.e. have a high gratitude score, and how much they are likely to give. We dive into the products, the AI technology, and the real value and benefits delivered by the integrated solution. We wrap up the discussion with a look forward and get some particularly insightful and useful guidance on where donor prospecting is headed according to Bill and Nathan. Enjoy this week's episode. As always, if you have questions or feedback, feel free to email me at jeff.patrick@cohort3.com.

This week we talk with Bill Tedesco, CEO at DonorSearch and Nathan Chappell, President at Futurus Group about the product partnership they announced recently. Of course, Bill and DonorSearch are well-known in the industry for their donor prospecting tool incorporating the nation's largest philanthropic database and serving 1,000's of nonprofit, higher ed, and foundation organizations.  Futurus Group, a startup focused on deploying AI for major donor prospecting invented the Gratitude Score - a measure of a prospect's gratitude or affinity for an organization. The technology uses the machine learning technique called deep learning to evaluate the prospect's history of interactions with the organization and determine if they are likely to give. The Futurus+Donor Search brings their products together to provide fundraisers with valuable guidance on which donors are likely to give; i.e. have a high gratitude score, and how much they are likely to give. We dive into the products, the AI technology, and the real value and benefits delivered by the integrated solution. We wrap up the discussion with a look forward and get some particularly insightful and useful guidance on where donor prospecting is headed according to Bill and Nathan. Enjoy this week's episode. As always, if you have questions or feedback, feel free to email me at jeff.patrick@cohort3.com.

This week we talk with Art Komorov from Wisely, a startup focused on helping major gift officers raise more revenue using AI. Art, based in Toronto is the founder and CEO at Wisely, and a member of Next Canada, an accelerator program for startups. Art gives us the low-down on the Toronto start-up scene ("its frothing"), the twisty-turny path he took to leading a startup by way of public policy and sales at Blackbaud, and all the details about Wisely's Donor Portfolio Management solution powered by AI.

This week we talk with Art Komorov from Wisely, a startup focused on helping major gift officers raise more revenue using AI. Art, based in Toronto is the founder and CEO at Wisely, and a member of Next Canada, an accelerator program for startups. Art gives us the low-down on the Toronto start-up scene ("its frothing"), the twisty-turny path he took to leading a startup by way of public policy and sales at Blackbaud, and all the details about Wisely's Donor Portfolio Management solution powered by AI.

Misinformation, disinformation, fake news, deepfake videos, and the big event. We talk with think tank researcher Claire Leibowicz from the Partnership on AI -  the organization formed by the AI leaders at Google, Facebook, Amazon, IBM, and others. Its mission is to ensure AI technology has a positive impact on the people using it. That's a tall task given the nascent, chaotic, largely unregulated nature of the industry. We sort through it all.

Misinformation, disinformation, fake news, deepfake videos, and the big event. We talk with think tank researcher Claire Leibowicz from the Partnership on AI -  the organization formed by the AI leaders at Google, Facebook, Amazon, IBM, and others. Its mission is to ensure AI technology has a positive impact on the people using it. That's a tall task given the nascent, chaotic, largely unregulated nature of the industry. We sort through it all.

AI is making its way into fundraising at higher education institutions. This week Dana Gresko, from EAB (a Washington DC-based fundraising agency for advancement organizations) shares her insights on how AI is helping tune the direct marketing promotion for alumni communications.