Hearing on Artificial Intelligence and Food Insecurity 

🎯 Key points for quick navigation: 00:04 *🏛️ Introduction and Agenda Overview* - Introduction of the hearing on AI and food insecurity, - Agenda and witness schedule, - Public comment procedures. 04:00 *📜 Study Background and Previous Work* - Review of the 2018 AI report and previous hearings, - Focus on AI addressing food insecurity. 07:12 *🍎 Food Insecurity in Yolo County* - Nolan Sullivan's overview of Yolo County's demographics, - Statistics on food insecurity. 14:07 *🤝 Partnerships and Funding Issues* - Role of Yolo Food Bank and funding challenges, - Issues with CalFresh funding and participation. 17:07 *🧠Application of AI in Social Services* - Integrating AI to improve social services, - Use of AI to streamline CalFresh applications. 21:05 *📱 Innovative Solutions and Outreach* - Implementation of Get CalFresh portal, - Expansion of outreach through mobile solutions. 24:04 *🏛️ Barriers and Political Will* - Political will and funding challenges at the county level, - Addressing the need for prioritizing food-insecure populations. 30:09 *🎓 Addressing Student Food Insecurity* - Efforts to target college students through financial aid offices, - Using FAFSA data for automatic CalFresh enrollment. 31:20 *🛠️ Technological Solutions and Cost Savings* - AI's potential to autofill applications across multiple programs, - Discussion on financial savings from reduced administrative costs. 33:07 *🛡️ Balancing Security and Accessibility* - Ensuring easy access to benefits while addressing fraud concerns, - Protecting privacy and avoiding profiling. 38:27 *💼 Broader Implications and Final Recommendations* - AI in preventing EBT skimming and starting with targeted populations, - Need for better funding and support for food banks. 42:27 *🛠️ AI and County Funding Challenges* - Challenges counties face in meeting CalFresh funding match, - Importance of supporting counties with limited means. 42:52 *📊 Introduction of Dr. Ilias Tagkopoulos* - Dr. Tagkopoulos' background in AI for food systems, - Focus on data integration, modeling, and decision-making. 48:42 *📉 Challenges and Needs for AI in Food Systems* - Need for data, models, and infrastructure specific to food systems, - Addressing these needs to make AI impactful. 51:10 *🚜 AI Applications in Agriculture* - Existing AI applications in agriculture, - Need for comprehensive integration and scaling. 56:22 *🏛️ Legislative and Infrastructure Support* - Role of legislative support in advancing AI in food systems, - Importance of access to supercomputing and research infrastructure. 59:45 *🍎 Beyond GMOs: AI and Food Quality* - Improving food quality with AI, - Creating nutritious and sustainable food products. 01:06:51 *🌱 AI in Food Quality and Sustainability* - Using AI to improve food quality and sustainability, - Creating commercially valuable food products. 01:15:20 *🤝 Collaborative Efforts for AI in Food Systems* - Collaboration between public policy, industry, academia, and consumers, - Successful AI applications in food production. 01:18:52 *📈 Improving Agricultural Extension with AI* - Digital Green's use of AI for cost-effective farmer training, - Generative AI reducing extension costs. 01:22:03 *🧩 Challenges and Feedback Mechanisms* - Addressing AI hallucinations and response accuracy, - Importance of human feedback loops and benchmark metrics. 01:26:00 *📱 Multimodal Access to AI Tools* - Ensuring AI tool accessibility across devices, - Collaborative efforts with UC Davis. 01:31:56 *🌱 Enhancing Agricultural Tools with AI* - Integrating UC Davis's crop management tool with AI, - Transitioning to mobile and natural language interfaces. 01:37:25 *🚜 Engaging Extension Agents and Ethnic Communities* - Role of extension agents in AI adoption, - Efforts to reach ethnic community farmers. 02:59:54 *📉 Impact of Pandemic Policies on Food Insecurity* - Food insecurity trends during COVID-19, - Effective policies to reduce food insecurity rates. 03:02:08 *🏥 Integrating CalFresh and Medi-Cal Enrollment* - Addressing low CalFresh enrollment rates, - Cross-talk between Medi-Cal and CalFresh enrollment platforms. 03:03:27 *🩺 Predicting Food Insecurity in Clinical Settings* - Using AI to identify food-insecure individuals in clinical populations, - Predicting eligibility for federal nutrition programs. 03:07:59 *🤝 Opportunities with CalAIM* - Integrating Medi-Cal with social services under CalAIM, - Enabling community-based organizations to bill for services. 03:12:23 *🏛️ Policy and Governance in AI Implementation* - Importance of ethical and responsible AI deployment, - Establishing frameworks for testing and scaling AI tools. 03:24:40 *🔄 Addressing Inequities with AI* - AI to address systemic inequities, - Protecting privacy and maintaining public trust. 03:31:19 *📋 State Employee Training and Procurement* - Training programs on AI for state employees, - Focus on senior managers for initial training. 03:41:54 *🌐 The Role of CalSAWS in Service Delivery* - CalSAWS as the case management system for eligibility support, - Enhancing customer experience and empowering county staff. 03:47:48 *🔍 Ethical Use of AI at CalSAWS* - Ensuring AI is fair and impartial, - Protecting customer privacy and data security. 03:56:11 *🕒 Benefits of AI in Call Centers* - Reducing post-call wrap-up time, - Ensuring consistent and accurate call summaries. 04:01:10 *🤔 Addressing Accuracy and Bias in AI* - Ensuring accuracy and context in AI-generated summaries, - Continuous validation of customized AI solutions. 04:10:14 *📝 Tracking Abandoned Applications* - CalSAWS tracks abandoned applications, - Engaging with applicants to remove barriers.

Lots to unpack listening to the entirety here. Coming from the food waste arena and seeing the amounts from 'timed out/leftovers' from the 12K weekly medical meals made by a governmental contracted commercial kitchen, the inherent waste (time, materials, and labor) pales to nothing when compared the bureaucratic organization working within the silos and dealing with the stupefying lack of efficiency. My team of 2 runners can dip in and collect 500-800lbs of Animal Food Rescue(d) weekly and distribute to nearly 200 animals on a regular basis within the "golden hour" of the material, but 200 needy people entering the safety nets will spend far too much energy just trying to communicate their needs with the organizations. And then wait for weeks! I don't think AI is the key here. At least Julia Erdkamp, Executive Director of the California Statewide Automated Welfare System (CalSAWS) gives me hope.