Human connection
Strengthen real-world human connections.
SUNY AI Partnership Project 3
AI for Good Challenge
Theme: Social Connection and Community Resilience
October 16 & 172026
Minerva Room (LI-B003)University Library, University at Albany
The challenge begins in
AI for Good Challenge
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Welcome to the AI for Good Challenge!
Artificial intelligence has the power to transform how we live, work, and connect. But technology creates its greatest value when it helps solve real human problems.
Led by the University at Albany AI & Society College, and funded by the SUNY AI for the Public Good Initiative, the AI for Good Challenge brings together students and faculty across four SUNY campuses (University at Albany, SUNY Oneonta, SUNY Cobleskill, and Hudson Valley Community College) to design AI-enabled solutions that address one of the most pressing social issues of our time: social isolation and loneliness. Participants will work in interdisciplinary teams to explore how AI can help reconnect people with their communities, strengthen social support networks, and improve access to meaningful opportunities for engagement.
Over two days, teams will move from problem discovery and human-centered design to prototype development, responsible AI assessment, and solution pitching. Along the way, participants will apply technical skills, creativity, ethical reasoning, and collaborative problem-solving to develop solutions that have the potential to create measurable social impact.
This Year’s Design Challenge
Rates of social isolation and loneliness have increased across age groups and communities. In Upstate New York, these challenges are often intensified by geographic dispersion, aging populations, limited transportation options, shrinking community institutions, and barriers to accessing local resources.
How might we use AI to reconnect socially isolated individuals with the people, places, organizations, and services that can strengthen their sense of belonging and participation in community life?
Participants are challenged to design solutions that:
- Understand users through a simple, low-friction intake process.
- Identify barriers to social connection and community participation.
- Provide personalized recommendations and pathways to engagement.
- Encourage sustained involvement with community networks and services.
- Use AI to facilitate human relationships rather than substitute for them.
More Than a Hackathon
This challenge is not simply about building technology. It is about designing responsible, inclusive, and practical solutions that address real community needs. Successful teams will demonstrate how AI can:
- Strengthen real-world human connections
- Improve accessibility and inclusion
- Support rural and underserved populations
- Promote trust, privacy, and responsible innovation
- Create meaningful and sustainable social impact
Join us as we explore how technology can help build stronger, more connected communities. Together, we can imagine and create AI solutions that put people first.
Design principles
Use AI to facilitate human relationships rather than substitute for them.
Strong ideas, user-centered design, accessibility, responsible AI practices, and community impact are valued as highly as technical sophistication.
Accessibility and inclusion
Improve accessibility and inclusion and support rural and underserved populations.
Responsible innovation
Promote trust, privacy, and responsible innovation.
Rules and eligibility
Who Can Participate?
The AI for Good Challenge is open to faculty as well as undergraduate and graduate students from all academic disciplines.
We encourage participation from individuals with diverse backgrounds, including:
- Computer Science and Information Science
- Data Analytics and Artificial Intelligence
- Public Administration and Policy
- Health and Human Services
- Psychology and Sociology
- Philosophy
- Design and Human-Computer Interaction
- Business and Entrepreneurship
- Other related fields
Interdisciplinary collaboration is strongly encouraged.
Teams will have a maximum of ten members and will have representation from two or more institutions. Represented institutions will have a maximum of one faculty member as well as a minimum of two undergraduate and two graduate students.
If you are a student and do not have a team but would like to be part of one, please, fill the following expression of interest form.
Student form ↗If you are a faculty member and do not have a team but would like to be part of one, please, fill the following expression of interest form.
Faculty form ↗Deliverables
Teams will submit four core deliverables:
Working software prototype
Working software prototype (for example, a lightweight web application, mobile app, dashboard, or chatbot) that demonstrates the core functionality of the proposed solution.
UI/UX wireframe or user journey map
UI/UX wireframe or user journey map illustrating the intended user experience, key workflows, and user interactions.
Pitch deck
Pitch deck (5 to 10 slides) describing the problem, proposed solution, AI methodology, anticipated benefits, target users, implementation strategy, and expected societal value.
Responsible AI assessment
Responsible AI assessment addressing ethics, bias, fairness, transparency, privacy, security, potential risks, unintended consequences, and mitigation strategies.
Teams should focus on developing a compelling proof of concept rather than a production-ready platform. Further, teams are encouraged to draw on diverse perspectives and skills, including community engagement, design, ethics, public policy, social sciences, health, and technology. Successful solutions will balance technical innovation with social impact, accessibility, and responsible AI considerations.
Resources
Accessibility Guidance and Resources
W3C Web Content Accessibility Guidelines (WCAG) 2.2https://www.w3.org/WAI/standards-guidelines/wcag/ ↗W3C Accessibility Fundamentalshttps://www.w3.org/WAI/fundamentals/ ↗ADA.gov Digital Accessibility Guidancehttps://www.ada.gov ↗Microsoft Inclusive Design Toolkithttps://inclusive.microsoft.design ↗
UI/UX design references and examples
Recommended Development Tools
Participants are welcome to use any tools that help them develop and communicate their solution. Technical expertise is not required to participate. Teams are encouraged to select tools that match their skills and project goals. Strong ideas, user-centered design, accessibility, responsible AI practices, and community impact are valued as highly as technical sophistication. Teams may use:
- Generative AI tools (e.g., ChatGPT, Copilot, Claude, Gemini)
- Low-code and no-code development tools (e.g., Bubble, Glide, Softr, Microsoft Power Apps, AppSheet)
- Design and prototyping tools (e.g., Figma, Canva, Miro)
- Machine learning and AI development platforms (e.g., PyTorch, TensorFlow, Hugging Face)
- Open-source software and development frameworks (e.g., React, Flutter, Streamlit, Django, .NET)
- Publicly available datasets and data sources
- Cloud services and APIs
- Machine learning and AI development platforms (e.g., Microsoft Azure, AWS, Google Cloud, OpenAI API)
- Commercial software and services with appropriate licenses
Tutorials and Learning Resources
October 13, 10am–12pmJoin Zoom session ↗
Instructor: Prof. Mahdi Ahmadi
Schedule and event experience
The AI for Good Challenge is structured as a two-day, problem-first, faculty-mentored design sprint. Rather than emphasizing coding alone, the event should guide interdisciplinary student and faculty teams across campuses through a sequence of activities that includes:
- Understanding a real community problem
- Identifying affected stakeholders and community needs
- Developing a focused and feasible AI-supported solution
- Examining the solution’s ethical and social implications
- Creating a prototype or proof of concept
- Communicating the solution to judges and community partners
- Reflecting on the learning process and possibilities for future development
Day 1: Understanding the Problem and Designing Solutions
Day 1 Objective
The goal for Day 1 is to understand the problem, define the user, identify barriers to connection, and design an AI-enabled solution that strengthens participation in community life. The main question teams will work on is: Who is experiencing social isolation, why is it happening, and how can AI help reconnect them to community life?
By the end of Day 1, teams should have:
- A clearly defined target population
- A well-articulated problem statement
- An understanding of barriers to connection
- A proposed solution concept
- A user journey
- A clear explanation of how AI adds value
- A clear pathway from AI interaction to human connection
Expected output for Day 1 is a validated solution concept, not a prototype. In other words, teams should end Day 1 knowing: “This is the problem we are solving, for these users, and this is how our AI-based solution creates meaningful community connections”.
Day 1 Agenda
Registration, breakfast, and informal networking
Participants check in, receive materials, meet students from other campuses, and enjoy breakfast
Opening ceremony
Welcome from UAlbany’s Provost and AI & Society College leadership; guest speaker on responsible innovation, including privacy, bias, transparency, accessibility, safety, human oversight, and potential unintended consequences
Introduction to challenge, logistics, and rooms’ assignments
Introduction to event objectives, challenge, schedule, rules, resources, judging process, and expectations; review logistics and schedule for the day and confirm available organizers
Sprint 1: Problem discovery and user understanding
Teams create problem statement (who is experiencing social isolation?, why is isolation occurring?, what are the consequences?), user profile (target user, context, needs, strengths, constraints), and community connection barrier analysis (e.g., transportation, lack of information, language barriers, low confidence,…)
Working lunch
Teams continue problem discovery and user understanding
Milestone finalization point 1; break and progress announcement
Teams submit a one-paragraph problem statement, a primary user profile, and a community connection barrier analysis; organizers share reminders
Sprint 2: Solution design
Teams develop their concept, taking into account deliverables’ characteristics and judging criteria
Milestone finalization point 2; break and progress announcement
Teams submit solution overview, user journey map, description of AI functionality, and human connection strategy; organizers share reminders
Sprint 3: End-of-day concept review
Teams work on the end of the day concept review, which includes information about problem, user, barrier, proposed solution, and user journey; teams’ faculty challenge assumptions and help refine concepts; teams plan for Day 2
Milestone finalization point 3; reflection on Day 1 and closing
Teams submit the end of the day concept review; participants complete a short reflection and receive Day 2 instructions
Day 2: Prototype Development and Validation
Day 2 Objective
The goal for Day 2 is to develop a prototype, evaluate its impact and responsibility, and communicate a compelling vision for implementation and scale. The main question teams will work on is: Can we demonstrate that this idea is feasible, responsible, and capable of creating real-world impact?
By the end of Day 2, teams should have:
- A working software prototype (for example, a lightweight web application, mobile app, dashboard, or chatbot) that demonstrates the core functionality of the proposed solution
- A UI/UX wireframe or user journey map illustrating the intended user experience, key workflows, and user interactions.
- A pitch deck (5 to 10 slides) describing the problem, proposed solution, AI methodology, anticipated benefits, target users, implementation strategy, and expected societal value.
- A responsible AI assessment addressing ethics, bias, fairness, transparency, privacy, security, potential risks, unintended consequences, and mitigation strategies.
Expected output for Day 2 is a prototype-supported proposal that demonstrates community need and relevance; social impact, equity, and accessibility; responsible use of AI, privacy and trust; and feasibility and sustainability.
Day 2 Agenda
Arrival, breakfast
Teams reconnect, review plans, and resolve immediate technical or logistical issues
Day 2 launch
Organizers review the submission deadline, presentation format, judging criteria, and available support
Sprint 4: Prototype development
Teams develop the primary functions, workflow, model, interface, visualization, mockup, or technical demonstration
Midpoint design review
Teams report status using a simple green, yellow, or red indicator, identify any critical obstacles, and review the following questions: 1) how does the solution reduce social isolation?, 2) what human connection is being created?, 3) how are equity and accessibility addressed?, 4) what risks have been identified and how are they going to be addressed?, and 5) would this work in a rural or small-town setting?
Working lunch
Teams review prototype and continue development
Sprint 5: Responsible-AI assessment
Teams conduct a responsible AI assessment that addresses ethics, bias, fairness, transparency, privacy, security, potential risks, unintended consequences, and mitigation strategies
Sprint 6: Finalize submission and pitch
Teams complete documentation, record backup demonstrations if needed, and rehearse presentations
Milestone finalization point 4
All required materials are locked for judging
Break and showcase setup
Teams move to presentation stations or prepare the main presentation room
Preliminary showcase or judging round
Judges rotate among team stations
Judges deliberate
Participants complete reflections about the event while judges deliberate
Awards and closing ceremony
Winners are announced; community partners and organizers recognize all participants and identify opportunities for continued development
Submission requirements
There will be four submissions during the two days:
Day 1 - Milestone finalization point 1Teams submit a one-paragraph problem statement, a primary user profile, and a community connection barrier analysis; organizers share reminders.
Day 1 - Milestone finalization point 2Teams submit solution overview, user journey map, description of AI functionality, and human connection strategy.
Day 1 - Milestone finalization point 3Teams submit the end of the day concept review.
Day 2 - Milestone finalization point 4Teams submit final package consisting of working software prototype, UI/UX wireframe or user journey map, pitch deck, and responsible AI assessment.
Submissions will be collected through Microsoft Forms for standard file formats (e.g., pitch deck and responsible AI assessment). Code repositories, prototypes, and other materials may be submitted via a cloud storage service such as OneDrive. Submissions will automatically receive a timestamp. Late submissions could remain eligible for participation and feedback but become ineligible for competitive awards unless the delay resulted from a documented event-wide technical issue.
Judging criteria
Submissions will be evaluated on the following six dimensions:
25%Community need and relevance
20%Social impact, equity, and accessibility
15%AI appropriateness and innovation
20%Responsible AI, privacy, and trust
10%Feasibility and sustainability
10%Prototype, user experience and communication
Under each dimension, judges will consider the following:
Community need and relevance (25%)
- Does the team understand the problem?
- Does the solution drive meaningful in-person connection?
- Does it address the needs of isolated individuals?
- Is the solution designed for the realities of the region and local communities?
Social impact, equity, and accessibility (20%)
- Will the solution generate meaningful social benefit?
- Does it reach seniors, rural residents, low-digital-literacy populations, and non-smartphone users?
- Is accessibility built into the design, including consideration of ADA and WCAG accessibility principles, where applicable?
- Does it promote inclusion and equity?
AI appropriateness and innovation (15%)
- Is AI being used where it adds genuine value?
- Is the approach creative and innovative?
- Does the solution make meaningful use of contextual information such as language, culture, age, or user needs?
Responsible AI, privacy, and trust (20%)
- Does the solution respect privacy and dignity?
- Are consent and transparency addressed?
- Have risks, biases, and unintended consequences been identified?
- Are mitigation strategies realistic and appropriate?
Feasibility and sustainability (10%)
- Can the solution realistically be implemented?
- Will it work in rural and small-town settings?
- Can it be maintained and scaled over time?
Prototype, user experience, and communication (10%)
- Does the prototype effectively demonstrate the concept?
- Is the user journey clear and intuitive?
- Does the pitch communicate the idea convincingly?
Prizes
The team with the highest score will receive $3,000 total in gift cards to be distributed among participating students.
The team with the second highest score will receive $2,000 total in gift cards to be distributed among participating students.
The team with the third highest score will receive $1,000 total in gift cards to be distributed among participating students.
Judges
Annmarie Lanesey
LinkedIn profile ↗
Shourya Sarcar
LinkedIn profile ↗
Amy
Nitza
LinkedIn profile ↗
Derek Werthmuller
LinkedIn profile ↗Guest speaker
Dr. J. Ramon Gil-Garcia
Responsible AI Innovation in the Public Sector: Characterizing Accountability from a Citizen Perspective
LinkedIn profile ↗View bio
J. Ramon Gil-Garcia, Ph.D., is a Full Professor of Public Administration and Policy and the Director of the Center for Technology in Government, University at Albany, State University of New York (SUNY). Dr. Gil-Garcia is a Fellow of the National Academy of Public Administration in the United States. In 2009, Dr. Gil-Garcia was considered the most prolific author in the field of digital government research worldwide and in 2018 and 2019 was named “One of the World’s 100 Most Influential People in Digital Government” by Apolitical, a nonprofit organization from the United Kingdom. In 2021, he was one of the recipients of the two inaugural Digital Government Society Fellows Awards. He is also a professor at Universidad de las Américas Puebla in Mexico, a Faculty Affiliate at the National Center for Digital Government at the University of Massachusetts Amherst, and an Affiliated Faculty member of the Information Science Doctorate Program at the University at Albany. His research interests include collaborative digital government, smart cities and smart governments, artificial intelligence in government, emerging technology adoption and implementation, digital divide policies, digital government success factors, and multi-method research approaches.
Registration page
General Information
What is the SUNY for the Public Good initiative?
It is a partnership between the University at Albany, SUNY Oneonta, SUNY Cobleskill, and Hudson Valley Community College to strengthen AI teaching and research across the region. It includes four coordinated initiatives:
- The AI Preparedness Academy and Faculty Learning Community, a collaborative initiative designed to build institutional capacity for AI by equipping faculty with the tools and critical frameworks to teach about and with AI, while fostering interdisciplinary dialogue, hands-on learning and exchange of practices.
- The AI for Good Challenge, an annual cross-campus competition bringing together interdisciplinary teams of students and faculty to develop AI-powered solutions to real-world community challenges.
- The Visiting/Affiliated Faculty Program, a collaborative effort supporting faculty in co-developing AI-infused microcredentials, courses and instructional materials, expanding interdisciplinary learning opportunities for students across institutions.
- The AI Plus Collaborative Research Experience (CORE), a hands-on research and mentorship program connecting undergraduate students, graduate assistants and faculty in cross-campus teams, culminating in a Summer Research Intensive hosted by UAlbany.
What is the AI for Good Challenge?
The AI for Good Challenge is a two-day innovation competition that brings together students and faculty from diverse disciplines to design AI-enabled solutions that address a significant social challenge. This year's focus is social isolation and loneliness, with an emphasis on strengthening community connections and improving participation in community life.
What is this year's design challenge?
Participants are asked to address the following question: How might we use AI to reconnect socially isolated individuals with the people, places, organizations, and services that can strengthen their sense of belonging and participation in community life?
Who can participate?
The challenge is open to both undergraduate and graduate students as well as faculty from all academic disciplines. Teams with technical, design, social science, public policy, health, business, and other backgrounds are encouraged to participate.
Do I need programming experience?
No. Technical expertise is not required. Teams are encouraged to combine diverse skills and perspectives. Strong ideas, user-centered design, accessibility, responsible AI practices, and community impact are valued as highly as technical implementation.
Can I participate if I have never used AI tools before?
Yes. The challenge is designed to be accessible to participants with varying levels of experience. Resources and learning materials will be provided to help participants get started.
Teams
Can I register as an individual?
No. However, we can help you find a team. If you are a student please, fill the following expression of interest form. If you are faculty member, please, fill the following expression of interest form.
Can I register with a team?
Yes. Teams may register together if they already have a group assembled.
How many people can be on a team?
Teams will have a maximum of ten members and will have representation from two or more institutions. Represented institutions will have a maximum of one faculty member as well as a minimum of two undergraduate and two graduate students.
Can team members come from different disciplines?
Absolutely. Interdisciplinary teams are strongly encouraged because successful solutions often require technical, social, design, and policy perspectives.
Technology and Development
Do we have to build a fully functional application?
No. Teams are expected to develop a proof of concept that demonstrates the key ideas behind their solution. Judges will evaluate both the concept and its implementation.
What technologies can we use?
Teams may use any appropriate tools, including:
- Generative AI tools
- Low-code and no-code platforms
- Design and prototyping tools
- Open-source software
- Machine learning frameworks
- Public datasets
- Cloud services and APIs
- Commercial tools with appropriate licenses
Can we use generative AI tools such as ChatGPT, Copilot, Claude, or Gemini?
Yes. Participants are encouraged to use AI tools responsibly and transparently as part of their development process.
Can we use pre-existing code or libraries?
Yes. Teams may use publicly available libraries, frameworks, and tools, provided they comply with applicable licensing requirements and properly acknowledge their use.
Deliverables
What must teams submit by the end of the challenge?
Each team must submit:
- A working software prototype
- A UI/UX wireframe or user journey map
- A pitch deck (5-10 slides)
- A Responsible AI Assessment
What should the Responsible AI Assessment include?
Teams should discuss:
- Ethics and fairness
- Transparency
- Privacy and security
- Potential risks
- Unintended consequences
- Bias mitigation strategies
- Accessibility considerations
Judging
How will projects be evaluated?
Projects will be judged on:
- Community need and relevance
- Social impact, equity, and accessibility
- AI appropriateness and innovation
- Responsible AI, privacy, and trust
- Feasibility and sustainability
- Prototype, user experience, and communication
Is the most technically advanced project likely to win?
Not necessarily. Judges will evaluate how well solutions address the challenge, create social value, promote accessibility and inclusion, and use AI appropriately. Technical sophistication is only one component of evaluation.
Are accessibility and inclusion important?
Yes. Solutions should consider the needs of rural communities, aging populations, individuals with limited digital literacy, and people from diverse linguistic and cultural backgrounds.
What does "AI should facilitate human relationships rather than substitute for them" mean?
The goal is to design solutions that help people connect with other people, organizations, services, and community activities. Successful solutions will demonstrate how AI supports real-world engagement rather than replacing it.
Event Logistics
What should I bring?
Participants should bring:
- A laptop
- Chargers and accessories
- Any software or accounts needed for development
- Enthusiasm and creativity
Will food be provided?
Yes, breakfast and a light lunch will be served during both days.
Will Internet access be available?
Yes. Information about Internet access will be available during the first day of the event.
What happens after the challenge?
Teams will present their solutions to a panel of judges. Awards will be presented following judging and deliberation.
Intellectual Property
Who owns the ideas and projects developed during the challenge?
Teams retain ownership of the ideas, code, designs, and materials they create during the event unless otherwise specified by the organizers.
Can organizers showcase submitted projects?
Yes. By participating, teams grant organizers permission to showcase project summaries, presentations, screenshots, and demonstrations for educational and promotional purposes, with appropriate attribution.
People behind the challenge
Executive Team Committee
- Mila Gasco Hernandez, AI & Society College, University at Albany
- Hany Elgala, AI & Society College, University at Albany
- Isabella Sunkes, AI & Society College, University at Albany
Organizing Committee
The AI for Good Challenge would not have been possible without the participation of the following individuals:
University at Albany
Jianwei Zhang, Mahdi Ahmadi, Zheng Wu, Chanhee Choi, Nathan Dahlin, Rukhsana Ahmed, Ohbet Cheon, Luyi Jian
SUNY Cobleskill
Ian MacDonald, Grace Begany, Andrew Magnuson
SUNY Oneonta
Sen Zhang, Steve Maniscalco, Gina Solano
Hudson Valley Community College
Tyler H. Kessel, Peter Sawyer, Shawna-Kay E Addison, Jaya Dasgupta, Jodi Mather, Robert Braathe, Danielle R. Blesi, Linda Lim, Colleen Bartels, Sara Martin
Still Have Questions?
Please, for additional information or inquiries about the AI for Good Challenge, contact:
Sponsors
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