"Code for a Cause" Philanthropic Tech Online Challenge Concludes, Practicing "Using Technology to Address Real Needs"

China News Network, Shanghai, August 30 (Reporter Chen Jing) - The "Code for a Cause" philanthropic technology online challenge, guided by the principle of "Using Technology to Address Real Needs," successfully concluded on the 30th.

Centered around two key themes – animal-assisted therapy and tech education – the competition focused on pressing social issues, attracting a wide range of participants from working developers to secondary school students, with the youngest contestant being just 13 years old. The judging panel, composed of leaders from non-profit organizations, technical experts, and frontline practitioners, conducted comprehensive evaluations based on social value, technical feasibility, sustainability, and implementation pathways.

Gloria Guo, the initiator of the competition, stated online: "Our generation was exposed to artificial intelligence very early. Meeting with non-profit organizations face-to-face and hearing about the challenges they face gives us a clearer sense of direction. It also helps more tech-skilled peers realize that code should not only be innovative but also useful – it must solve real-world problems."

Translating AI skills into social value embodies a concrete form of "technological idealism." In the animal-assisted therapy track, participants used the therapy, activities, and education framework of "Animal-Assisted Intervention (AAI)" to translate concepts into actionable digital solutions: One contestant integrated a "knowledge base + AI dialogue" into a mini-program, consolidating specialized content scattered across public accounts and training materials into a retrievable, queryable "domain-specific knowledge base," enabling the public and new volunteers to access professional information anytime.

Another contestant, with long-term experience in stray animal rescue, proposed gamified interactions for daily animal therapy activities, promoting a closed loop of guidance, education, governance, and community service. Furthermore, a participant used machine learning to build an "AI-Paw" human-machine collaborative selection system. This system identifies individuals with therapeutic potential from among family pets and stray animals and generates interpretable reports, aiming to reduce training failure rates and costs, thereby alleviating the industry bottleneck of "scarce therapy animals."

In the tech education track, participants applied the concept of "AI learning companions" to specific demographics and curricula. A female contestant from the computer industry, drawing from personal experience, focused on programming initiation and confidence building for adolescent girls. A student participant upgraded a campus platform into a global "PseudoOJ++ platform," integrating multiple computer science courses and providing features like automated judging with feedback, interactive training, and resource co-creation. This allows students in remote or under-resourced areas to also access high-quality, sustainable learning support, improving learning efficiency and expanding reach.

The judging panel noted that the competition entries, guided by real-world problems and aimed at practical implementation, demonstrated a strong practical ability to closely integrate technology, scenario, and user needs. The organizing committee will provide outstanding teams with follow-up support, including connections with philanthropic foundations and technical mentors, pilot implementation opportunities, and roadshow presentations, to promote the small-scale validation and iteration of excellent proposals within communities, schools, and partner organizations.