Breaking the silos on AI Research for Good
A full-day Workshop at AI for Good Global Summit will foster impactful solutions on AI for Good
By Amir Banifatemi and Georgina Curto
Recent trends in AI research are reflecting a shift from purely technological advancements to the creation of AI solutions with significant societal impact. The AI community is increasingly focused on harnessing AI to support crucial global objectives including enhancing education quality, alleviating poverty, and combating climate change.
Despite these noble intentions, the actual impact of AI for Good initiatives remains modest in regard to its immense potential – as it aims to overcome hurdles bringing technical researchers and development communities together.
Establishing clusters for collaboration on these foundational topics, alongside applied domains like healthcare diagnostics and climate prediction for instance, could align and amplify our efforts.
Bridging the gap between theoretical AI advancements and tangible community benefits is critical for ensuring that innovations are both relevant and respectful. Encouraging research in fields like resource distribution analytics and AI-driven energy solutions for example can pave the way for sustainable, scalable social impact. Furthermore, overcoming data challenges will catalyze the transition of AI research from theory to transformative practice.
At the AI for Good Global Summit, this 1-day interactive workshop and discussion led by multidisciplinary and multilateral speakers participants will:
- Learn from the state of the art, opportunities, and obstacles in AI design for public good in practice.
- Discuss and design frameworks and incentives towards a collaborative approach to AI for Good from research to field applications.
- Define next steps and specific actions to accelerate the development and implementation of joint impactful, scalable and sustainable AI research for public good projects.
Collaboration among academia, technology corporations, nonprofits, and government entities is crucial for the Public Good. However, these sectors often operate in isolation driven by divergent goals, and while commendable they lack integration with the communities they aim to assist, undermining sustainability. Pure research areas such as algorithmic fairness, robust machine learning, and explainable AI could be useful for social good projects.
The path to integrating AI with social good initiatives is complex, requiring not just technological innovation but also an inclusive and coordinated approach that respects and involves local communities. This workshop aims to explore these challenges and collaboratively forge a roadmap for AI research that is directly impactful and sustainable.
Join the workshop and register for the AI for Good Global Summit here.
View all Workshops and Masterclasses at the AI for Good Global Summit.
