The AAAI has released a comprehensive roadmap for the AI research community, identifying seventeen high-priority areas that span technical advancement, ethical considerations, and broader societal implications. This expert-developed list provides a valuable framework for researchers, policymakers, and industry leaders to focus their efforts as AI capabilities continue to evolve and transform research methodologies and applications across disciplines.
1. AI Reasoning
This research area focuses on developing AI systems capable of logical thinking, inference, and problem-solving using rational processes similar to human reasoning.
2. AI Factuality & Trustworthiness
This priority addresses the challenge of ensuring AI systems provide accurate, reliable information while reducing hallucinations and misrepresentations that could mislead users.
3. AI Agents
This area explores autonomous AI systems that can perceive their environment, make decisions, and take actions to achieve specific goals, potentially working independently or collaboratively with humans.
4. AI Evaluation
This research focus aims to develop rigorous methodologies for assessing AI system performance, safety, and alignment with human values across diverse applications and capabilities.
5. AI Ethics & Safety
This priority examines the moral implications of AI development and deployment, including harm prevention, bias mitigation, and establishing frameworks for responsible innovation.
6. Embodied AI
This area investigates AI systems that interact with the physical world through robotics and sensor integration, enabling real-world perception and manipulation capabilities.
7. AI & Cognitive Science
This research explores the intersection between human cognition and artificial intelligence, potentially leading to more human-like AI systems and better understanding of our own mental processes.
8. Hardware & AI
This priority focuses on developing specialized computing architectures and infrastructure optimized for AI workloads, addressing efficiency, performance, and sustainability challenges.
9. AI for Social Good
This area applies AI capabilities to address pressing societal challenges in healthcare, education, climate science, and humanitarian efforts.
10. AI & Sustainability
This research examines both how AI can address environmental challenges and how to reduce the environmental impact of AI systems themselves through more efficient design.
11. AI for Scientific Discovery
This priority leverages AI to accelerate breakthroughs across scientific disciplines, from drug discovery to materials science and fundamental physics.
12. Artificial General Intelligence (AGI)
This area focuses on developing AI systems with human-level intelligence across multiple domains, including the technical challenges and potential impacts of such systems.
13. AI Perception vs. Reality
This research examines the gap between public perceptions of AI capabilities and their actual limitations, addressing both overhype and unwarranted dismissal of genuine advancements.
14. Diversity of AI Research Approaches
This priority promotes methodological diversity in AI research beyond the current focus on large language models and deep learning to explore alternative paradigms.
15. Research Beyond the AI Research Community
This area encourages interdisciplinary collaboration between AI researchers and experts from fields like sociology, psychology, economics, and law to address AI’s broader implications.
16. Role of Academia
This research focus examines how academic institutions can maintain their crucial role in AI advancement despite increasing industry dominance in the field.
17. Geopolitical Aspects & Implications of AI
This priority addresses international competition, cooperation, and governance challenges surrounding AI development and deployment across global power structures.
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