Francesca Rossi
IBM Fellow and AI Ethics Global Leader, AAAI
As artificial intelligence capabilities evolve rapidly, the field of AI research is undergoing a major transformation—reshaping its topics, methods, and community structures alike.
As AI capabilities evolve rapidly, AI research is also undergoing a fast and significant transformation along many dimensions, including its topics, methods, research community, and working environment. Topics like AI reasoning and agentic AI have been studied for decades but now have an expanded scope considering current AI capabilities and limitations. AI ethics and safety, AI for social good, and sustainable AI have become central themes in major AI conferences. Moreover, research on AI algorithms and software systems is becoming increasingly tied to substantial amounts of dedicated AI hardware, notably GPUs, leading to AI architecture co-creation, in a way that is more prominent now than over the last three decades.
AI ethics and safety, AI for social good,
and sustainable AI have become central
themes in major AI conferences.
Corporate Influence and the Changing Research Landscape
Related to this shift, more AI researchers work in corporate environments, where the necessary hardware and other resources are more easily available, compared to academia, questioning the roles of academic AI research, student retention, and faculty recruiting. The pervasive use of AI in our daily lives and its impact on people, society, and the environment makes AI a socio-technical field of study, highlighting the need for AI researchers to work with experts from other disciplines, like psychologists, sociologists, philosophers and economists. The growing focus on emergent AI behaviors rather than on designed and validated properties of AI systems renders principled empirical evaluation more important than ever. Hence the need arises for well-designed benchmarks, test methodologies, and sound processes to infer conclusions from the results of computational experiments. The exponentially increasing quantity of AI research publications and the speed of AI innovation are testing the resilience of the peer-review system, with the immediate release of papers without peer-review evaluation having become widely accepted across many areas of AI research. Legacy and social media increasingly cover AI research advancements, often with contradictory statements that confuse the readers and blur the line between reality and perception of AI capabilities. All this is happening in a geo-political environment, in which companies and countries compete fiercely and globally to lead the AI race. This rivalry may impact access to research results and infrastructure as well as global governance efforts, underscoring the need for international cooperation in AI research and innovation.
For more information: https://aaai.org/about-aaai/presidential-panel-on-the-future-of-ai-research/
