Abstract: Artificial Intelligence has reached a stage where the complexity of building, deploying, and maintaining models often rivals the challenges of the problems it seeks to solve. As AI systems scale across industries, the demand for automation in the AI lifecycle—from data preparation to model deployment—has become increasingly critical.
In this talk, Dr. Saket Anand and Dr. Lisa Amini will explore emerging opportunities in automating AI, focusing on how automation can accelerate innovation while reducing barriers to adoption. The discussion will highlight advances in AutoML, automated data engineering, and adaptive model management, emphasizing how these technologies can democratize AI by making it more accessible to non-experts.
Key themes include:
The role of automation in reducing human effort across the AI pipeline.
How automated systems can improve reproducibility, scalability, and fairness in AI applications.
Challenges in balancing automation with transparency and accountability.
Case studies from IBM Research and academic collaborations that showcase practical implementations of automated AI systems.
By examining both technical breakthroughs and organizational impacts, the speakers will shed light on how automation can transform AI from a specialized tool into a widely usable, reliable technology. The presentation will underscore the potential of automated AI to drive efficiency, foster innovation, and open new pathways for research and industry adoption.