Highlights from Gary Gensler and Lily Bailey’s “Deep Learning and Financial Stability” outline five ways AI could lead to future financial crises.
Senior Lecturer, Marketing, Academic Head, Enterprise Management Certificate
This collection of prompt templates functions like cognitive scaffolding, providing structure without limiting options as you innovate.
Open-source and open-weight AI models perform well and cost less — but users opt for closed models 80% of the time, according to new research.
To foster a data-centric culture, adopt the right technology, improve data literacy, and don’t be afraid to disrupt the status quo.
Leaders must rethink the way they manage people and projects to ensure that everyone reaps the efficiency and innovation benefits of generative AI.
Henna Karna, EMBA ’18, discusses her journey through academia and her professional career, reflecting on how MIT Sloan's unique mix of quantitative and qualitative learning has influenced her work.
When stakeholders become more involved in generative AI design and implementation, it’s more likely that such tools will augment work rather than displace workers.
A new MIT Sloan Experts Series talk explains how algorithms and humans can work together to compensate for blind spots and create clearer outcomes.
Generative AI’s broad accessibility and applicability make it a vital tool for businesses — but those traits can also cause trouble when upskilling employees.
