Home AI News MIT Awarded Seed Grants to Enhance Modern Workspaces with AI and HCI

MIT Awarded Seed Grants to Enhance Modern Workspaces with AI and HCI

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MIT Awarded Seed Grants to Enhance Modern Workspaces with AI and HCI

The MIT Stephen A. Schwarzman College of Computing has recently awarded seed grants to seven projects focused on exploring the use of artificial intelligence (AI) and human-computer interaction to enhance modern workspaces. These projects aim to improve management and increase productivity by leveraging AI technology. The grants, funded by Andrew W. Houston ’05 and Dropbox Inc., encourage interdisciplinary collaboration between researchers in computing, social sciences, and management.

These seed grants provide the selected project teams with the resources to conduct research in this rapidly evolving field and lay the foundation for further endeavors. Additionally, the grants aim to foster a sense of community and encourage discussions around AI-augmented management.

The seven projects that received seed grants are as follows:

1. LLMex: Implementing Vannevar Bush’s Vision of the Memex Using Large Language Models – This project, led by Patti Maes and David Karger, aims to design and test memory prosthetics using large language models. Inspired by Vannevar Bush’s Memex, the AI-based system will help individuals manage vast amounts of information, improve productivity, and reduce errors by automatically recording work actions and meetings, providing proactive suggestions, and assisting with information retrieval.

2. Using AI Agents to Simulate Social Scenarios – Led by John Horton and Jacob Andreas, this project explores the use of AI agents to simulate social scenarios before their implementation. By utilizing modern large language models as computational models of humans, this project aims to improve the realism and predictability of social simulations.

3. Human Expertise in the Age of AI: Can We Have Our Cake and Eat it Too? – Manish Raghavan and Devavrat Shah lead this project, which examines the potential for AI algorithms to complement human decision-making in various settings. Rather than replacing human professionals, this project envisions a future where AI and algorithmic decision aids work alongside human expertise.

4. Implementing Generative AI in U.S. Hospitals – Julie Shah, Retsef Levi, Kate Kellog, and Ben Armstrong collaborate on this project, aiming to develop a framework to study how generative AI technologies can increase productivity and improve job quality for healthcare workers. The project addresses the burnout experienced by doctors and nurses due to administrative burdens associated with electronic health records and other technologies.

5. Generative AI Augmented Software Tools to Democratize Programming – Harold Abelson, Cynthia Breazeal, and Eric Klopfer lead this project, which focuses on transforming computing education for individuals without technical training. The goal is to create a software tool that eliminates the need for learners to deal with code, thereby democratizing programming.

6. Acquiring Expertise and Societal Productivity in a World of Artificial Intelligence – David Atkin, Martin Beraja, and Danielle Li collaborate on this project to better understand how AI technologies impact skill acquisition and productivity. The project also explores policy interventions to maximize the benefits of AI technologies.

7. AI Augmented Onboarding and Support – Led by Tim Kraska and Christoph Paus, this project aims to develop new onboarding and support systems powered by large language models. These systems will help users overcome the steep learning curve typically associated with large language models, improving user experience and support team operations.

These projects represent exciting advancements in the field of AI and its applications in enhancing workspaces. By integrating AI and human-computer interaction, researchers aim to revolutionize management practices and increase productivity. The seed grants provided by the MIT Stephen A. Schwarzman College of Computing facilitate further research in this area and encourage interdisciplinary collaboration.

[img src=”https://news.mit.edu/sites/default/files/styles/news_article__cover_image__original/public/images/202308/Hands.jpg?itok=cL58lo8L” /]

Sources:
– MIT Stephen A. Schwarzman College of Computing: https://news.mit.edu/2023/artificial-intelligence-augmentation-and-productivity-0818

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