The following insights are derived from a recent session on GenAI in Healthcare. On November 15th, the D^3 Institute’s Generative AI Observatory hosted the first session in its GenAI in Healthcare series, produced in collaboration with the Responsible AI Institute. Speakers Satish Tadikonda (HBS), Nikhil Bhojwani (Recon Strategy), Var Shankar (Responsible AI Institute), and Alyssa […]
The following insights are derived from a recent Insights from the Field event featuring Chad Sanderson, covering the topic of Data Contracts for achieving high-quality data for Artificial Intelligence (AI). Overview Chad began this session by demystifying some hyperbolic claims in the world of Artificial Intelligence (AI), including the idea that AI models could replace […]
The following insights are derived from a recent Assembly talk featuring Hywel Benbow, regarding applying data analytics to enhance the performance of educational institutions. We presented a few question to Hywel during this talk, and what follows is a summary of his responses. Could you speak to some overarching and generalizable ways educational organizations could […]
On October 22-23, the Digital Reskilling Lab hosted the “Revitalize, Reinvent, Reskill: Unlocking Workforce Productivity” conference, a collaborative effort between the Digital Data Design Institute at Harvard and Managing the Future of Work at Harvard Business School. This event convened business leaders and reskilling practitioners to engage in discussions on reskilling methodologies and share cutting-edge […]
Since the launch of ChatGPT, GenAI has taken center stage, prompting business leaders to explore its potential for creating value. In a recent stimulating discussion featuring Bratin Saha, Iavor Bojinov, and Edward McFowland III, the conversation delved deep into the radical potential of GenAI and its seismic impact on businesses.
The following insights are derived from a recent Assembly talk featuring Olivia Jung, PHD, and Andrea Dorbu, MPH on Innovation Contests in Federally Qualified Health Centers in the United States. In this talk, Andrea and Olivia discussed a research project that they conducted across 54 Federally Qualified Health Centers (FQHCs) in the United States to […]
Historically, there has been limited attention and innovation in addressing issues like menopause, endometriosis, and menstrual health. This is partly due to the underrepresentation of women as inventors and entrepreneurs. However, some exceptional women like Geetha Manjunath and Linda Griffith have made significant contributions by leveraging their personal experiences and expertise. Geetha Manjunath, with a […]
In collaboration with Boston Consulting Group (BCG), new research from Digital Data Design Institute at Harvard chair and co-founder Karim Lakhani and others explores field experimental evidence of the effects of AI on knowledge worker productivity and quality. It involved evaluating the performance of 758 consultants, which make up 7% of the individual contributor workforce of the […]
The following insights are derived from a recent Assembly talk featuring Samir Sharma, the CEO of datazuum. Â
In this talk, Samir emphasizes the importance of connecting data strategy with business objectives via a detailed discussion of operating models, which are structured frameworks or organizational approaches that govern how an organization manages and utilizes its data analytics and related processes. Samir draws from his expertise in organizational psychology to highlight the challenges organizations face in embedding data and analytics into their core practices and considers the critical role of talent, systems, processes, and upskilling in building a successful operating model.
See table for a summary of the five types of operating models Samir discussed in this talk along with the advantages and challenges that come with adopting each model in a business setting.
When it comes to artificial intelligence and inequality, algorithmic bias rightly receives a lot of attention. But it’s just one way that AI can lead to inequitable outcomes. To truly create equitable AI, we need to consider three forces through which it might make society more or less equal: technological forces, supply-side forces, and demand-side […]