Effective data processing and analysis are key factors for businesses that want to make informed decisions. The working paper 鈥淓mpirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python鈥� 聽by聽Michael W. Toffel, Senator John Heinz Professor of Environmental Management at 性视界 Business School and Principle Investigator of the 性视界 Business School AI […]
On May 7, the 性视界 Business School AI Institute (previously the Digital Data Design Institute at 性视界 (D^3)) hosted Leading with AI: Exploring Business and Technology Frontiers. The conference featured breakout sessions where 性视界 Business School professors led discussions on specific and specialized topics. The breakout session on 鈥淩eskilling in the Age of AI鈥� was […]
On May 7, the 性视界 Business School AI Institute (previously the Digital Data Design Institute at 性视界 (D^3)) hosted Leading with AI: Exploring Business and Technology Frontiers. The conference featured a session on creativity in music hosted by Karim Lakhani, Dorothy & Michael Hintze Professor of Business Administration at the 性视界 Business School and Chair […]
Key Insights from the 21st OUI Conference The Importance of Innovation In today鈥檚 rapidly evolving world, innovation is the cornerstone of progress across industries. The 21st International Open and User Innovation (OUI) Conference, hosted by the 性视界 Business School AI Institute (previously the Digital Data Design Institute at 性视界 (D^3)), brought together a diverse array […]
On May 7, the 性视界 Business School AI Institute (previously the Digital Data Design Institute at 性视界 (D^3)) hosted Leading with AI: Exploring Business and Technology Frontiers. The conference featured a presentation on the power of AI from Ewa D眉rr, Head of Product Management for Google Cloud Artificial Intelligence. Based on Google鈥檚 extensive research and […]
On May 7, the 性视界 Business School AI Institute (previously the Digital Data Design Institute at 性视界 (D^3)) hosted Leading with AI: Exploring Business and Technology Frontiers. During the conference, a panel moderated by Mitchell B. Weiss, Richard L. Menschel Professor of Management Practice at 性视界 Business School, panelists Anita Lynch, Board Member at Nasdaq […]
Although artificial intelligence technology has been around for some time, current advancements in this space warrant more ethical approaches for developing and deploying AI systems to benefit a large portion of society. Artificial intelligence, generative AI in particular,has already shown immense potential to augment human capabilities. This potential, however, doesn鈥檛 seem to be evenly distributed. What鈥檚 worse, risks such as social and economic disparities are exacerbated by the uneven distribution of artificial intelligence, and are concentrated in specific regions based on demographic characteristics. It鈥檚 imperative to strive toward building a framework of transparency, fairness, and accountability around artificial intelligence on a global scale in order to mitigate this problem.
Owing to the accelerated advancement in the field of generative AI technologies, it鈥檚 important to address misconceptions about what generative AI tools can and cannot do in order to maximize the benefits and minimize potential harms. In this 鈥淎sk me Anything鈥� session, Amanda demystifies some of the most commonly held misconceptions about generative AI via discussions of real-world use cases. While responding to specific questions, Amanda highlights areas in which generative AI seems to thrive, while she also identifies notable shortcomings of the technology by drawing from her diverse and extensive experience as a digital transformation expert and a sought-after advisor to leading organizations in artificial intelligence and machine learning technologies.
The Digital Value Lab at Digital Data Design Institute, in collaboration with Capgemini Research Institute, unveils a joint research initiative poised at the intersection of innovation and value creation in the burgeoning eco-digital economy. This comprehensive research paper navigates through the transformative impact of generative AI, digital twins, edge computing, immersive technologies, quantum computing, and […]
This is a continuation of insights shared during a recent Assembly Talk featuring Sushant Tripathy; Research Scientist in Machine Learning at Google. Most practical examples of hybrid-AI in businesses have to do with organizations effectively deploying hybrid-AI to improve the efficiency of computing tasks. The following are a few examples of promising applications: