Learning About Technology

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’t seem to be evenly distributed. What’s 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’s 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’s 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 “Ask me Anything” 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:

The following insights are derived from a recent Assembly Talk featuring Sushant Tripathy, Research Scientist in Machine Learning at Google. Hybrid AI has gained traction in recent years due to the increasing computational demands of advanced machine learning models. This article delves into the concept of hybrid AI, discussing its potential opportunities and limitations. The information […]

HBS Gender Initiative Director Colleen Ammerman wants to know: when does technology not work for you?

HBS Digital Initiative Director David Homa wants to know: how would you describe tech inequality?

Pathways to a Just Digital Future brings together thinkers, makers, and activists to unpack the roots of inequality in tech and chart a course toward a digital world that works for everyone.

DI editor Theresa Diederich reflects on the DI’s digital publication a year on and shares her highlights of the advancements in the tech community at HBS.

The explosion of available data and subsequent renaissance in data-driven decision making is poised to open up 2.7 million new jobs in analytics by 2020. To meet this growing demand, Harvard is taking an interdisciplinary approach to help professionals upskill their business analytics mastery.