RESEARCH AND PUBLICATIONS

Whether we want it or not, our lives are increasingly intertwined with smart and pervasive emerging digital technologies. We must acknowledge that while these technologies offer opportunities for enhanced convenience and efficiency, they also present a variety of challenges that can significantly impact their overall societal benefits. This research presents an analytical framework to critically assess the risks posed by new technological applications. Termed “brittle touchpoints,” these are interfaces between technology and users that hold the potential for significant negative impacts. The framework hinges on two key considerations: the technology’s “degree of brittleness” and the “frequency of touchpoints” during human-technology interactions. Based on this taxonomy, we classify touchpoints into four distinct types and discuss possible strategies with different levels of agency – Product Design, Ecosystem Orchestration, and Regulation and Oversight – that organizations can follow to mitigate risks and maximize the responsible adoption of their technologies.

Boosting insulation in homes – both new and old – represents a significant opportunity for reducing energy consumption and enhancing sustainability. The existing methods for retrofitting and insulation, which are both time-consuming and labor-intensive, pose a significant challenge. We propose that intelligent machines can improve and speed up our ability to make homes and buildings more energy efficient. Leveraging Northeastern University’s renowned expertise in robotic innovation, this joint project will develop best business practices for human-machine interactions in service of sustainability, through interdisciplinary collaboration with the Institute for Experiential Robotics (IER). This research program aims to a) understand how to organize tasks between intelligent machines and humans, by identifying the specific tasks in which machines can add the most value, and b) incorporate our findings in the design of intelligent machines to ensure safe and efficient interactions between machine and human stakeholders.

This research program aims to create a data-based decision-making model to enhance academic entrepreneurship by leveraging existing resources and data from The Center for Research Innovation (CRI). We will analyze the archival data from the previous Spark Fund applications and run surveys for entry into the Entrepreneurship Consultants (EC) program to gain insights into the successful science-to-business translation. Additionally, this research will explore novel approaches to evaluate the readiness of founders and their business ventures, and how to best match them with appropriate resources. We seek to guide both technology transfer offices and academic entrepreneurs to make informed decisions, improve their chances of securing funding, and foster a more vibrant entrepreneurial ecosystem within the university and beyond.