How Might We Make Understanding Algorithms Easier for Everybody? AI-kitchen ran from 2015-2017 and focused on how to make it easy to discuss and critique how algorithms work. We worked with collaborators to translate algorithmic ‘writing’ into plain language to help people understanding how AI works and how it could be improved. We believe that the basic inputs, assumptions, steps, and outputs of algorithms should be as accessible as sharing and discussing recipes. To do this, our team reverse-engineered popular algorithms like Tinder’s matching algorithm and AirBnB’s location algorithm, and hosted regular discussion events at Harvard where we presented on how they work in plain language. Some of our core themes included: Human Values and How They Relate to AI; Algorithmic Writing and Critique; The Design of AI; Human-Robot Interaction; Human-Computer Interaction, and How to make AI more accessible, representative, and desirable. Ai-kitchen began as a mix of professionals and
Is Digital Nomadism a Viable Future of Work? After teaching a field course for a group of Harvard students in Indonesia in 2015 on the rise of a global digital nomadic workforce, Altringer began researching how digital nomads manage their finances. The research makes it clear that this is a growing phenomenon, and that a relatively small percentage of nomads are able to make a lifestyle of working while traveling or living abroad financially viable. The majority of nomads incur considerable financial risk with this approach to their careers. Read the research findings in this Forbes article: Globetrotting Digital Nomads: The future of work or too good to be true? A PDF copy is available by request. *NEW* We expect that digital nomadism is changing rapidly and want to see if things have changed since our initial findings in 2016. We have re-opened the survey as of April 2018! You
How Might We Train the Next Generation of Tech Leaders? In 2017-2018, Altringer has been building upon this research to co-design curriculum for a new dual graduate degree program at Harvard: the engineering MS + MBA. She and her team are also working to eventually make this body of work interactive and available to the public.
How Might We Make Design and Innovation Education More Evidence-Based? This multi-year study involved in-depth qualitative and quantitative analysis of over 300 projects in top design firms like IDEO. It examined the real-world complexity of innovation projects, which often involve multi-disciplinary, multi-cultural and multi-organizational collaboration, searching for patterns associated with more (and less) successful outcomes. This research has been supported by the Harvard Initiative for Learning and Teaching. Previous support came from MIT International Design Center and the University of Cambridge. The work was later continued as a six-year longitudinal study on the effectiveness of project-based experiential design and innovation courses.