Instructor Spotlight: Emmett McKinney

Tell us about your background and what inspired you to teach this course

I think of myself as a transit planner and civic technologist. Decarbonization has been the guiding passion of my career, though my theory of change has evolved over time. First, I focused on environmental law. Translating policy goals into real emissions cuts requires that we develop new technology and rethink all of our infrastructure systems. Cities interest me in particular because they’re where the people are! Over 50% of humanity dwells in an urban environment. Thus, cities hold the potential for deep emissions cuts — from buildings, energy grids, and transportation systems — but they are also contested, evolving spaces. 

So when pursuing my Master’s in City Planning from MIT, I focused on data science and equitable development. My thesis zeroed in on Los Angeles’s shared mobility pilots, highlighting the potential of open data to support transit systems that are both “smart” and “equitable.” This expertise led me to join the Product team at Superpedestrian, a micromobility start-up where I led data science projects and managed several teams of engineers.

Why teach this course? For me, it’s because tech is shaping our relationship to cities and the built environment in fundamental ways. The “smart city” movement has long promoted the idea that new technology can “solve” cities’ longstanding, deeply entrenched challenges. Maybe that’s true of some technologies, for some issues. But if we, as a society, are to maximize the benefits (and limit the harms) of new technology, we have to sharpen our senses, cut through the hype, and think deeply about the tradeoffs technology presents.

What kinds of “Smart” tech might Tufts students encounter off or on campus?

Indoors, a common one would be appliances like thermostats, refrigerators, and dishwashers, which use AI to optimize usage and save consumers on energy bills. Your residence may also have a “smart meter,” which shares real-time information with the utility company about your home energy usage. This allows the utility to increase the reliability and lower the carbon footprint of the energy system. Walking down the street, you’re likely to be recorded by security cameras that are passing footage to AI systems analyzing all kinds of things: from counting pedestrians and cyclists to inform transportation planning, to scanning faces in search of suspected criminals. Look up at what you think is a tree, and you may spot a distributed antenna system, which amplifies the cell signal from a radio tower much further away and allows you to get 5G coverage on campus. While you’re pondering how cell networks work, an autonomous vehicle may cruise by. And when you get back to your dorm to tell your roommate all about the technology you saw today, you may be greeted by a projection of your roommate’s eyes on the front of their new VR headset. 

Your course focuses specifically on civic technology projects happening in Boston. Can you tell us a bit more about these projects and how students are interacting with it? 

Boston is a great place to teach about smart cities, since the city and region are full of technologists and urbanists looking for solutions to big problems. The Mayor’s Office of New Urban Mechanics (MONUM) is the City of Boston’s in-house innovation team. MONUM uses a blend of high-tech and low-tech approaches to help the city better meet the needs of its residents. This semester we’ll have a few guest speakers from MONUM, which will give students a chance to see what it really means to build a “smart city” and meet the people working on it in their own backyard.

What do you hope that students will take away from your course?

My goal is for students to leave feeling more aware of urban tech, skeptical of it, and inspired to put tech to its highest and best uses. The course aims to build students’ vocabulary to talk about tech, and the paradoxes and tradeoffs that come with it. I hope they’ll leave feeling ready to engage fellow citizens on these big questions, and rather than being paralyzed by the complexity, that they’ll feel empowered to propose a way forward.

What has happened so far in class that has surprised you?

We have spent the last few weeks talking about data. What do we count as “data”? Where does it come from? How is it produced? How can data be biased — and who does that bias benefit or harm? 

To unpack these questions, I asked students to quantify something in the building. It could be anything: backpacks, posters, water fountains. The only rule was that students had to collect 10 observations with at least 5 attributes each.  Students discovered that the process of building a dataset is actually rife with subjective judgements. One team counting backpacks wrestled with questions like: do all pockets, or only zip pockets count? If a backpack is multicolored, which color is the main one? How big does a backpack need to be to fit into the “big” category? Does a messenger bag count as a backpack? This led into a discussion of algorithms and machine learning tools used to “optimize” various systems. If the data that is produced in the first place is biased, can we really trust the outcome of the model?

Emmett McKinney is an urban planner and civic technologist. He has worked closely with city planners, leveraging data to inform sustainable transportation plans and integrate e-scooters with public transit. Emmett has edited research for the MIT Science Policy Review, co-led data analysis with local planning non-profits, and built several web-based visualizations of open data published by the MBTA and BlueBikes. He holds a Master’s in City Planning from MIT.