Before now, I had never really considered sensor journalism— or even really knew what it was— nor what it means for the future of reporting. On first hearing of sensor journalism, I imagined that it was gathering data from highly specialized instruments that only well-trained journalists could use. But listening to the guest speakers and working our own class workshop, I learned that censorship journalism means taking in data from sensors to tell a story, which is something that journalists do everyday. Using this definition, it’s more exciting to think about the possibilities of storytelling through sensor journalism. 
After hearing the presentation by MIT student Lily Bui, I learned that anything that takes in data from the environment— thermometers, step trackers, heart rate monitors, cell phones, and even our own five senses. Because there are many sensors for reporters to use, the opportunities for sensor journalism are many and the data gathered helps not only to tell the story, but also to show how the story impacts the audience. The most obvious examples would be weather and climate based data taken from various meteorological sensors, showing readers how the immediate and near-future weather reports would affect their lives. 
But other more specific stories involving sensors would be like the example from the Tow Center, the case study featuring Alison Young’s stories about possibly toxic soil samples. The Tow Center wrote that in Young’s research, she kept seeing a certain instrument to measure soil make up. The X-Ray Fluorescence (XRF) analyzer shoots a laser and injects soil with an x-ray and fills atoms with energy. Because atoms then give off a specific wavelength, the XRF then reads and registers the data, and displays it. 
The Tow Center wrote that Young realized that “(the) fact that so many different people were using these new tools hinted to Young that the reporters could do some of the data collection themselves, bypassing the huge expense of outsourcing the sampling and increasing the amount of data they could collect, economically speaking.”
In the end, Young’s report made waves in its community and the sensors she used for the story helped greatly. Her example shows how journalists can use new technology to gather their own data and learn to interpret it themselves. Sensors like XRF are a bit more complicated than the average thermometer or pedometer, but Young proved that the technology to tell specialized sensor stories is out there and not impossible to learn.
Young’s story with the XRF is one example of journalists taking advantage of new tools to gather data for an important story, but in class we learned about another type of sensor journalism, one that takes its data from sensors given to citizens to crowd source. The example we learned of in class was the Public Lab and water testing. Our workshop in class featured a DIY water testing kit that with help and instructions all of us were able to put together and then use to test our own samples. The hands-on approach and easy to assemble kit showed me how accessible journalists and news outlets could make sensor technology for the people. Though our findings and the overall end results weren’t very applicable to show specific data findings, the kits proved that sensor journalism isn’t limited to the newsroom and if the reader gets involved, they become more invested in the data and the story. I realized that when students used water from the dorms and other Emerson sources, and I wanted to test to make sure that our water was clean.
Overall, my new experiences with censorship journalism excited me to the new ways to find, tell, and enhance news stories. As technology advances, I can see the many opportunities for this form of journalism to become an expected part of the digital future. If things that people carry everyday, like wearables, phones, and computers are constantly sensing the users every move, eventually that will become public data. Journalists face an ethical dilemma in waiting for the access to some of the data personal sensors collect, but based off recent trends of companies actively publishing the data it collects from its products, journalists need to only wait for the information to become public. For example, Facebook publishes facts it collects about its users, and Lily Bui demonstrated that sensor companies like Jawbone released a chart on sleep patterns after an earthquake in California. I don’t believe that it’s ethical for journalists themselves to go after the personal sensor data in products. However, if they were able to crowd source the information through a joint effort with the community or make it known that they were collecting the data— like Bui’s other example with the biking route app— then that helps contribute to the importance and future impact of sensor journalism.
Another challenge that sensor journalism faces is that depending on the device and technology used as the censor, there could be no standard or certified way of gathering the data. Certain tools already common, like ones for measuring weather, have a standard use, measure, and readings, but newer technology poses the risk of skewing the data if a collective of sensors aren’t calibrated correctly. This can only be solved in time with more use of certain tools and waiting for companies to agree upon specific tools that journalists will use. Without a proper seal of approval between at least a handful of reliable sources, some sensors and its data could be dismissed as faulty or inaccurate.
Overall, I look forward to incorporating more sensor journalism into the newsroom and journalism’s digital future. The more training upcoming reports get in how to use sensors and read the data gathered, the more of an expectation is will become in careers. Stories will gain an extra layer by adding on data collected by sensors because it’s more focused and personal than general numbers collected through polls or other vast troves of complicated research. Instead of hearing about how poisoned the water in Flint, Michigan is for the citizens, journalists can go with relatively inexpensive sensors and actually compare and quantify the pollution in Flint versus big cities like New York City, or other suffering neighborhoods in America. Stories now can go more in-depth and specific to a certain topic on their own, instead of relying on larger research that could take a much longer time to publish or be weighed down by bias. Sensor journalism gives stories a defined point of view on much broader topics.
Journalists now need to become more comfortable and open to learning how to work with sensor and incorporate that data into their stories. If having such a fine focal point and specificity benefits a story, then reporters need to know how to work the technology that makes those points possible. There’s already a high level of standards for upcoming journalists and their expected skill set, but adding a few skills in understanding sensors and data can’t hurt. In the future, more technology will introduce sensors not only to the media industry, but also to the masses. Wearables and drones are only a small part of what’s available, and journalists need to keep up with the curve— if not beat it— to truly reflect the news of our time.