All past and present journalists know that the media landscape is constantly evolving. With each development comes new opportunity, raising the same question: what does this mean for the future of journalism?
The internet provided challenges for legacy media companies, particularly those who were unwilling to adapt. At the same time, many web-based news companies and collaborative, information-focused blogs and sites were born in a new technological age. The Tow report on sensor journalism says, “for journalism, there is a special symmetry of demand and supply. Behind the computer-aided reporters and data savvy journalists have come a generation of programmer-journalists. They all compete for fresh data to include in their stories.”
As data journalism was introduced, some journalists incorporated data into stories in new ways and created databases of information which led to new discoveries. Others used data just as they had before, as a supplement that was now easier than ever to access. And some took off from the data journalism platform, creating news and information pieces based on data analysis. Just this week, Walt Hickey of Nate Silver’s FiveThirtyEight blog published an almost 100-percent accurate “Data Driven Guide to the Oscars,” using this model to predict who would win awards, based on previous awards they had won. Today, we are on the frontier of sensor journalism, an exciting prospect that introduces a DIY-aspect to the storytelling process. Not only is information is readily available, but data can be created and accumulated by journalists themselves, or sourced from the public.
At the same time, new media is a contextual thing. Twitter cannot be used as a tool in every story. Some data sets will only be misconstrued if shoved into stories that just don’t fit. Crowd-sourced information can prove a point in some cases and fall short in others. Every method to advance media and communication must be put up to journalistic standards and used within specific contexts, resulting either in brilliant conclusions or a mess of half-proven numbers and charts.
Lily Bui from MIT’s Media Lab shared some exciting examples of sensor journalism with us. We watched video of a drone flying over the nuclear site at Chernobyl, as an example of how drones can go where humans can’t to access information. She compared this to a project to for a DIY drone, created by Public Labs, that was used to take aerial photographs of Boston’s city hall. Bui mentioned a few projects that had been done by established media companies, for instance, a piece in the Sun Sentinel showing how journalists cracked down on speeding cops by using records of transponders in police vehicles passing through tolls, and then measuring how fast the officers traveled between two tolls. This piece seemed solid and proven, in addition to being very open about all the blood and guts (data sets and sources) that went into the process. In a very different example, Bui showed us WNYC’s Cicada Tracker, which invited the general public to track the emergence of cicada populations, using DIY sensor kits. WNYC trusted in the general public to successfully build and install their sensors, and then use and interpret them properly. They trusted everyone to tell the truth and hoped that nobody would abuse the system. It worked for a fun trend piece and effectively highlighted the collaborative aspects of sensor journalism, but because of the variables, it might be wholly ineffective to prove a point as a statistic in a more serious piece. As it says in the Tow report on sensor journalism, “Journalists considering whether to include sensor data in their own reporting may want to evaluate their story, their goals, and the potential data they need.” It’s all about context.
In our water conductivity workshop, we were able to test the conductivity of water samples we collected from locations ranging from a babbling brook in Holliston to dirty street snow in Mission Hill. Using our breadboards and coqui sensors, we tested to see what frequency each water sample would produce with an app from Public Labs. As Mystic River Watershed Executive Director Patrick Herron explained during his presentation, we were working with a lot of factors. He explained that water samples would be affected by temperature, the presence of inorganic dissolved solids such as chloride, nitrate, sulfate, and phosphate anions (ions that carry a negative charge) or sodium, magnesium, calcium, iron, and aluminum cations (ions that carry a positive charge). Our coquis were built using screws of different metals, screwed into a bottle cap at around the same distance apart. This meant there could be little differences in the conductivity, based on the separation of those screws. We didn’t regulate the water temperature, another factor which varied between samples. Our research and experimentation brought up further questions: Is it possible that sodium ions, only carrying a positive charge, would only flock to the positive end of the coqui? Could that affect the final result? How did the chunks of ice floating in some samples affect the frequency? and finally, could we take an experimental sensor (the coqui) and a week-old Public Labs online app and get a real, accurate and serious journalistic conclusion?
Beyond our specific questions about our project, sensor journalism brings up the larger question of ethics and privacy. According to the Tow report on sensor journalism, “Ethical Foundations of Privacy Use of sensors for data collection puts novel pressures on legal conceptions of privacy. We often premise privacy on the protection of personal space. We conceive of places where a person might have a reasonable expectation of privacy and punish intrusions into that space.” Bui introduced us to the idea of “sensing cities,” with light poles that can adjust to natural light, sense air quality and send alerts to those with asthma, streets and roads that could report their own damage, etc. According to this model, the same information that is available to the city council will be available to the public. An important part of this example is that individual users will not be tracked, and their privacy will be respected.
In class, we have discussed at length how various companies use data for advertising purposes, tracking users with their consent, but without their knowledge. Bui showed us an example of wearable technology device company Jawbone, which created a visualization that showed how an earthquake affected people sleeping in California. It seems very unlikely that each of these sleeping people had agreed to be a part of this specific study, yet by clicking “I agree” to mobile location services or a contract from the app, they were all used as data points. A counterpoint for the journalist might be that there are sensors on all of us anyway, and cellphone companies, Google, and various apps including social media, dating sites and rideshare services are already tracking our movements and our behavior. If we can’t beat ‘em, why not join them and use the data around us to make our world a better place?
Finally, it is important to remember that sensor journalism must pass the same ethical and moral tests any other piece would. Each project is placed within a context, and each journalism must act the ombudsman for their data project, (sometimes in addition to another newsroom ombudsman). The Tow report on sensor journalism describes the caution with which we must approach any new frontier:
"Josh Stearns wrote the following words, which seem like the perfect description of the current evolutionary state of laws and ethics in journalistic sensing, and a prescription for how to proceed. “It is worth remembering that just as newsrooms are learning about the power and potential of sensors, so too are our communities. We are in the early stages of sensor technology, what Julie Steele of O’Reilly Media calls the precursor, the ancestor, to what will change our lives.’”