Digital Labor

Michael Schober

person  

Michael Schober is a researcher who studies how people understand and misunderstand each other in face to face and mediated (phone, texting, videochat, Twitter) interactions. For a while he and his collaborators have been interested in the interactions at the core of large-scale social measurement—survey interviews—-and how the landscape of social measurement for the official statistics that shape social policies (e.g., unemployment, health, housing, etc.) is changing. (For example, he and Fred Conrad edited a Wiley volume called Envisioning the Survey Interview of the Future, bringing together communication researchers and survey methodologists to think through how our quickly changing communication landscape may affect participants’ experience as well as the quality and trustworthiness of data from survey interviews.).


Mis-/Understanding in F2F & Mediated Interactions
I’m a researcher who studies how people understand and misunderstand each other in face to face and mediated (phone, texting, video chat, Twitter) interactions. For a while my collaborators and I have been interested in the interactions at the core of large-scale social measurement—survey interviews—-and how the landscape of social measurement for the official statistics that shape social policies (e.g., unemployment, health, housing, etc.) is changing. (For example, Fred Conrad and I edited a Wiley volume called Envisioning the Survey Interview of the Future, bringing together communication researchers and survey methodologists to think through how our quickly changing communication landscape may affect participants’ experience as well as the quality and trustworthiness of data from survey interviews.).

More recently we have become fascinated with claims that mining data from Internet searches and social media streams might be able to augment or even replace the (expensive and burdensome) survey interviewing that forms the basis of official statistics. As I see it, the science has not yet been done that would let us know how feasible this really is, and of course there are hugely complicated questions about how survey respondents’ time and effort—and the time and effort of social media posters—are and should be valued. There are also quite complicated questions about how societies should think about what survey respondents and social media posters are consenting to with regards to the data they are producing, and the social values reflected in asking members of the public to provide anonymized data that they consent to provide for the social good vs. using “found” data that social media posters and search engine users may or may not know they have made public.

I see these issues as extremely thorny and multilayered, and they involve many players with different agendas (e.g., labor force or public opinion measurement for informing social policy decision-making is a really different enterprise than for-profit market research or political polling). I have not yet been involved in many of the conversations and perspectives represented at this conference, but I know they form an important piece of the puzzle; I’ll be extremely interested to learn from the discussions.

 
Search, Data Flows, & Vertical Extraction
Fri, November 14
02:15 PM - 04:45 PM