Building Values into the Design of Pervasive Mobile Technologies

Corporations, governments, and individuals can increasingly collect new forms of personal data using pervasive technologies such as mobile tablets and phones. These always-on, always-present devices carried by billions can capture and transmit users’ location, images, motion, and user input. Mobile technologies could become a platform to document community needs and advocate for civic change, to understand personal habits and routines, or to document health problems and manage chronic illness. Simultaneously, new forms of data collection software utilize techniques traditionally employed by tools of surveillance: granular data gathering, sophisticated modeling, and inferences about a personal behavior and attributes.There is a shifting and permeable boundary between data collection for individual or social goals, and corporate or government surveillance. This boundary invokes social values in design: the features, principles, or ethics we collectively value in the design of data collection technologies. Because technology regulation is often years behind the rate of innovation, this question is often answered, consciously or un-, by engineering teams.This dissertation studies an influential engineering laboratory working in participatory sensing, a form of personal data collection utilizing pervasive mobile devices. The dissertation employs ethnographic methods to examine design practices and agents that promote social values, and particularly anti-surveillance values – privacy, equity, consent, and forgetting – in design. The multi-year study of sensing development reveals how such abstract social values were built into concrete technological features.Anti-surveillance values became material as the design team built consensus around values such as privacy, consent, equity, and forgetting; and then translated those values into technological features. This process was enabled by values levers: practices that opened new conversations about social values, and encouraged consensus around those values as design criteria. While literature on values in design has previously suggested that values help construct the day-to-day work of design, my dissertation illustrates that the opposite is also true: the routinized practices of design work shape the values incorporated into new technologies. If anti-surveillance values such as privacy, consent, equity and forgetting are to be materialized in the design of pervasive sensing technologies, laboratories must be structured to encourage values levers, which facilitate and bolster the process of building values into technology

Building Values into the Design of Pervasive Mobile Technologies

Corporations, governments, and individuals can increasingly collect new forms of personal data using pervasive technologies such as mobile tablets and phones. These always-on, always-present devices carried by billions can capture and transmit users’ location, images, motion, and user input. Mobile technologies could become a platform to document community needs and advocate for civic change, to understand personal habits and routines, or to document health problems and manage chronic illness. Simultaneously, new forms of data collection software utilize techniques traditionally employed by tools of surveillance: granular data gathering, sophisticated modeling, and inferences about a personal behavior and attributes.There is a shifting and permeable boundary between data collection for individual or social goals, and corporate or government surveillance. This boundary invokes social values in design: the features, principles, or ethics we collectively value in the design of data collection technologies. Because technology regulation is often years behind the rate of innovation, this question is often answered, consciously or un-, by engineering teams.This dissertation studies an influential engineering laboratory working in participatory sensing, a form of personal data collection utilizing pervasive mobile devices. The dissertation employs ethnographic methods to examine design practices and agents that promote social values, and particularly anti-surveillance values – privacy, equity, consent, and forgetting – in design. The multi-year study of sensing development reveals how such abstract social values were built into concrete technological features.Anti-surveillance values became material as the design team built consensus around values such as privacy, consent, equity, and forgetting; and then translated those values into technological features. This process was enabled by values levers: practices that opened new conversations about social values, and encouraged consensus around those values as design criteria. While literature on values in design has previously suggested that values help construct the day-to-day work of design, my dissertation illustrates that the opposite is also true: the routinized practices of design work shape the values incorporated into new technologies. If anti-surveillance values such as privacy, consent, equity and forgetting are to be materialized in the design of pervasive sensing technologies, laboratories must be structured to encourage values levers, which facilitate and bolster the process of building values into technology

Qu’est-ce que le travail scientifique des données ?

Puisant ses analyses et ses exemples dans des champs scientifiques variés, cet ouvrage (dont l’original est paru en 2015 chez MIT Press) offre une étude inédite des utilisations des données au sein des infrastructures de la connaissance – utilisations qui varient largement d’une discipline à l’autre. Bien que le big data ait régulièrement les honneurs de la presse des deux côtés de l’Atlantique, Christine L. Borgman met en évidence qu’il vaut mieux disposer des bonnes données qu’en avoir beaucoup. Elle montre également que les little data peuvent s’avérer aussi précieuses que les big data, et, que, dans bien des cas, il n’y a aucune donnée, parce que les informations pertinentes n’existent pas, sont introuvables ou sont indisponibles… Au travers d’études de cas pratiques issus d’horizons divers, Christine L. Borgman met aussi en lumière que les données n’ont ni valeur ni signification isolément : elles s’inscrivent au sein d’une infrastructure de la connaissance, c’est-à-dire d’un écosystème de personnes, de pratiques, de technologies, d’institutions, d’objets matériels et de relations. Pour l’autrice, gérer les données et les exploiter sur le long terme requiert ainsi des investissements massifs dans ces infrastructures de la connaissance. L’avenir de la recherche, dans un monde en réseau, en dépend

Qu’est-ce que le travail scientifique des données ?

Puisant ses analyses et ses exemples dans des champs scientifiques variés, cet ouvrage (dont l’original est paru en 2015 chez MIT Press) offre une étude inédite des utilisations des données au sein des infrastructures de la connaissance – utilisations qui varient largement d’une discipline à l’autre. Bien que le big data ait régulièrement les honneurs de la presse des deux côtés de l’Atlantique, Christine L. Borgman met en évidence qu’il vaut mieux disposer des bonnes données qu’en avoir beaucoup. Elle montre également que les little data peuvent s’avérer aussi précieuses que les big data, et, que, dans bien des cas, il n’y a aucune donnée, parce que les informations pertinentes n’existent pas, sont introuvables ou sont indisponibles… Au travers d’études de cas pratiques issus d’horizons divers, Christine L. Borgman met aussi en lumière que les données n’ont ni valeur ni signification isolément : elles s’inscrivent au sein d’une infrastructure de la connaissance, c’est-à-dire d’un écosystème de personnes, de pratiques, de technologies, d’institutions, d’objets matériels et de relations. Pour l’autrice, gérer les données et les exploiter sur le long terme requiert ainsi des investissements massifs dans ces infrastructures de la connaissance. L’avenir de la recherche, dans un monde en réseau, en dépend