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2019 ITU Kaleidoscope Academic Conference




           Secondly,  while  deriving  relevant  insights  from  health   justice. As noted by Taylor [27], the ends of various data
           informatics  primarily  ensues  through  the  individual’s   justice formulations is to achieve both specific outcomes and
           engagement  with  their  data,  research  has  found  that   also  specific  configurations  of  the  associated  data
           individuals also engage in sharing of their data with others   assemblages towards the achievement of those outcomes: in
           for sense-making purposes  [20]–[22]. Thus, the collection   the  case  of  Johnson’s  [29]  framework,  the  end  goal  is
           and  use  of  data  by  individuals  also  comprise  the  social   embedding anti-discrimination principles and features in the
           dimension.                                         design of database systems; for Heeks and Renken [28], the
                                                              focus is on data distribution in a way that achieves fair access,
           Thirdly,  personal  health  data  also  gets  shared  to  support   participation and representation; and lastly Dencik et al. [30]
           external pursuits such as biomedical research, where data on   are interested in the means of limiting data collection and
           health profiles, cohort data, as well as physical activity data   distribution in contexts of surveillance capitalism.
           can  support  projects  such  as  the  Global  Alliance  for
           Genomics  and  Health  [23].  The  sharing  of  data  in  this   In the work of Mortier et al. [31], in which they formalize
           context  can  be  motivated  from  the  perspective  of  the   the notion of human-data interaction (HDI), they explicate
           Universal Declaration of Human Rights, which recognizes   the interaction between humans and data systems in a way
           the “right of everyone to share in scientific advancement and   that places “the human at the center of the flows of data, and
           its benefits” [23]. Thus sharing of data can be towards these   providing  mechanisms  for  citizens  to  interact  with  these
           goals, which are associated with citizen science, as well as   systems and data explicitly”. While the formulation of HDI
           increased  participation  and  engagement  in  advancing   is not explicitly from a social justice nor ethics perspective,
           scientific research [24].                          it gives recognition to the fact that the underlying issues in
                                                              HDI  sit  at  the  intersection  of  “the  various  disciplines
           In all these cases of external sharing of personal health data,   including   computer   science,   statistics,   sociology,
           there  is,  however,  the  persistent  risk  of  “Googlization  of   psychology,  and  behavioral  economics”  [31].  Further,  it
           health  research,”  which  is  associated  with  the  increasing   gives  recognition  to  the  fact  that  human-data  interaction
           data-driven  encroachment  and  involvement  of  the  major   happens in the context of complex data ecosystems, which
           technology  companies  within  the  health  and  biomedical   are  constitutive  of  the  global  data-driven  society.  In  this
           sectors [17]. The potential benefits of the application of these   complex interaction of different stakeholders with different
           technological  developments  on  issues  of  health  and   capabilities,  interests  and  agendas,  there  is  an  ongoing
           wellbeing are immense; they include major improvements in   contestation  for  the  voices  of  humans  and  human-centric
           disease  diagnosis,  improving  access  to  services  through   perspectives not to be marginalized and excluded. Some of
           telehealth  solutions  and  advancing  the  developmental   the powerful and key actants within the health informatics
           aspirations  of  achieving  universal  health  coverage.  The   ecosystem  include  health-service  providers,  the  health
           challenges, however, are equally immense and are associated   industry,  as  well  as  the  non-human  technology-related
           not only with adverse health outcomes but also with negative   actants, as has been highlighted by Sharon [17] regarding the
           sociocultural and economic consequences. These challenges   influence  of  the  technology  companies  in  the  health  data
           are related to issues of bias, privacy [25], informed consent,   research. Further highlighting the complexity, Morley and
           context  transgressions  [26],  health  data  commoditization,   Floridi [16] offer a poignant critique of the techno-utopian
           new  power  asymmetries  and  discriminations  [27],  data   formulation of mHealth technologies as empowering devices
           valorization  and  benefit-sharing,  and  the  importation  of   and warn against the risk of medical paternalism. Privileging
           digital capitalism practices into the health realm [17].   the  position  of  the  humans  within  the  health  informatics
                                                              ecosystem, as has been done in the HDI framework, allows
             3.  DATA JUSTICE IN HEALTH INFORMATICS           for the critical investigation of issues towards an explicit goal
                                                              of  enhancing  the  substantive  freedoms  of  individuals  to
           Numerous definitions of “data justice” have been advanced   achieve their desired health outcomes and enhancing their
           in the literature, which fundamentally recognize the social   health capabilities [32].
           justice dynamics and impacts of the use of data in society.
           Taylor [27] defines data justice as the “fairness in the way   In this paper, the HDI framework has been adopted to frame
           people are made visible, represented and treated as a result   the  discussion  of  the  outworking  of  data  justice  in  health
           of the production of digital data.” In her formulation of data   informatics systems. The paper expands on the imperatives
           justice  she  decomposes  the  concept  to  three  notions  of   of  legibility,  agency  and  negotiability  to  identify  specific
           (in)visibility – associated with access to representation, and   considerations  and  non-functional  requirements  to  inform
           informational  privacy;  (dis)engagement  with  technology,   the design of health informatics systems.
           which  is  linked  to  sharing  in  data  benefits  as  well  as
           autonomy in data choices; and to antidiscrimination, which   3.1   Legibility
           is linked with the ability to challenge bias and preventing
           discrimination. Heeks and Renken [28] define data justice   Legibility  is  summarily  defined  as  “being  able  to  be
           simply  as  “the  primary  ethical  standard  by  which  data-  understood  by  people  they  concern,  as  a  precursor  to
           related  resources,  processes  and  structures  are  evaluated.”   exercising their agency” [31]. This is defined with regards to
           They,  however,  expand  this  to  formulate  three  notions  of   the data, as far as individuals understanding what data has
           instrumental,  procedural  and distributive  rights-based  data   been collected, how it is being used, by whom, and when it




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