22
R. Dette
Challenge 6: Increasing inequality and power imbalances
Even those technology implementations that seem seamless and successful can entail
problematic power dynamics that disadvantage aid recipients or lead to long-term
negative consequences (Jacobsen 2015; Toyama 2015). Technologies affect their
surroundings, which can be detrimental in contexts of discrepancy and donor–recipient relationships. In academia, technology has been critiqued as ‘deepening the
processes of creating inequalities’ as those in power who introduce new tools risk
undermine the engagement of those in the periphery (Santos 2000).
Challenge 7: Dependence on non-humanitarian actors and sectors
Technology-enabled aid attracts and actively depends on new actors to the field,
including computer experts and for-profit businesses. Some of these may not adhere
to, or even contradict, the humanitarian principles of neutrality, independence and
impartiality (Raymond and Card 2015b). Increasing dependence on the services and
expertise of these new actors can compromise the values and objectives of aid efforts
(Duffield 2014).
Challenge 8: Double-standards and hypocrisy compromise humanitarian principles
Some controversy has risen where aid efforts relied on tools that were not considered
ethical or adequate in other contexts (Hosein and Nyst 2013; Jacobsen 2015: 10).
In Europe, for example, public backlash led policymakers to halt the integration of
advanced biometrics in citizen registration. In contrast, this is widespread and praised
for refugee registration (Hosein and Nyst 2013: 8; Jacobsen 2015). Aid actors often
do not have regulatory safeguards for technologies (Duffield 2014: 3). Unless crisisaffected communities understand and object to the risks, subjecting them to digital
technologies can introduce new dependencies and inequalities.
2.4 Mitigation Measures
Risk awareness aids responsibility
Oftentimes, the most successful tactics to minimize technology harm are not technical
at all, but behavioural such as self-imposed limitations on what information to collect
and transmit digitally (Steets et al. 2016; Antin et al. 2014; Internews 2015). When
the name or age or even gender of a person is not critically necessary for household
nutrition surveys, it may be better not to record it. Similarly, it is good to aggregate and
generalize information at the first stage of data collection to prevent reidentification
that could lead to harm or problems for individuals (de Montjoye et al. 2014). Security
audits can help identify who has access to aid data and how easily staff accounts and
emails could be compromised (Shostack 2014; Internews 2015). It is also good to
introduce privacy-conscious technology and ‘free and open source software (FOSS).’
These tools run on code that is published and can be reviewed by anyone, such that
R. Dette
Challenge 6: Increasing inequality and power imbalances
Even those technology implementations that seem seamless and successful can entail
problematic power dynamics that disadvantage aid recipients or lead to long-term
negative consequences (Jacobsen 2015; Toyama 2015). Technologies affect their
surroundings, which can be detrimental in contexts of discrepancy and donor–recipient relationships. In academia, technology has been critiqued as ‘deepening the
processes of creating inequalities’ as those in power who introduce new tools risk
undermine the engagement of those in the periphery (Santos 2000).
Challenge 7: Dependence on non-humanitarian actors and sectors
Technology-enabled aid attracts and actively depends on new actors to the field,
including computer experts and for-profit businesses. Some of these may not adhere
to, or even contradict, the humanitarian principles of neutrality, independence and
impartiality (Raymond and Card 2015b). Increasing dependence on the services and
expertise of these new actors can compromise the values and objectives of aid efforts
(Duffield 2014).
Challenge 8: Double-standards and hypocrisy compromise humanitarian principles
Some controversy has risen where aid efforts relied on tools that were not considered
ethical or adequate in other contexts (Hosein and Nyst 2013; Jacobsen 2015: 10).
In Europe, for example, public backlash led policymakers to halt the integration of
advanced biometrics in citizen registration. In contrast, this is widespread and praised
for refugee registration (Hosein and Nyst 2013: 8; Jacobsen 2015). Aid actors often
do not have regulatory safeguards for technologies (Duffield 2014: 3). Unless crisisaffected communities understand and object to the risks, subjecting them to digital
technologies can introduce new dependencies and inequalities.
2.4 Mitigation Measures
Risk awareness aids responsibility
Oftentimes, the most successful tactics to minimize technology harm are not technical
at all, but behavioural such as self-imposed limitations on what information to collect
and transmit digitally (Steets et al. 2016; Antin et al. 2014; Internews 2015). When
the name or age or even gender of a person is not critically necessary for household
nutrition surveys, it may be better not to record it. Similarly, it is good to aggregate and
generalize information at the first stage of data collection to prevent reidentification
that could lead to harm or problems for individuals (de Montjoye et al. 2014). Security
audits can help identify who has access to aid data and how easily staff accounts and
emails could be compromised (Shostack 2014; Internews 2015). It is also good to
introduce privacy-conscious technology and ‘free and open source software (FOSS).’
These tools run on code that is published and can be reviewed by anyone, such that