Hilje Anna Ida Hudig

While the use of artificial intelligence (AI) for sustainable development is growing at a rapid pace, recent studies show that the way in which AI systems are designed and deployed poses threats to sustainable AI. The current dynamics of this industry, driven by the mantra ‘the more data the better’, dictate the extraction of data from human lives. Consequently, power asymmetriesariseor amplifybetween those who possessand control AI systems and those fromwhom the data areextracted(‘data subjects’).These mechanisms pose significant threats,particularlywhen manifestedinthe context of low-income countries (LICs). The literature suggeststhat there is a need for research into a different possible paradigm in the data business, as well as for approaches that positionthe data subjectsat the heart of the company.

This research exploresthe approaches of businesses that positionthose who serve as data sources as a centralstakeholder of their business: ‘user-centricbusinesses’.Case studies were performed to examinethepotentialof theseapproaches to address the concerns of the unfolding dynamics of the data industry for development in LICs.Informed bybusiness model theories, a framework was designed to systematically capture the contexts and approaches ofuser-centric businesses, and to guide interviews withfounders andemployees.Within-and cross-case analyses revealedthree themes: engagement(direct social value return), participation(indirect social value return),and self-reflectionacrossthe business model approaches.

Although direct social value returns – such as using data primarily for understandingpeople’s contexts and views, providing possession or controlover data, and non-identifiability–holdpotentialto contradictthe extractive logicof data markets, the data suggest that a tensionpersistsbetweendelivering services to customers and returning social valueto the datasubjects.Moreover,theperception of individuals as to whethersocial value returns truly compensate for extractionremains unclear.Furthermore,thisstudy revealsthatforms of ownershipover dataandparticipationpracticescan provide opportunities foragency and empowerment to data subjects,but challenges remaininbuildingrobustand reliablesystems for offering possession and privacyto individuals. Recommendations aremade toresearchers, practitioners and policy makersfor driving changetowards more inclusive and sustainable AI.