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Contribution short abstract:

This study examines AI's application in Turkey's leading NGOs, highlighting the challenges in data set expansion and open access amidst Big Tech and government policies. Initial findings suggest NGOs prioritize data expansion over bias, navigating restrictions to responsibly grow data sets.

Contribution long abstract:

I explore the application of AI in the context of Turkey's leading NGOs, informed by the material-colonial aspects of labor and data extraction and the epistemic practices underlying AI development. This study aims to illustrate how AI's usage in local settings, particularly among these NGOs, can differ significantly from global AI discussions. A key observation is the NGOs' focus on expanding data sets rather than addressing data bias, necessitating open access from public entities that are often reluctant to provide it. This challenge requires innovative strategies to expand data sets responsibly and accountably.

Additionally, the research highlights the critical issue of data accessibility, emphasizing the ideological implications of keeping data open and free. This raises the question of whether organizations should use their data for competitive growth or maintain it for the common good. A notable gap is identified in the availability of Turkish language AI applications and localized databases despite ongoing efforts in Turkish language processing. This indicates a broader issue in localized data processing capabilities.

The study also addresses the complex relationship between Big Tech, civil society, and public policies, with Big Tech platforms seeking to expand their market while aligning with government AI policies. This may lead to tensions with civil society. Overall, these findings contribute to understanding the unique challenges and dynamics at play in the local application of AI technology.