<![CDATA[Abstrak. Perkembangan big data dan Artificial Intelligence telah mengubah paradigma produksi pengetahuan ilmiah, khususnya dalam ilmu sosial dan komunikasi. Penelitian ini bertujuan untuk mengkaji posisi big data dan AI dalam produksi pengetahuan ilmiah, tantangan metodologis penggunaannya dalam penelitian sosial, serta peran refleksivitas peneliti dalam menjaga validitas pengetahuan ilmiah. Metode yang digunakan adalah kualitatif dengan pendekatan Systematic Literature Review (SLR). Hasil penelitian menunjukkan bahwa integrasi big data dan Artificial Intelligence membuka peluang analisis sosial yang lebih luas, real-time, dan beragam, namun di sisi lain menimbulkan persoalan serius terkait bias algoritma, etika penelitian, serta tantangan validitas dan representativitas data. Refleksivitas peneliti menjadi kunci dalam memastikan pengetahuan ilmiah yang dihasilkan tetap valid, bermakna, dan kontekstual di era digital. Big data menghadirkan isu privasi, keadilan, serta keberpihakan data, sedangkan Artificial Intelligence memunculkan pertanyaan tentang transparansi, akuntabilitas, dan tanggung jawab peneliti terhadap makna yang dihasilkan sistem komputasional. Hasil penelitian ini juga menunjukan bahwa keseimbangan antara kecanggihan yang bersifat teknis dan kepekaan epistemologis menjadi syarat utama agar big data dan Artificial Intelligence dapat bermafaat sebagai instrumen penguatan pengetahuan ilmiah. Dengan demikian, penelitian ini menegaskan pentingnya kesadaran etika dan refleksivitas metodologis bagi peneliti di bidang sosial untuk menjaga integritas penelitian dan relevansi sosial pengetahuan ilmiah di tengah perkembangan teknologi data yang semakin kompleks ini.Abstract. The development of big data and Artificial Intelligence has transformed the paradigm of scientific knowledge production, particularly in the fields of social sciences and communication. This study aims to examine the position of big data and Artificial Intelligence in scientific knowledge production, the methodological challenges of their use in social research, and the role of researcher reflexivity in maintaining the validity of scientific knowledge. The method employed is qualitative, using a Systematic Literature Review (SLR). The results show that the integration of big data and Artificial Intelligence provides opportunities for broader, real time, and more diverse social analyses however, it also raises serious issues related to algorithmic bias, research ethics, and challenges to data validity and representativeness. Researcher reflexivity becomes a key factor in ensuring that the scientific knowledge produced remains valid, meaningful, and contextual in the digital era. Big data introduces issues of privacy, fairness, and data partisanship, while Artificial Intelligence raises questions of transparency, accountability, and the researcher’s responsibility for the meanings produced by computational systems. The findings also indicate that balancing technical sophistication and epistemological sensitivity is a crucial requirement for big data and Artificial Intelligence to serve as effective instruments for strengthening scientific knowledge. Thus, this study emphasizes the importance of ethical awareness and methodological reflexivity among social researchers to maintain research integrity and the social relevance of scientific knowledge amid the increasing complexity of data driven technologies.]]>
