Algorithmic Curation and Cultural Memory: Ethical Implications of AI-Driven Archiving in Digital Humanities Projects
DOI:
https://doi.org/10.21590/ijtmh20230904022Keywords:
Algorithmic curation; Cultural memory; Digital humanities; AI ethics; Digital archives; Representational harm; Archival governanceAbstract
Digital humanities projects increasingly rely on machine learning pipelines to select, classify, describe, and surface cultural materials at scales that exceed human archival capacity. While algorithmic curation promises efficiency and discoverability, it also transfers consequential judgments about what a society remembers, and how, from accountable human institutions to opaque computational systems. This paper develops a conceptual framework for analysing the ethical implications of AI-driven archiving along four dimensions: selection (what enters the archive), description (how items are represented), retrieval (what is surfaced to whom), and preservation (what persists over time). Drawing on cultural memory theory and the ethics of information, we argue that algorithmic curation does not merely accelerate archival work but restructures the memory function itself, introducing distinctive risks of representational harm, silent exclusion, contextual flattening, and memory drift. We propose a set of governance principles — provenance transparency, contestability, plural curation, and periodic human re-review — and map them to concrete design interventions for digital humanities infrastructure. The paper contributes a vocabulary and an evaluative checklist that project teams, funders, and cultural institutions can use when deciding where, and under what safeguards, algorithmic curation is appropriate.
References
1. Jaiswal, I. A. (2023). Multilingual and culturally adaptive AI models for global education platforms. International Journal for Research in Education (IJRE), 12(9), 17–27. https://doi.org/10.63345/ijre.v12.i9.1
2. M. S. Prashanth, R. Aluvalu, and M. V. V. Kantipudi, “Enhancing Health Product Traceability on the Blockchain: A Novel Approach for Supply Chain Management Inspection to AI,” EAI Endorsed Transactions on Pervasive Health & Technology, vol. 10, no. 1, 2024.
3. H. K. Jani, M. V. V. Prasad Kantipudi, G. Nagababu, D. Prajapati, and S. S. Kachhwaha, “Simultaneity of Wind and Solar Energy: A Spatio-Temporal Analysis to Delineate the Plausible Regions to Harness,” Sustainable Energy Technologies and Assessments, vol. 53, Art. no. 102665, 2022
4. Jaiswal, I. A. (2022). Natural language processing for security policy and log analysis. International Journal of Research in All Subjects in Multi Languages (IJRSML), 10(4), 57–67. https://doi.org/10.63345/ijrsml.v10.i4.1
5. Khan, S. (2019). Sales force security compliance: An in-depth study of GDPR, HIPAA, and PCI-DSS enforcement in cloud-based CRM systems and their implications for global enterprises. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 8(9), 2211–2219. https://doi.org/10.15662/IJAREEIE.2019.0809010
6. S. Choudhary, C. H. Kandikattu, S. Kumar, M. V. V. P. Kantipudi, and M. Kumar, “Enhancing cybersecurity through combined convolutional neural network-gated recurrent unit approach for distributed denial of service attack detection,” in Proceedings of the 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR), pp. 1–6, 2024.
7. S. Rani, D. Ghai, and S. Kumar, “Reconstruction of wire frame model of complex images using syntactic pattern recognition,” in IET Conference Proceedings CP791, vol. 2021, no. 11, pp. 8–13, 2021.
8. Swathi, S. Kumar, S. Rani, A. Jain, and R. K. M. V. N. M., “Emotion classification using feature extraction of facial expression,” in Proceedings of the 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS), pp. 283–288, 2022.
9. S. Choudhary, S. Kumar, S. Gowroju, M. Gulhane, and R. Sri Lakshmi, Eds., Genomics at the Nexus of AI, Computer Vision, and Machine Learning. Hoboken, NJ, USA: John Wiley & Sons, 2024.
10. S. Kumar, S. Choudhary, S. Gowroju, and A. Bhola, “Convolutional neural network approach for multimodal biometric recognition system for banking sector on fusion of face and finger,” in Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, pp. 251–267, 2023.
11. S. Choudhary, S. Kumar, M. Gulhane, and M. Kumar, “Secured automated certificate creation based on multimodal biometric verification,” in Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision, pp. 269–281, 2023.
12. Jaiswal, I. A. (2024). AI-powered observability and incident prediction in distributed enterprise platforms. Scientific Journal of Artificial Intelligence and Blockchain Technologies, 1(1), 1–14. https://doi.org/10.63345/sjaibt.v1.i1.201
13. S. Choudhary, C. H. Kandikattu, S. Kumar, M. V. V. P. Kantipudi, and M. Kumar, “Enhancing cybersecurity through combined convolutional neural network-gated recurrent unit approach for distributed denial of service attack detection,” in Proceedings of the 2024 1st International Conference on Innovative Engineering Sciences and Technological Research (ICIESTR), pp. 1–6, 2024.
14. Jaiswal, I. A. (2023). High-Performance AI-Augmented Content Management Systems for Distributed Clouds. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 2 (2), 90–97. Retrieved from https://ijmirm. com/index. php/ijmirm/article/view, 243.
15. Khan, S. (2018). The role of zero-trust models in database security: Eliminating implicit trust and enforcing continuous verification in enterprise data access systems. International Journal of Research in Electronics and Computer Engineering, 6(1), 1622–1628.
16. Jaiswal, I. A. (2024). Self-healing REST services using artificial intelligence in multi-cloud environments. Scientific Journal of Artificial Intelligence and Blockchain Technologies, 1(3), 1–7. https://doi.org/10.63345/sjaibt.v1.i3.201
17. V. Saini, A. Jain, Anurag, and M. V. V. Prasad Kantipudi, “An Efficient Approach for Improving the Performance of Autonomous Vehicle Using Advanced Computer Vision,” in International Conference on Soft Computing and Pattern Recognition, Cham, Switzerland: Springer Nature Switzerland, 2023, pp. 164–174.
18. Khan, S. (2017). The role of privacy-preserving techniques in database security: Secure multi-party computation, differential privacy, and homomorphic encryption. The Research Journal, 3(4), 29–35.
19. Khan, S. (2016). A study of data provenance and integrity in database security: Ensuring authenticity, non-repudiation, and accountability in data lifecycle management. International Journal of Research in Electronics and Computer Engineering, 4(3), 180–186.
20. Rallabandi, B. R. (2020). MEC-native 5G systems: Orchestration algorithms for ultra-low latency cloud-edge integration. International Journal of Intelligent Systems and Applications in Engineering, 8(4), 398–408. https://ijisae.org/index.php/IJISAE/article/view/7889
21. Rallabandi, B. R. (2018). Joint deployment and operational energy optimization in heterogeneous cellular networks under traffic variability. International Journal of Communication Networks and Information Security, 10(3), 638–647. https://ijcnis.org/index.php/ijcnis/article/view/8604
22. Cherladine, K., Rallabandi, B. R., Goel, A., Kaushik, K., Dhillon, A., & Soni, M. (2025). Generative adversarial defense models for simulated cyberattack scenarios in virtual networks. In 2025 International Conference on Digital Innovations for Sustainable Solutions (ICDISS) (pp. 1–6). IEEE. https://doi.org/10.1109/ICDISS68238.2025.11320686
23. C. H. Neetha and M. P. Kantipudi, “Adaptive Edge-Based Bilinear Interpolation for Smart Healthcare,” in IET Conference Proceedings CP824, vol. 2022, no. 26, Stevenage, U.K.: The Institution of Engineering and Technology (IET), 2022, pp. 7–13.
24. R. Aluvalu, R. Venkatachalam, V. Uma Maheswari, R. J. Anandhi, M. V. V. Kantipudi, and S. Prashanth Mallellu, “IWHO-Based Cluster Head Selection for Vehicle-to-Vehicle Communication in Intelligent Transport System,” International Journal of Transport Development and Integration, vol. 8, no. 2, pp. 154–166, 2024
25. S. Velamuri, S. K. Sudabattula, M. V. V. Prasad Kantipudi, and N. Prabaharan, “Q-Learning Based Commercial Electric Vehicles Scheduling in a Renewable Energy Dominant Distribution Systems,” Electric Power Components and Systems, pp. 1–14, 2023
26. Singh, M., Rallabandi, B., Gattupalli, K. K., & Sai Medarametla, M. (2025). Autonomous private 5G field area networks: Achieving secure, scalable, and self-healing smart grid communications. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448712
27. Desai, A. B., Rallabandi, B., Gattupalli, K. K., & Medarametla, M. S. (2025). Agentic AI for rural connectivity and spectrum-aware networks to power smart agriculture ecosystems. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448879
28. Goyal, S., Rallabandi, B., Gattupalli, K. K., & Medarametla, M. S. (2025). Digital twin-enabled context-aware networks: Enhancing smart grid resilience through predictive intelligence. In 2025 2nd International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT) (pp. 1–6). IEEE. https://doi.org/10.1109/ICRTEECT67512.2025.11448880
29. Tripathi, N., Gattupalli, K. K., Rallabandi, B., & Medarametla, M. S. (2025). AI-native Cloud-RAN orchestration for enterprise private 5G using digital twin models. In 2025 1st IEEE Uttar Pradesh Section Women in Engineering International Conference on Electrical Electronics and Computer Engineering (UPWIECON) (pp. 851–857). IEEE. https://doi.org/10.1109/UPWIECON67212.2025.11390348
30. Goyal, S., Gattupalli, K. K., Rallabandi, B., & Medarametla, M. S. (2025). Integrating terrestrial and non-terrestrial networks for reliable rural coverage in agriculture and smart grids. In 2025 1st IEEE Uttar Pradesh Section Women in Engineering International Conference on Electrical Electronics and Computer Engineering (UPWIECON) (pp. 846–850). IEEE. https://doi.org/10.1109/UPWIECON67212.2025.11390331
31. N. Pachauri, V. Suresh, M. V. V. Prasad Kantipudi, R. Alkanhel, and H. A. Abdallah, “Multi-Drug Scheduling for Chemotherapy Using Fractional Order Internal Model Controller,” Mathematics, vol. 11, no. 8, Art. no. 1779, 2023,
32. M. V. V. Prasad Kantipudi, S. Vemuri, N. S. Pradeep Kumar, S. Sreenath Kashyap, and S. Eslamian, “Proposing Model for Water Quality Analysis Based on Hyperspectral Remote Sensor Data,” in Handbook of Hydroinformatics, Elsevier, 2023, pp. 317–324.
33. Rana, M., Srinivas, S., Jamili, L. K., Jaiswal, I. A., Nakka, S., & Kasetti, S. (2025, May). Real-Time Monitoring and Prediction of Blood Sugar Levels in Diabetic Patients with Functional Models. In 2025 International Conference on Engineering, Technology & Management (ICETM) (pp. 1-6). IEEE.
34. Jaiswal, I. A. (2023). Intelligent Cybersecurity Framework for Large-Scale RESTful Service Architectures. International Journal of Research Radicals in Multidisciplinary Fields, ISSN: 2960-043X, 2 (1), 178–184. Retrieved from https://www. researchradicals. com/index. php/rr/article/view, 252.
