Measuring the Unseen Hand: Methodological Challenges in Quantifying the Welfare Effects of Algorithmic Persuasion

  • Unique Paper ID: 190655
  • Volume: 12
  • Issue: 8
  • PageNo: 3507-3514
  • Abstract:
  • In today's India, our lives are increasingly intertwined with the digital world. From shopping on Flipkart and Amazon to ordering food on Zomato and managing investments on platforms like Zerodha and Groww, powerful Artificial Intelligence (AI) systems are constantly working behind the scenes.[1] These algorithms learn our habits and "nudge" us toward certain choices through personalised recommendations and curated information a process known as algorithmic persuasion.[2] This technology promises unprecedented convenience and efficiency, but it also raises a critical question: Are these digital nudges truly improving our well-being, or do they primarily serve the commercial interests of the companies that deploy them? This paper provides a comprehensive methodological review of the profound challenges researchers face in quantifying the real-world welfare effects of these persuasive systems. We identify and elaborate on five core, interlocking challenges: (1) the fundamental difficulty in measuring consumer surplus, especially its non-monetary components; (2) the ambiguity in defining a credible counterfactual against which to evaluate sophisticated algorithmic systems; (3) the complexity of establishing robust causal inference in dynamic, endogenous digital environments; (4) the severe data access limitations and algorithmic opacity that impede independent research and audits; and (5) the difficulty of capturing long-term, dynamic, and heterogeneous effects across a diverse population. By examining these challenges, this paper aims to create a detailed methodological roadmap to better understand and shape India's burgeoning digital economy for the equitable benefit of all its citizens.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{190655,
        author = {Sharath Kumar M P and Dr V Sumathi},
        title = {Measuring the Unseen Hand: Methodological Challenges in Quantifying the Welfare Effects of Algorithmic Persuasion},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {3507-3514},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190655},
        abstract = {In today's India, our lives are increasingly intertwined with the digital world. From shopping on Flipkart and Amazon to ordering food on Zomato and managing investments on platforms like Zerodha and Groww, powerful Artificial Intelligence (AI) systems are constantly working behind the scenes.[1] These algorithms learn our habits and "nudge" us toward certain choices through personalised recommendations and curated information a process known as algorithmic persuasion.[2] This technology promises unprecedented convenience and efficiency, but it also raises a critical question: Are these digital nudges truly improving our well-being, or do they primarily serve the commercial interests of the companies that deploy them? This paper provides a comprehensive methodological review of the profound challenges researchers face in quantifying the real-world welfare effects of these persuasive systems. We identify and elaborate on five core, interlocking challenges: (1) the fundamental difficulty in measuring consumer surplus, especially its non-monetary components; (2) the ambiguity in defining a credible counterfactual against which to evaluate sophisticated algorithmic systems; (3) the complexity of establishing robust causal inference in dynamic, endogenous digital environments; (4) the severe data access limitations and algorithmic opacity that impede independent research and audits; and (5) the difficulty of capturing long-term, dynamic, and heterogeneous effects across a diverse population. By examining these challenges, this paper aims to create a detailed methodological roadmap to better understand and shape India's burgeoning digital economy for the equitable benefit of all its citizens.},
        keywords = {},
        month = {January},
        }

Cite This Article

P, S. K. M., & Sumathi, D. V. (2026). Measuring the Unseen Hand: Methodological Challenges in Quantifying the Welfare Effects of Algorithmic Persuasion. International Journal of Innovative Research in Technology (IJIRT), 12(8), 3507–3514.

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