Instytut Podstawowych Problemów Techniki
Polskiej Akademii Nauk

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Bartosz Pieliński


Ostatnie publikacje
1.  Giziński S., Kaczyńska P., Ruczyński H., Wiśnios E., Pieliński B., Biecek P., Sienkiewicz J., Big Tech influence over AI research revisited: Memetic analysis of attribution of ideas to affiliation, Journal of Informetrics, ISSN: 1751-1577, DOI: 10.1016/j.joi.2024.101572, Vol.18, No.4, pp.101572-1-17, 2024

Streszczenie:
There exists a growing discourse around the domination of Big Tech on the landscape of artificial intelligence (AI) research, yet our comprehension of this phenomenon remains cursory. This paper aims to broaden and deepen our understanding of Big Tech's reach and power within AI research. It highlights the dominance not merely in terms of sheer publication volume but rather in the propagation of new ideas or memes. Current studies often oversimplify the concept of influence to the share of affiliations in academic papers, typically sourced from limited databases such as arXiv or specific academic conferences.
The main goal of this paper is to unravel the specific nuances of such influence, determining which AI ideas are predominantly driven by Big Tech entities. By employing network and memetic analysis on AI-oriented paper abstracts and their citation network, we are able to grasp a deeper insight into this phenomenon. By utilizing two databases: OpenAlex and S2ORC, we are able to perform such analysis on a much bigger scale than previous attempts.
Our findings suggest that while Big Tech-affiliated papers are disproportionately more cited in some areas, the most cited papers are those affiliated with both Big Tech and Academia. Focusing on the most contagious memes, their attribution to specific affiliation groups (Big Tech, Academia, mixed affiliation) seems equally distributed between those three groups. This suggests that the notion of Big Tech domination over AI research is oversimplified in the discourse.

Słowa kluczowe:
Knowledge diffusion, Novelty, Affiliation influence, Big tech impact, Complex networks, Natural language processing

Afiliacje autorów:
Giziński S. - inna afiliacja
Kaczyńska P. - inna afiliacja
Ruczyński H. - inna afiliacja
Wiśnios E. - inna afiliacja
Pieliński B. - inna afiliacja
Biecek P. - inna afiliacja
Sienkiewicz J. - inna afiliacja
140p.

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