TY - JOUR
T1 - Artificial intelligence and fertility
T2 - Gender and educational inequalities in family formation
AU - Adserà, Alícia
N1 - Publisher Copyright:
© The Author(s) 2025 Open Access This article is published under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) that allows the sharing, use and adaptation in any medium, provided that the user gives appropriate credit, provides a link to the license, and indicates if changes were made.
PY - 2025/1
Y1 - 2025/1
N2 - Artificial intelligence (AI) is propelling a new phase of technological change beyond routine automation, and impacts directly the domains where individuals decide if, when and with whom to have children. This debate essay outlines four interlocking channels through which AI is likely to reshape – and often widen – fertility inequalities over the next two decades. (1) Labour market polarisation: AI fosters labour augmentation, capital labour substitution and the emergence of new tasks. Those impacts may in turn affect income levels as well as gender pay differentials across educational groups, and alter the economic preconditions for partnership and childbearing. (2) AI-enabled reproductive medicine and fertility apps: machine-learning tools promise higher success rates and finer cycle tracking, yet their benefits could concentrate among affluent, digitally literate couples depending on the policy environment. (3) Algorithmic partner matching: recommender systems in dating platforms intensify educational homogamy and may entrench socioeconomic assortative mating, with downstream effects on union formation and completed fertility. (4) Algorithmic influence on ideals and information: personalised social media feeds and workplace monitoring shape perceptions of the “right” timing, costs and effort of parenthood, potentially reinforcing existing divides. Whether these mechanisms merely replace earlier drivers of fertility inequality or accumulate atop them remains an open question for demographic research and policy.
AB - Artificial intelligence (AI) is propelling a new phase of technological change beyond routine automation, and impacts directly the domains where individuals decide if, when and with whom to have children. This debate essay outlines four interlocking channels through which AI is likely to reshape – and often widen – fertility inequalities over the next two decades. (1) Labour market polarisation: AI fosters labour augmentation, capital labour substitution and the emergence of new tasks. Those impacts may in turn affect income levels as well as gender pay differentials across educational groups, and alter the economic preconditions for partnership and childbearing. (2) AI-enabled reproductive medicine and fertility apps: machine-learning tools promise higher success rates and finer cycle tracking, yet their benefits could concentrate among affluent, digitally literate couples depending on the policy environment. (3) Algorithmic partner matching: recommender systems in dating platforms intensify educational homogamy and may entrench socioeconomic assortative mating, with downstream effects on union formation and completed fertility. (4) Algorithmic influence on ideals and information: personalised social media feeds and workplace monitoring shape perceptions of the “right” timing, costs and effort of parenthood, potentially reinforcing existing divides. Whether these mechanisms merely replace earlier drivers of fertility inequality or accumulate atop them remains an open question for demographic research and policy.
KW - Artificial intelligence
KW - Educational inequality
KW - Fertility
KW - Gender inequality
KW - Labour market polarisation
KW - Online dating
KW - Reproductive technology
UR - https://www.scopus.com/pages/publications/105024704976
UR - https://www.scopus.com/pages/publications/105024704976#tab=citedBy
U2 - 10.1553/p-5fff-96k6
DO - 10.1553/p-5fff-96k6
M3 - Article
AN - SCOPUS:105024704976
SN - 1728-4414
VL - 23
SP - 1
EP - 10
JO - Vienna Yearbook of Population Research
JF - Vienna Yearbook of Population Research
IS - 1
ER -