Administración de la innovación para el desarrollo sostenible. Fundamentos estratégicos

Artificial intelligence (AI) has become one of the most influential axes of contemporary science, not only because of its capacity to process large volumes of information and optimize analytical processes, but also because it profoundly reconfigures the epistemological, ethical, and institutional conditions of knowledge production. Its accelerated incorporation into scientific research, technological management, education, and innovation has generated significant advances; however, it has also raised critical questions concerning authorship, responsibility, transparency, governance, and scientific legitimacy. This book starts from the recognition that AI is not a neutral technology, but rather a sociotechnical artifact that embodies values, decisions, and power relations. Critical Artificial Intelligence in Contemporary Science is situated within this context and proposes an analytical and reflective reading of AI from a critical and interdisciplinary perspective. The work conceives AI not merely as an instrumental tool, but as a phenomenon that transforms scientific practices, institutional structures, and regulatory frameworks. From this standpoint, a critical approach does not imply technological rejection, but rather the need to understand, evaluate, and govern AI in an ethical, responsible manner oriented toward sustainable development. The eleven chapters that make up the volume address central issues emerging from the interaction between AI and science: institutional governance and intellectual property, the ethical use of generative models in qualitative research, open innovation, inequality in access to digital infrastructures, corporate social responsibility, educational sustainability, agri-food management, the training of entrepreneurs, technological development in Mexico, articulation with local forms of knowledge, and financial dissemination. This thematic diversity reflects the transversal nature of AI and the need for approaches that go beyond fragmented or exclusively technical visions. A distinctive feature of the book is the constant articulation between scientia and praxis. The chapters combine rigorous theoretical analyses with applied proposals, conceptual models, and institutional guidelines aimed at influencing real contexts of research, management, and decision-making. Likewise, the book engages with recent international frameworks on AI ethics and governance, incorporating a perspective situated within the Latin American and Mexican context. Taken as a whole, this work invites a rethinking of science in the age of artificial intelligence, promoting a critical integration of these technologies that preserves the centrality of human judgment, strengthens institutional legitimacy, and contributes to a socially responsible and ethically committed science.