1st Edition

What AI Can Do Strengths and Limitations of Artificial Intelligence

    458 Pages 69 Color & 15 B/W Illustrations
    by Chapman & Hall

    458 Pages 69 Color & 15 B/W Illustrations
    by Chapman & Hall

    The philosopher Spinoza once asserted that no one knows what a body can do, conceiving an intrinsic bodily power with unknown limits. Similarly, we can ask ourselves about Artificial Intelligence (AI): To what extent is the development of intelligence limited by its technical and material substrate? In other words, what can AI do? The answer is analogous to Spinoza’s: Nobody knows the limit of AI.

    Critically considering this issue from philosophical, interdisciplinary, and engineering perspectives, respectively, this book assesses the scope and pertinence of AI technology and explores how it could bring about both a better and more unpredictable future.

    What AI Can Do highlights, at both the theoretical and practical levels, the cross-cutting relevance that AI is having on society, appealing to students of engineering, computer science, and philosophy, as well as all who hold a practical interest in the technology.


    Section 1 – Nature and Culture of the Algorithm

    Chapter 1 AI Ethics as a Form of Research Ethics

    Florian Richter

    Chapter 2 Going through the Challenges of Artificial Intelligence: Gray Eminences, Algocracy, Automated Unconsciousness

    Vania Baldi

    Chapter 3 AI, Ethics, and Coloniality: a Feminist Critique

    Paola Ricaurte and Mariel Zasso

    Chapter 4 A Cultural Vision of Algorithms: Agency, Practices, and Resistance in Latin America:

    Gabriela Elisa Sued

    Chapter 5 From Deepfake to Deeptruth: Towards a Technological Resignification with Social and Activist Uses

    Jacob Bañuelos and Mariángela Abbruzzese

    Chapter 6 The Neurocomputational Becoming of Intelligence: Philosophical Challenges

    Manuel Cebral-Loureda

    Section 2 – Knowledge Areas Facing AI

    Chapter 7 A Cluster Analysis of Academic Performance in Higher Education through Self-organizing Maps

    C.F. Rodríguez-Hernández, E. Kyndt and E. Cascallar.

    Chapter 8 Artificial Intelligence as a way to Improve Educational Practices

    O. Olmos-López, E.G. Rincon-Flores, J. Mena., O. Román and E. López-Camacho.

    Chapter 9 Using AI for Educational Research in Multimodal Learning Analytics

    L.F. Morán-Mirabal., J. Alvarado-Uribe and H.G. Ceballos.


    Chapter 10 Artificial Intelligence in Biomedical Research and Clinical Practice

    Alejandro Garcia-Gonzalez

    Chapter 11 The Dark Side of Smart Cities

    Hinojosa Hinojosa, K. and González-Cacho, T.,

    Chapter 12 The Control of Violence Between the Machine and the Human

    Vivar Vera, J. and Díaz Estrada, F

    Chapter 13 Al in Music: Implications and Consequences of Technology Supporting Creativity

    Carolina Sacristán Ramírez, Flavio Everardo, Yamil Burguete Fourzali and Brecht De Man

    Section 3 Future Scenarios and Implications for the Application of AI

    Chapter 14 Classification Machine Learning applications for Energy Management Systems in Distribution Systems to Diminish CO2 Emissions

    Juan R. Lopez, Pedro Ponce and Arturo Molina

    Chapter 15 Artificial Intelligence for Construction 4. 0: Changing the Paradigms of Construction

    Pedro Fonseca, Juan Pablo Solís, Juan Guadalupe Cristerna Villegas

    Chapter 16 A Novel Deep Learning Structure for Detecting Human Activity and Clothing Insulation

    Omar Mata, Diego L´opez, Adan Medina, Pedro Ponce Arturo Molina and Ricardo Ramirez

    Chapter 17 Building predictive models to efficiently generate new nanomaterials with antimicrobial activity.

    Gildardo Sánchez-Ante, Edgar R. López-Mena, and Diego E. Navarro-López

    Chapter 18 Neural Networks for an Automated Screening System to Detect Anomalies in Retina Images

    Gildardo Sanchez-Ante, Luis E. Falcon-Morales and Humberto Sossa-Azuela

    Chapter 19 Artificial Intelligence for Mental Health: A Review of AI Solutions and their Future

    Gerardo Castañeda Garza, Héctor Gibrán Ceballos Cancino and Paola Gabriel Mejía Almada

    Chapter 20 What AI can do for Neuroscience: Understanding How the Brain Represents Word Meanings

    Nora Aguirre-Celis and Risto Miikkulainen


    Chapter 21 Adversarial Robustness on Artificial Intelligence

    Ivan Reyes-Amezcua, Gilberto Ochoa Ruiz and Andres Mendez-Vazquez


    Manuel Cebral-Loureda is a full-time professor and researcher at the Tecnológico de Monterrey, School of Humanities and Education, Campus Monterrey. He holds a PhD in Philosophy (University of Santiago de Compostela), with the thesis "The cybernetic revolution from the philosophy of Gilles Deleuze: a critical review of data mining and Big Data tools", and has a master's degree in Statistical Learning and Data Mining (UNED), as well as another in Art, Philosophy and Creativity (University of Valencia). His current interests focus on Digital Humanities (applying computational tools and methods to humanistic studies), the critical reflection on technology, and Posthumanism. Some of his most recent articles include "The beginnings of the COVID19 pandemic on Twitter. Computational analysis of public conversation in the Spanish language" (2021) or "Will and desire in modern philosophy: a computational approach" (2020). Since 2021, he is a member of the Mexican National System of Researchers (SNI).

    Elvira G. Rincon-Flores holds a PhD in Education Sciences from the University of Salamanca, Cum Laude thesis. Actually, she is an Impact Measurement Research Scientist at  the Institute for the Future of Education of the Tecnologico de Monterrey, and she is also a professor at the same institution. She belongs to the National System of Researchers of Mexico (SNI-Level 2), and the research groups: GRIAL and GIIE, the University of Salamanca, and Tecnologico de Monterrey, respectively. She is the leader of the following research projects: Adaptive Learning, Gamification in Higher Education, Student Mentoring, Wellbeing Students, and Educational Spaces. It also collaborates with the University of Lima in the development of a dynamic platform for Gamification called Gamit! Her lines of research are Educational Innovation Evaluation and Educational Gamification.

    Gildardo Sanchez-Ante is a full-time professor and researcher at the Tecnológico de Monterrey School of Engineering and Sciences, Campus Guadalajara. Holds a PhD in Computer Science from Tecnologico de Monterrey in 2002. From 1999-2001 he was a Visiting Researcher at the Robotics Laboratory of Stanford University and from 2004-2005 he was a Research Fellow at the National University of Singapore. He is a Senior Member of the IEEE and the ACM. Member of the National System of Researchers (SNI). His research interests are in automatic learning and pattern recognition, as well as its application to robotics. He has recently worked in the computational modeling of nanomaterial properties to optimize their performance.