Big Tech Research examines the increasing concentration of Artificial Intelligence research within major technology companies and its broader impact on the AI ecosystem. The book explores whether AI innovation will be driven by a diverse range of voices or primarily by a select few corporations. Readers gain insights into the evolution of AI, from academic roots to its current commercial imperative, without needing deep technical knowledge. The book argues that, while Big Tech's investment has accelerated AI progress, this concentration poses risks to innovation diversity and ethical considerations. The analysis is supported by data from academic publications, patent filings, and conference proceedings, using bibliometric and network analysis to map relationships between researchers and institutions. For example, the book highlights how talent acquisition strategies and data access policies within Big Tech contribute to this concentration.
Structured in four parts, the book begins by defining key concepts and establishing a framework. It then profiles major Big Tech research divisions, analyzes the implications of research concentration, and proposes alternative models for fostering greater openness and societal benefit. This approach offers a novel perspective by combining data analysis with commentary on the ethical dimensions of AI research, making it valuable for policymakers, business leaders, and anyone interested in understanding the forces shaping the future of AI.
