Science LTD examines the evolving relationship between scientific knowledge, technology, and society in an era where deep tech companies are increasingly driven by discoveries rather than market demand. Written from the perspective of metascientific entrepreneurs, this timely work explores how scientific research struggles to balance profit with truth, individual objectives with collective values, and human creativity with machine capabilities. The book addresses the undisputed influence of science in contemporary society while questioning the sustainability of current research paradigms.
The book tackles critical operational questions about modern science: How is scientific knowledge produced and prioritized? How are research funds distributed? What constitutes effective dissemination and application of discoveries? Chapters examine the journey from laboratory innovation to commercial implementation while exploring two fundamental challenges facing the scientific community. First, the urgent need to reform scientific practices, particularly rethinking academic publishing and research funding models to create more open and sustainable science. Second, the complex prospect of human-machine collaboration in research, moving beyond traditional instruments to AI assistants with capabilities that exceed human limitations. Enriched with expert interviews and real-world anecdotes, the book provides both practical insights and speculative analysis of science's automated future.
This accessible work is designed for researchers, entrepreneurs, policymakers, and anyone curious about the intersection of science and technology. It serves academics seeking to understand contemporary research dynamics, industry professionals navigating the deep tech landscape, and general readers interested in how scientific discovery shapes society. The book offers valuable perspectives for those involved in research funding, science policy, and technology transfer, while remaining engaging for anyone concerned about the future of human-driven versus machine-assisted scientific innovation.
