The Past, Present, and Future of Technology Forecasting with Jeff Alstott
Aug 30, 2024
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Jeff Alstott, an expert at the National Science Foundation and director of the Center for Technology and Security Policy at RAND, dives deep into technology forecasting. He critiques traditional methods and emphasizes the need for strategic foresight and robust data to enhance predictions. Alstott discusses the challenges of data accessibility and the impact of historical contexts on future advancements. He also shares insights on the role of AI in shaping national security and the importance of collaborative initiatives in technology assessment.
Jeff Alstott emphasizes the importance of understanding historical technological developments to inform future investments and strategies effectively.
Advancements in natural language processing are revolutionizing technology forecasting, enhancing data collection and enabling the development of causal models.
The NSF's APTO program aims to improve national security through better predictions of emerging technologies, optimizing R&D investments and resource allocation.
Deep dives
Expertise in Technology and Policy
The discussion highlights the unique intersection of Jeff Alstott's career, which combines expertise in technology forecasting, national security, and public policy. Initially studying a diverse range of subjects such as biology, cognitive science, and history, Alstott developed a framework for understanding technology's evolution and implications for society. This foundational knowledge enabled him to pivot towards artificial intelligence and its future potential, particularly in assisting governmental and societal advancements. By revisiting historical timelines of technology, he emphasizes that understanding these past developments can better inform future investments and strategies.
The Role of Data in Advancing Science
Alstott explains that significant scientific progress, particularly in fields like neuroscience, often hinges on the availability of data and effective measurement technologies. He asserts that aspiring scientists are frequently constrained by the technical capabilities available for gathering data, which limits the scope of possible research questions. Historical examples illustrate that breakthroughs often occur when new measurement tools or engineering innovations become available, driving scientific discovery forward. This insight underscores the need for timely predictions regarding when new technologies will become accessible, enabling researchers to align their studies with forthcoming advancements.
Forecasting Technology Evolution
The conversation dives deep into the concept of technological forecasting, moving beyond traditional anecdotal wisdom to a more empirical basis for predictions. Alstott critiques existing forecasting models, such as Moore's Law, for their lack of underlying mechanistic theories that could explain technology's progression over time. He argues that while these models have been useful, they often lead to inaccurate forecasts without a comprehensive framework to account for various influencing factors. The need for a nuanced understanding of individual technology sectors emerges as crucial, allowing for more accurate predictions across multiple fields.
The Launch of the APTO Program
The Assessing and Predicting Technology Outcomes (APTO) program at the NSF represents a shift in how technology forecasting can be accomplished, particularly due to advancements in natural language processing and large language models (LLMs). Alstott illustrates how these tools can significantly enhance data collection efforts across various technology sectors, enabling researchers to build causal models based on historical data. The program aims to establish a robust community of researchers dedicated to improving technology forecasting, while also exploring the roles of R&D investments in shaping future outcomes. Through cooperative agreements, the APTO program emphasizes rigorous evaluation and accountability among participants to ensure substantial advancements in predictive capabilities.
Implications for National Security and Beyond
Alstott discusses the broader implications of the APTO program, particularly how it relates to national security and the strategic planning capacities of various organizations. By accurately predicting emerging technologies, both governmental and private sector entities can make informed decisions that optimize R&D investments and resource allocation. This capacity to forecast technological change can be vital for addressing challenges such as bioweapons proliferation or other developments that could threaten public safety. Ultimately, the integration of rigorous forecasting methodologies is anticipated to empower decision-makers with the knowledge necessary to navigate complex technological landscapes effectively.
In this episode, we are joined by Jeff Alstott, expert at the National Science Foundation (NSF) and director of the Center for Technology and Security Policy at RAND, to discuss past technology forecasting across the national security community (20:45) and a new NSF initiative called Assessing and Predicting Technology Outcomes (APTO) (31:30).
