by Sophie Welsh
As the strategic rivalry between the U.S. and China has intensified in the Indo-Pacific region, the U.S. allies have had to adapt their own foreign and national defense policies. Two practitioners and a scholar from Japan spoke in a panel in February 2022 to analyze such security policy dynamics. Tokuhiro Ikeda (Vice Admiral, ret.) spoke about current developments in Japan’s Maritime Self-Defense Forces (MSDF) in the context of the U.S.-China conflict. Concerns have been rising due to China’s 2019 Defense White Paper that stressed the importance of territorial unification of China. The military balance in Indo-Pacific has gradually become more favorable to China vis-a-vis the U.S. and its allies. In recent months, there have been speculations that China could take military action against Taiwan in the next several years. the Chinese leadership has made it clear that it is willing to use force to prevent Taiwan from becoming an independent sovereign country.
Given that China possesses the world’s largest navy and its expanding maritime operations, Japan’s MSDF has also changed its activities in recent years, shifting its Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) from passive to active surveillance in 2012. The government of Japan issued the new National Defense Program Guidelines (NDPG) and has made quantitative and qualitative improvements in its military equipment. It has added six destroyers, added six submarines, and is to build 22 new frigate types. Ikeda notes that China is testing MSDF’s durability and toughness. The government of Japan is also preparing the latest NDPG to enhance its defense further, which would likely emphasize strengthening the Self-Defense Forces (SDF) and the U.S.-Japan alliance to pursue security and peace in the Indo-Pacific region.
Keita Azuma (Cabinet Secretariat) examined the different structures of what he called “collective intelligence” in the U.S. decision-making processes over gray zone conflicts. He applied what he called the “dual process theory,” and explored conditions under which collective intelligence can have positive effect on national decision-making. He examined questions such as: How does the U.S. perceive its security challenges in gray zone conflicts, and their impact on U.S. strategic superiority and the existing international order? How does collective intelligence shape its strategic response? How will the U.S. react if China changes the status quo through gray zone activities that do not involve military escalation? Under what conditions does collective decision-making lead to sensible conclusions or to serious miscalculations and errors?
In a research project involving participants in both Japan and the U..S, he found two different systems. In system 1, decisions are made quickly with consensus, regardless of research or debate. This system was characterized by efficiency and stability, but also entailed risks in heuristics and biases. By contrast, in system 2, decisions were made with involved more debate and deliberation, but incurred costs in research, discussion, and consideration, requiring constant updates of assumptions and information based on observation.
A key finding of applying the dual process theory to cognitive intelligence is that integrated collective intelligence is more effective for system 1 decision-making, and diverse collective intelligence is more effective for system 2 decision-making. These two systems present a trade-off.
The presentation by Aki Nakai (Policy Innovations Fellow) focused on the questions of how Japan is responding to artificial intelligence (AI), and what influences Japan’s artificial intelligence budget. His study considered two competing explanations for Japanese policymaking on each ministry’s AI budget in each year from 2016 to 2021. One possible scenario was the “developmental state”, where bureaucrats are the primary decisionmakers and direct funds to benefit the overall economic welfare of the country. The other hypothesis emphasizes electoral politics, where elected politicians try to pursue and enhance their narrowly defined self-interests. Each of these explanations had several proxy variables. For the developmental state hypothesis, these included the annual economic growth rate by industry, payroll by industry, production inducement coefficient by industry, frequency of the term AI in the “Basic Policies” documents issued by the Council on Economic and Fiscal Policy (CEFP). For electoral politics, proxy variables included the number of potential voters by industry, number of interest group members by industry, recruitment of former bureaucrats by industry, and whether or not an election took place in each year.
Nakai used the Ordinary Least Squares (OLS) regression analysis, which showed statistically significant effects of the term AI in CEFP’s “Basic Policies,” showing support for one of the developmental state hypothesis. Japan has spent 1.3 trillion yen on AI in the last 6 years. The AI budget increased over several years, leading to a major spike in 2020, then dramatically decreased in 2021. This pattern closely follows the pattern of AI mentions in the Basic Policies. In addition, there was a significant correlation between the AI budget and number of interest group members by industry, supporting one of the electoral politics hypothesis. These findings demonstrate the role of the institutionally empowered Prime Minister and their views on the U.S.-Japan alliance, and the Japanese government’s focus on setting international rules and standards in the area of AI.
Jennifer Lind (Dartmouth College) offered feedback on each presentation, highlighting different alliance and domestic political dynamics in the policy areas of maritime defense, use of intelligence for national security decision-making, and policy support for AI. Her comments were followed by a wide ranging discussion on the U.S.-China power dynamics in the region, and Japan’s security policy options as a U.S. ally.