東京大学公共政策大学院 | GraSPP / Graduate School of Public Policy | The university of Tokyo

Today's class in 6th period is cancelled.

Makeup class will be held on January 15th, Wednesday, in 6th period.

Please refer to UTOL information section in detail.

The higher temperatures brought about by UHI stem from a combination of effects, including greater absorption of heat in road and building materials, ‘canyon’ heat-trapping of tall structures, and waste heat from cars and facilities. Exacerbated by climate change, heat-related stress and mortality risk will increasingly pose a hazard for the world’s cities, which accommodate a growing majority of the population.

To anyone who has had the chance to visit Thailand’s modern-day metropolis, the implications of UHI might be enough to trigger more than a few tropical flashbacks. During its infamous dry season, UHI raises temperatures in Bangkok another 6–7°C, awarding it the fourth highest for heat exposure in the world. Causes for such extreme conditions include limited green space, poor urban design, extensive air conditioning and high vehicle emissions. In light of the dire predictions of climate change, what Bangkok is experiencing today potentially foreshadows a fate awaiting many other cities in the world. Hence, the Bangkok government faces an opportunity to set a precedent which other regions, particularly those in Southeast Asia recognised to be highly climate vulnerable, could follow great interest.

Yet, despite all the incentives to address the problem, the Thai and Bangkok administrations have shuffled their feet, stifled by weak governance, economic priorities, and bureaucratic obstacles. The challenge marked by the BangCool proposal is to find long-term solutions to the fragmentation of governance and lack of collaboration with private stakeholders, and devise a process to align the interests of each party. At the same time, it aims to promote public awareness of the critical effects of UHI, particularly in low-income communities in densely urbanised areas who are disproportionately vulnerable.

Thailand’s national policy for land use has a history which can be summarised as passive. An official was once quoted as admitting “our department focuses more on economic rather than environmental priorities”. At a local level, the Bangkok Metropolitan Administration (BMA) has several divisions assigned to heat adaptation; however, collaboration is rare, and no policy directly addresses the problem of UHI. Its City Planning Department’s “comprehensive” 2013 urban land use plan notably failed to protect its remaining green space, due to a lack of cross-departmental communication and insufficient fines for breaches.

Compounding the problem is Bangkok’s private sector, which has little history of engaging with environmentally friendly building projects. Bangkok is provides a golden example of the notion “Whenever there is a chance to turn a piece of land into a commercial space, developers always build the maximum.” It is clear that more proactive leadership is needed to issue incentives to developers to drive long-term countermeasures to UHI.

The student team’s proposal details a pilot to initiate this key public-private linkage, aiming to serve as a model for natural cooperation that can propagate throughout society. In the first phase, a task force will be assigned to spread awareness of the problems of UHI and their possible solutions. As a lack of public understanding was cited as hindering progress in the past, it is important to facilitate greater local community involvement and fair oversight of the infrastructure development process. This phase will include a study between local authorities and private developers to prove the concept of this collaboration, including subsidies for measures such as painting roofs white and planting vegetation.

The outcomes will be used in the second phase to implement incentives for businesses, including a rating system for sustainable buildings and revised purchasing criteria for public procurement. Again, transparency and involvement of stakeholders from the start of discussions will be key to effective adoption. Noting other similar initiatives which have been successful in the past, the implementation strategy includes forming partnerships with local universities, NGOs and the private sector, recruiting volunteers from local colleges and communities, and involving real estate developers for innovative UHI measures.

In the pilot’s implementation, BangCool would aim to cover 3,000 residential roofs in one of Bangkok's hotspot districts, such as Udom Suk, Khlong Toei or Huai Khwang. Monitoring and evaluation will be facilitated by installing temperature sensors and energy meters in selected homes while collecting feedback from residents. For funding, the initiative will appeal to local government, the private sector and international bodies which have previously backed UHI initiatives.

Regarding the crucial issue of division of responsibility, clear lines between national government ministries and the BMA will be drawn, discouraging developers from circumventing land use planning regulations. Furthermore, centralizing information on land use and infrastructure projects in the city offers considerable value to the BMA. Integrating this data with advanced technologies such as remote sensing and satellite imagery will enable local authorities to pinpoint areas of Bangkok's highest at risk from UHI, facilitating targeted intervention strategies.

Indicators to evaluate the proposal’s outcomes can be regularly monitored along the results chain, spanning from green rating building awards and reduced heat-related hospitalisations and deaths in the short-term, to improved health metrics and increased private sector investment in the long-term.

While the team has tailored the aims of BangCool to address specific needs of the local community, the project’s inclusive collaborative infrastructure can scale to Bangkok’s 50 districts and other cities internationally. Similarities in geography, demographics and socio-economics in South and Southeast Asian regions mean that Bangkok could set a standard in UHI mitigation, as well as provide an iterative model to deal with a range of pubic-private policy problems.

As proven by its chequered history, effective management of Bangkok's UHI problem is not a simple matter of funding urban infrastructure projects. A sustainable, long-term solution requires a process that ensures buy-in from the government, developers and local communities while reducing misalignment between stakeholders. The team’s solution in the Bangkok Cooling Initiative would positively influence the design of infrastructure through data-driven and locally-led prioritisation. The fruits of such cooperation would not only herald a new era in green development, but allow in the air for much-needed community perspectives on living together with businesses, governments, and a global future.

 

(Edited by Clement Ng)

This blog post was originally written as a proposal to the 2024 Global Public Policy Network Conference by a student team at GraSPP (Junya Eriguchi, Emily Murnane, Bradley Murray, and Taishin Noble) in December 2023.

The full version is available from the link below.

(Final Proposal) Bangkok Cooling Initiative: Incentivizing Private Investment for Urban Heat Mitigation in Bangkok, Thailand 

Related links

GPPN Annual conferences

GraSPP Policy Challenge 2023

Sorry, this entry is only available in 日本語.

公共政策大学院ではキャンパスアジア・プラスという留学プログラムを実施しています。

2024年10月募集を控え、キャンパスアジア・プラスの説明・相談会を行います。（予約不要）

キャンパスアジアについて興味があるという方、実際に応募しようとしている方、お気軽に参加してください。みなさんの質問にお答えします。

Sorry, this entry is only available in 日本語.

令和7（2025）年度東京大学大学院公共政策学教育部専門職学位課程（公共政策大学院）入学試験合格者（一般選抜・職業人選抜）は、以下のPDFファイル記載のとおり。

合格者（PDF）

This course aims to deepen understanding of East Asian political, economic, and social issues through multidisciplinary analysis. It is designed for students participating in the Campus Asia program but if you are interested in interacting with international students from East Asia, please register for the course.

The tentative schedule of lectures (subject to change) is as follows: -Guidance -Visit to the Japanese Government/Ministry of Economy, Trade and Industry (subject to change) -Group discussion with students -Field trip -Guest lecture

This course is open from A1 to A2. The timetable shows two consecutive lectures, but as this is a two-credit course, we meet irregularly. Please read the guidelines in UTOL carefully. Details of the timetable will be given on the first day of the course, so please attend the first meeting (October 2nd) if you wish to register for this class.

Non-CAMPUS Asia students interested in registering should submit the Application Form, which includes a Statement of Purpose and a PDF of TOEFL scores (if you were required to submit TOEFL scores during the admission process).

The capstone project course, a unique and integral part of GraSPP’s curriculum, offers students a rewarding learning opportunity. It allows students to engage in independent projects in a team setting, addressing real-world problems at the client’s request. This challenging experience, as the word “capstone” suggests, is typically reserved as a final assignment for students with the necessary knowledge and skills acquired during the enrolment years to tackle real-world challenges. However, GraSPP, as a professional school, encourages first- and second-year students to take capstone project courses, recognizing their potential and maturity.

One of the capstone project courses offered since the academic year 2023 is Asia’s Geoeconomic Landscapes with Bain & Company, a global management consulting firm, as the client.

As a practical training course with an active learning approach, students worked in teams under the instructors’ guidance. Their deliverables were reviewed and submitted to the client as if the students ran a real-world consulting project. The consulting assignment was to produce a report to assist a semi-fictional Japanese company in developing a business strategy under given scenarios in Asia’s geoeconomic reality and seek public policy implications.

The course provided hands-on professional writing and communication training to prepare students for future professional positions addressing various geoeconomic challenges in the public and private sectors.

Teaching staff and client representatives

The teaching staff and client representatives in the academic year 2023 were the following. All the statuses and affiliations of the persons are as of December 2023.

Teaching staff

Toshiro Nishizawa, Professor

Shiro Armstrong, Visiting Lecturer (Associate Professor at the Crawford School of Public Policy of The Australian National University and Editor of the East Asia Forum.)

Michio Ueda, Geopolitical Strategy Consultant

Bain & Company representatives

Azusa Owa, Partner, Tokyo

Sho Ikeno, Partner, Tokyo

Kaori Nogami, Manager

 

Student voices

“I strongly recommend this course for the following reasons. First, this course provided students with intensive professional training, including teamwork, problem-solving, presentation, and report writing. By preparing a corporate geoeconomic strategy under the guidance of a real consulting firm, I gained a better understanding of how interwoven geopolitics could influence the business world and what kind of deliverables would meet professional standards. Second, this course is a perfect networking opportunity. We got to present in front of people from Bain & Company. Not only did we learn a lot from them, but we were able to show our ideas and increase our presence in the world-class consulting firm. Moreover, the boot camp increased our exposure to professionals from Bain & Company. This was an excellent opportunity for students interested in consulting firms.”

“I appreciate the practical approach of this class. More than knowledge, it taught us skills that will be usefully and easily transferable to other classes and future professional experiences. The well-organized course had complementary phases (scenario planning and consulting case). The clear and structured methodology we learned is unique. The iterative approach and continuous exchanges with the instructors and client representatives from Bain & Company also helped us a lot. They allowed us to understand the consulting world. Prof. Armstrong’s lectures complemented the class and gave us a different, more academic perspective on the issues we dealt with.”

“Enjoyed the opportunity to work on a mock-up consulting case guided by professionals in the field. I recommend it to anyone who’d like to be exposed to consulting work or the professional services industry in general.”

“The course surely had the most interesting and stimulating teaching approach I have ever experienced at GraSPP. In addition to finely grasping the geopolitical issues specific to Asia amidst the increased tensions between China and the United States, it allowed us to be familiar with the methods and requirements of the professional world. I produced comprehensive deliverables on an exciting consulting case with my team members. The entire team of instructors and professionals overseeing this course showed a benevolent demand that pushed us to excel and improve. I learned a lot. Thank you!”

Background: The need for a potentially wrong and unjust algorithmic decision to be explained.

Governments around the world are relying increasingly on decision making powered by artificial intelligence. Sooner or later, they will make numerous decisions that are important to citizens, based on machine-learning (ML) algorithmic treatment (hereafter referred to as “algorithmic decisions”).

An issue arises because algorithmic decisions can be potentially misleading and biased and can wrongfully infringe on the rights and welfare of those who are affected by these decisions (hereafter referred to as “affectees”). This issue points to the importance of safeguarding affectees’ right to an explanation for an algorithmic decision and offering explanations that render a decision transparent, accountable, and contestable.

In recent years, there have been moves to promote the right to an explanation through the passage of laws and regulations, most notably European Union’s General Data Protection Regulation. Such moves have made explainable artificial intelligence (XAI), which is designed to make an AI system’s decisions and behaviors intelligible to humans by offering explanations, ever more important.

Our Research Question: Does the type of explanation matter to people’s attitudes towards an algorithmic decision?

From a legal perspective, providing explanations for algorithmic decisions is important, so affectees can challenge a decision if necessary. In our paper, we argue, from societal and human-centric perspectives, that it is important for members of society to perceive that public authorities are making fair, accurate, and trustworthy algorithmic decisions in light of the aforesaid issues. Explanations might be able to help promote positive attitudes towards the decisions.

We investigated whether the status and the type of explanation matters to the fairness, accuracy, and trustworthiness of an algorithmic decision, as perceived by the affectees. The XAI literature points to the fact that explanations for algorithmic decisions can differ in type with respect to the kind of information they present; they can be

input-based, explaining how much an input variable influences the output, group-based, showing the outcome distributions across groups in the AI’s training data, case-based, presenting the cases in the AI’s training data that are most similar to the inquirer’s case, or counterfactual, pointing out what would have had to be different to yield a desirable outcome.

Inspired in part by psychological studies examining factors that have an impact on a person’s attitudes towards an outcome they receive, we posited that the perceived fairness, accuracy, or trustworthiness of an adverse algorithmic administrative decision depends on the type of explanation, because explanations differ in scope; some are global, explaining how an overall model works, while others are local and instance-specific, explaining the outcome in the case in question. Explanations also differ with respect to the points of comparison for the assessment of the distributive justice they provide, and with respect to the impression they give about the extent to which the AI system is subject to monitoring and correction.

Our Pre-Registered Studies: Experiments using scenarios involving decisions regarding a grant application and a tax inspection.

To test our hypotheses, we conducted two studies in December 2022, each of which involved an online survey experiment, pre-registered via the Open Science Framework. In both studies, the subjects were officers in high positions at stock companies registered in Japan, and they were presented with a hypothetical scenario consisting of an algorithmic decision made by a public authority: a ministry’s decision to reject a grant application from their company (Study 1) and a tax authority’s decision to select their company for an on-site tax inspection (Study 2).

In both studies, we randomly assigned one of the experimental conditions (E1 to E5) to the subjects: they were told that no explanation was given (E1) or they were given a generic description of the type of explanation offered -- namely, input-based (E2), group-based (E3), case-based (E4), or counterfactual (E5). We then asked all the subjects to assess whether the decision was fair, accurate, and trustworthy, and investigated how their attitudes differed across experimental groups.

Findings and Implications: It’s not just about offering any explanation – types matter.

Our studies revealed that offering the subjects some types of explanations had a positive impact on their attitude towards a decision, to various extents, except in the case of fairness in the tax inspection study. However, the detailed results were not robust across studies and decision domains. One reason for the discrepancies might have had to do with the nature of the decisions involved and differences in the types of explanations the subjects were seeking in order to develop their attitude towards the decision.

It is most important for algorithmic decisions to be actually fair, accurate, and trustworthy, but even if they are, whether members of the public perceive the decisions as such is a different issue. While more studies are needed to build strong evidence, our studies suggest that public authorities should consider providing some sort of explanation for an algorithmic decision to promote affectees’ perceptions of its fairness, accuracy, and trustworthiness. In doing so, they are reminded of the fact that some types of explanations might work better than others and that the effects might differ across decision domains.

Research Team

Naomi Aoki (Graduate School of Public Policy) Tomohiko Tatsumi （Graduate Schools for Law and Politics / Faculty of Law） Go Naruse（Graduate Schools for Law and Politics / Faculty of Law） Maeda Kentaro (Graduate School of Public Policy / Faculty of Law)

Paper Information

Aoki, N., Tatsumi, T., Naruse, Go., & Maeda, K. (2024). Explainable AI for government: Does the type of explanation matter to the accuracy, fairness, and trustworthiness of an algorithmic decision as perceived by those who are affected? Government Information Quarterly, 41(4), 101965. https://doi.org/10.1016/j.giq.2024.101965

Related news

Profs. Naomi Aoki and Kentaro Maeda’s co-authored paper entitled “Explainable AI for government: Does the type of explanation matter to the accuracy, fairness, and trustworthiness of an algorithmic decision as perceived by those who are affected?” was accepted and published in the Government Information Quarterly

This course aims to deepen understanding of East Asian political, economic, and social issues through multidisciplinary analysis. It is designed for students participating in the Campus Asia program but if you are interested in interacting with international students from East Asia, please register for the course.

The tentative schedule of lectures (subject to change) is as follows: -Guidance -Visit to the Japanese Government/Ministry of Economy, Trade and Industry (subject to change) -Group discussion with students -Field trip -Guest lecture

This course is open from A1 to A2. The timetable shows two consecutive lectures, but as this is a two-credit course, we meet irregularly. Please read the guidelines in UTOL carefully. Details of the timetable will be given on the first day of the course, so please attend the first meeting (October 2nd) if you wish to register for this class.

Non-CAMPUS Asia students interested in registering should submit the Application Form, which includes a Statement of Purpose and a PDF of TOEFL scores (if you were required to submit TOEFL scores during the admission process).