School of Advanced Study

An increasing amount of work in AI aims to build computational systems that are not just tools for human users but agents in their own right. In AI, agency is often taken to consist simply in the capacity to pursue and achieve goals. However, different kinds of sophistication in representational processing produce different degrees or varieties of goal-directedness. Realist representational accounts of goal-directedness usually omit or fail to highlight a requirement which is central to instrumentalist representational accounts, namely that there is a certain coherence or unity of purpose amongst the different goals that the system pursues. That is a commitment of Dennett’s Intentional Stance, for example. The same requirement operates when biologists adopt the rational agent heuristic to make sense of the evolved phenotypes of an organism. This paper argues that this requirement should be included when specifying what it is for an AI system to be an agent. If the degree to which an AI system is an agent is captured in terms of what it represents and what computations it performs, mechanisms that help achieve unity of purpose are an important ingredient. One dimension along which an AI system becomes more agentive is increased sophistication in such mechanisms. Conversely, when the objective is to build AI systems that are agents, satisfying this additional requirement will endow machine learning systems with a deeper kind of goal-directedness or agency.

There are numerous victims and consequences of corruption and money laundering (ML) in many developing countries (DCs). This article reiterates the conspicuous symbiotic relationship between corruption and ML, making it difficult to isolate them in financial crime. The article uses a doctrinal approach and relies on both primary and secondary documents in the analysis. Some of the documents are inclusive of but not limited to the United Kingdom Bribery Act 2010, the United States Foreign Corrupt Practices Act 1977, the Nigerian Economic and Financial Crimes Commission Act 2011 and Independent Corrupt Practices and other Related Offences Commission Act 2000 and some pronouncements of the World Bank. It is incontestable that corruption and ML have devastating domino implications in DCs, particularly Nigeria, and the time is now ripe to increase efforts towards tackling this problem which has a strong potential to become even more serious. This article seeks to highlight the problem of ML in DCs and bolster efforts to reduce it.

Bargaining is a fundamental social behavior in which individuals often accept unfair offers. Traditional behavioral models, based solely on choice data, typically interpret such acceptance as simple reward-maximization. However, regulating inequity aversion may also play a critical role in these decisions. Incorporating response time alongside choice data allows us to quantify participants' internal mental effort when deciding to accept unfair offers. We conducted functional magnetic resonance imaging (fMRI) while participants played the ultimatum game, deciding within 10 s whether to accept or reject monetary offers from a proposer. Using the drift diffusion model (DDM), we quantified decision-making dynamics based on both choice and response time. Participants with lower levels of behavioral disadvantageous inequity (DI) aversion (reflected by a lower DDM weight for DI) showed stronger neural representations of DI in the dorsal anterior cingulate cortex (dACC). Functional connectivity analysis revealed a negative correlation between the dACC and bilateral ventrolateral prefrontal cortex (vlPFC) when DI was high. This connectivity predicted both rejection rates and response times associated with the acceptance of DI offers. Furthermore, robust linear regression showed that only dACC-vlPFC connectivity-not reward-related activity-explained both the rejection rates and response times. Finally, right vlPFC activity correlated with amygdala activity under high DI conditions. These findings suggest that the dACC plays a key role in regulating responses to DI, thereby facilitating the acceptance of unfair offers.

Purpose This study aims to propose a multi-objective optimization framework for dry port location selection, integrating transport costs, intermodal transport ratios and carbon emissions. Through empirical validation with real-world data from Northeast China, it demonstrates the feasibility of constructing a low-carbon logistics network, offering actionable strategies for sustainable dry port planning. Design/methodology/approach A multi-objective mixed-integer model integrates NSGA-II and α-conditional lexicographic algorithms. Multi-scenario experiments validate the model, supported by empirical datas from 33 freight nodes. Findings The results demonstrate that the optimized dry port location plan significantly reduces total costs and increases the proportion of intermodal transport. Rail electrification and cost reduction show notable effects on emission reduction and efficiency improvement, while solely enhancing dry port capacity has limited short-term impacts on logistics networks. This study also highlights the advantages of combining algorithms to balance economic and environmental objectives. Originality/value First, this study combines NSGA-II and α-conditional lexicographic methods to resolve multi-objective conflicts. Second, it innovatively integrates cost, emissions and intermodal targets with dynamic thresholds. The Northeast China case pioneers a dynamic decision framework for dry port locations under environmental constraints, offering a paradigm for regional low-carbon logistics planning.

Kotanegara Village is located in East Ogan Komering Ulu (OKU) Regency, South Sumatra, and the majority of its residents make a living as farmers, especially rice. This village has abundant natural potential, but faces challenges in accessibility, infrastructure, and fluctuations in the price of agricultural products. Village communities implement a culture of mutual cooperation and still depend on the agricultural sector for their livelihood. problems faced by farmers in Kotanegara Village in promoting rice crops, especially due to the lack of access to effective promotional media. Most farmers still use conventional methods. The researcher aims to create a Website-Based UI/UX Application Design for Rice Crop Collectors in Kotanegara Village with the Design Thinking Method" aims to provide innovative solutions that focus on user needs. Through the Design Thinking method, this study succeeded in designing an application prototype designed to make it easier for collectors to manage crop yields, access market price information, and improve coordination with farmers. The results of this study show that the application of website-based technology can support work efficiency, transparency, and better data management.

ABSTRACT Scientific evidence supports dominant institutional understandings of the global socio-ecological crises of the triple planetary crisis-climate change, biodiversity loss and pollution-demonstrating the profound impacts of human activities on Earth systems. Pollution is intimately tied to these crises, through extractivism and production of chemicals, including plastics and poses serious threats to the environment and human rights. While science is often invoked in multilateral environmental for addressing chemicals, plastics, waste and pollution, some critically important dilemmas, conflicts of interest and power imbalances arise. In this context, the Right to Science, the right of all people to benefit from scientific progress and its applications, offers a powerful yet underutilised tool. Recognised in Article 15(1)(b) of the International Covenant on Economic, Social and Cultural Rights, this right reinforces the importance of evidence-based decision-making. However, it is increasingly undermined by vested interests deploying strategies of denial, delay, manufactured ignorance and misinformation. Upholding this right requires concrete measures: public funding for science and education, academic freedom, data transparency, meaningful participation of diverse knowledge holders and mechanisms to address conflicts of interest. Embedding a rights-based approach into Multilateral Environmental Agreements can help ensure science serves the public interest in addressing the pollution crisis.