Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

The Ethical Choice of Business English Interpreters under Chesterman’s Model of Translation Ethics

This paper explores the ethical challenges encountered by business English interpreters using Chesterman’s Model of Translation Ethics,set against the context of economic globalization and the“Belt and Road”initiative.With the increasing demand for interpreters,the paper delves into the ongoing discussion about the role of AI in translation and its limitations,especially concerning cultural subtleties and ethical issues.It highlights the importance of human interpreters’cross-cultural understanding and the ethical principles that inform their work,such as the Ethics of Representation,Service,Communication,Norm-based Ethics,and Commitment.Moreover,the paper examines how these ethical models are applied in practical business situations,including business banquets,business negotiations,business talks and business visits,etc.,and investigates the cultural misunderstandings that may occur during these interactions.The study concludes that although AI provides efficiency and cost savings,human interpreters are essential for their capacity to handle the intricacies of cross-cultural communication with cultural awareness and ethical discernment.

A Blind Spot in the Reframing of a Universe of Possibles: Towards a Suitable Model for Decision-Making Theory and A.I.

Bayesian inference model is an optimal processing of incomplete information that, more than other models, better captures the way in which any decision-maker learns and updates his degree of rational beliefs about possible states of nature, in order to make a better judgment while taking new evidence into account. Such a scientific model proposed for the general theory of decision-making, like all others in general, whether in statistics, economics, operations research, A.I., data science or applied mathematics, regardless of whether they are time-dependent, have in common a theoretical basis that is axiomatized by relying on related concepts of a universe of possibles, especially the so-called universe (or the world), the state of nature (or the state of the world), when formulated explicitly. The issue of where to stand as an observer or a decision-maker to reframe such a universe of possibles together with a partition structure of knowledge (i.e. semantic formalisms), including a copy of itself as it was initially while generalizing it, is not addressed. Memory being the substratum, whether human or artificial, wherein everything stands, to date, even the theoretical possibility of such an operation of self-inclusion is prohibited by pure mathematics. We make this blind spot come to light through a counter-example (namely Archimedes’ Eureka experiment) and explore novel theoretical foundations, fitting better with a quantum form than with fuzzy modeling, to deal with more than a reference universe of possibles. This could open up a new path of investigation for the general theory of decision-making, as well as for Artificial Intelligence, often considered as the science of the imitation of human abilities, while being also the science of knowledge representation and the science of concept formation and reasoning.

Ethical-GPT:一种面向人工智能伦理教育的垂类GPT工具设计与实现

人工智能技术在推动教育变革的同时,也引发了诸如隐私泄露、技术滥用等伦理风险挑战,使得加强人工智能伦理教育势在必行。同时,当前教育人工智能伦理建设过程中存在的学习资源稀缺、教学方式单一、缺乏实质性的伦理实践等问题也亟待解决。对此,文章首先采用“大语言模型微调+本地知识库”的技术路线,设计了面向人工智能伦理教育的垂类GPT工具——Ethical-GPT,并介绍了Ethical-GPT的基础问答、案例学习、情境模拟、智能测验四大功能模块;之后,文章从大模型选取、本地知识库建设、高效模型微调等方面重点阐述了Ethical-GPT的技术实现,并通过对比不同模型的回答结果进行了模型效果分析,发现Ethical-GPT具有良好的专业问答能力,并且能够随机生成并呈现多样化的伦理案例;最后,文章深入探讨了Ethical-GPT的教育应用场景。文章设计的Ethical-GPT不仅为人工智能伦理的教育实践提供了工具支持,也为推动教育领域专用大语言模型的构建提供了参考思路。

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Research on Maneuver Decision-Making of Multi-Agent Adversarial Game in a Random Interference Environment

The strategy evolution process of game players is highly uncertain due to random emergent situations and other external disturbances.This paper investigates the issue of strategy interaction and behavioral decision-making among game players in simulated confrontation scenarios within a random interference environment.It considers the possible risks that random disturbances may pose to the autonomous decision-making of game players,as well as the impact of participants’manipulative behaviors on the state changes of the players.A nonlinear mathematical model is established to describe the strategy decision-making process of the participants in this scenario.Subsequently,the strategy selection interaction relationship,strategy evolution stability,and dynamic decision-making process of the game players are investigated and verified by simulation experiments.The results show that maneuver-related parameters and random environmental interference factors have different effects on the selection and evolutionary speed of the agent’s strategies.Especially in a highly uncertain environment,even small information asymmetry or miscalculation may have a significant impact on decision-making.This also confirms the feasibility and effectiveness of the method proposed in the paper,which can better explain the behavioral decision-making process of the agent in the interaction process.This study provides feasibility analysis ideas and theoretical references for improving multi-agent interactive decision-making and the interpretability of the game system model.

Integrating GPT into the Journalism and Communication Industries:The Technological Logic,Ecosystem Reconstruction,and Ethical Chal enges

Generative AI,represented by GPT(Generative Pre-trained Transformer),is now leading the technological revolution and is reconstructing the journalism and communication industries'ecosystems because of its powerful generative capacity and diverse range of outputs.While GPT is busy revolutionizing and innovating the production of news content,working patterns,and operation modes,it has also given rise to ethical concerns in regard to news authenticity,data security,humanistic values,and other related aspects.Therefore,it is imperative to initiate strategies and approaches,such as establishing a mechanism for verifying information authenticity,enhancing data security and privacy regulations,and instituting an ethical supervision and governance framework for AI,in order to facilitate the systematic advancement of AI-based news production while reinstating public trust.

Consensus model of social network group decision-making based on trust relationship among experts and expert reliability

Due to people’s increasing dependence on social networks,it is essential to develop a consensus model considering not only their own factors but also the interaction between people.Both external trust relationship among experts and the internal reliability of experts are important factors in decision-making.This paper focuses on improving the scientificity and effectiveness of decision-making and presents a consensus model combining trust relationship among experts and expert reliability in social network group decision-making(SN-GDM).A concept named matching degree is proposed to measure expert reliability.Meanwhile,linguistic information is applied to manage the imprecise and vague information.Matching degree is expressed by a 2-tuple linguistic model,and experts’preferences are measured by a probabilistic linguistic term set(PLTS).Subsequently,a hybrid weight is explored to weigh experts’importance in a group.Then a consensus measure is introduced and a feedback mechanism is developed to produce some personalized recommendations with higher group consensus.Finally,a comparative example is provided to prove the scientificity and effectiveness of the proposed consensus model.

Emancipatory reflection on a nursing practice-based ethical issue about nurses' paternalistic decision-making for patients

Objective: This study aimed to demonstrate and promote the skill of critical emancipatory reflection through reflecting on a nursing practice-based ethical issue about nurses' paternalistic decision-making for patients. Meanwhile, critical awareness will be developed and the underlying issues of paternalism in nursing decision-making will be analyzed. Then, by applying the procedure, improvement in nursing decision-making practice will be expected.Methods: Taylor's model of emancipatory reflection with four steps, including construction, deconstruction, confrontation, and reconstruction, is utilized to guide the author's reflection.Results: Guided by the socialization theory, the author's personal and professional socialization is seen to be associated with the formation of the value of paternalism. The theory of reflexivity is applied to unearth the related issues, including deeper personal value,work environment, as well as historical and cultural contexts. Moreover, the power derived from policy, work relationship, and nursing administration, which could induce paternalism in the author's nursing decision-making practice, was critically debated using the hegemony theory. Finally, new insights into paternalism will be achieved, which enable change in terms of how to facilitate patients' autonomous decision-making.Conclusions: The process of refection makes it clear that respecting patients' right and performing patient-centered caring are the bases to change the paternalism existing in the nursing decision-making practice currently. The reconstruction step assists the author in terms of how to value the patients' autonomy and balance patients' safety and choice, rather than being overprotective; carry out risk assessment, and search for strong evidence to counterbalance the positive and negative aspects of risk-taking; communicate with patients appropriately in a manner that they can comprehend; spend more time to explore patients' preference and choice; make every effort to elevate the patients' decision-making capacity; implement patient-centered care and shared decision-making in nursing practice; consult with other colleagues and obtain the required support when limitations or challenges exist; try to justify and avoid hidden paternalism behind policy or guidelines; deal with the power in hand well and fairly; and also positively face the powers that constrain the author.

Bi-level model for shared parking decision-making based on parking lot assignment simulation

In order to carry out comprehensive decision-making of multi-class shared parking measures within a region, a bilevel model assisting decision-making is proposed. The upper level selects parkers＇ average satisfaction and the violation rate during peak hours as indices in object function, and sets probability distribution models describing dynamic parking demand of each site, the feasibility of shared parking scenarios and occupancy requirements during peak hours of each parking lot as restrictions. The simulation model in the lower level sets up rules to assign each parker in the random parking demand series to the proper parking lot. An iterative method is proposed to confirm the state of each parking lot at the start of formal simulations. Besides, two patterns linking initialization and formal simulation are presented to acquire multiple solutions. The results of the numerical examples indicate the effectiveness of the model and solution methods.

DECISION-MAKING OF SLICING SCHEME IN FUSED DEPOSITION MODELING PROCESS BASED ON ANALYTICAL HIERARCHICAL PROCESS

Based on analyzing the influences of a slicing scheme on stair-stepping effect, supporting structure, efficiency and deformation, etc. , analytical hierarchical process （AHP） combining with fuzzy synthetic evaluation is introduced to make decision in slicing schemes for a processing part. The application in determining the slicing scheme for a computer mouse during prototyping shows that the method increases the rationality during decision- making and improves quality and efficiency for the prototyping part.

A Decision-Making Framework Model of Cutting Fluid Selection for Green Manufacturing and the Case Study

Pursuing the green manufacturing (GM) of products i s very beneficial in the alleviation of environment burdens. In order to reap such benefits, green manufacturing is involved in every aspect of manufacturing proc esses. During the machining process, cutting fluid is one of the main roots of e nvironmental pollution. And how to make an optimal selection for cutting fluid f or GM is an important path to reduce the environmental pollution. The objective factors of decision-making problems in the traditional selection of cutting flu id are usually two: quality and cost. But from the viewpoint of GM, environmenta l impact (E) should be considered together. In this paper, a multi-object d ecision-making model of cutting fluid selection for GM is put forward, in which the objects of Quality (Q), Cost(C) and Environmental impact (E) are considered together. In this model, E means to minimize the environmental impact, Q means to maximize the quality and C means to minimize the cost. Each objective is anal yzed in detail too. A case study on a decision-making problem of cutting fluid selection in a gear hobbing process is analyzed, and the result shows the model is practical.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

COLLISION AVOIDANCE DECISION-MAKING MODEL OF MULTI-AGENTS IN VIRTUAL DRIVING ENVIRONMENT WITH ANALYTIC HIERARCHY PROCESS

Collision avoidance decision-making models of multiple agents in virtual driving environment are studied. Based on the behavioral characteristics and hierarchical structure of the collision avoidance decision-making in real life driving, delphi approach and mathematical statistics method are introduced to construct pair-wise comparison judgment matrix of collision avoidance decision choices to each collision situation. Analytic hierarchy process （AHP） is adopted to establish the agents＇ collision avoidance decision-making model. To simulate drivers＇ characteristics, driver factors are added to categorize driving modes into impatient mode, normal mode, and the cautious mode. The results show that this model can simulate human＇s thinking process, and the agents in the virtual environment can deal with collision situations and make decisions to avoid collisions without intervention. The model can also reflect diversity and uncertainly of real life driving behaviors, and solves the multi-objective, multi-choice ranking priority problem in multi-vehicle collision scenarios. This collision avoidance model of multi-agents model is feasible and effective, and can provide richer and closer-to-life virtual scene for driving simulator, reflecting real-life traffic environment more truly, this model can also promote the practicality of driving simulator.

Shared Decision-Making after Implementation of the Chronic Care Model (CCM)—An Evaluative Approach

Background: In paternalistic models, healthcare providers’ responsibility is to decide what is best for patients. The main concern is that such models fail to respect patient autonomy and do not promote patient responsibility. Aim: To evaluate mental healthcare team members’ perceptions of their own role in encouraging elderly persons to participate in shared decision-making after implementation of the CCM. The CCM is not an explanatory theory, but an evidence-based guideline and synthesis of best available evidence. Methods: Data were collected from two teams that took part in a focus group interview, and the transcript was analysed by means of qualitative thematic analysis. Results: One overall theme emerged—Preventing the violation of human dignity based on three themes, namely, Changing understanding and attitudes, Increasing depressed elderly persons’ autonomy and Clarifying the mental healthcare team coordinator’s role and responsibility. The results of this study reveal that until recently, paternalism has been the dominant decision-making model within healthcare, without any apparent consideration of the patient perspective. Community mental healthcare can be improved by shared decision-making in which team members initiate a dialogue focusing on patient participation to prevent the violation of human dignity. However, in order to determine how best to empower the patient, team members need expert knowledge and intuition.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the Electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi time points and multi indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the Multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

Applications and advancements in animal models for antiviral research on mosquito-borne arboviruses

Vector-borne diseases caused by arthropod-borne viruses(arboviruses) are a considerable challenge to public health globally. Mosquito-borne arboviruses, such as Chikungunya, Dengue, and Zika viruses, cause a range of human illnesses and may be fatal. Currently, efforts to control these diseases still face challenges due to growing vector resistance towards insecticides, urbanization, and limited effective antiviral treatments and vaccines. Animal models are crucial in antiviral research on mosquito-borne arboviruses, playing a role in understanding disease mechanisms,vaccine development, and toxicity testing, but the application of animal models still faces the challenges of ethical considerations and animal-to-human translational success. Genetically engineered mouse models, hamster models and non-human primate(NHP) are currently used in arbovirus research, but new models such as tree shrews and novel humanized mice are emerging. In the context of Malaysian research, the use of long-tailed macaques as potential NHP models for arbovirus research is possible;however, it faces the ethical dilemma of using an endangered species for scientific purposes. Overall, animal models play a crucial role in advancing infectious disease research, but a balance between medical research and species conservation must be upheld.

Ethical decision-making in older drivers during critical driving situations: An online experiment

The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios.204 participants from North America,grouped into two age groups(18–30 years and 65 years and above),were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem.Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment.Bayesian hierarchical models were used to analyze participants’responses,response time,and acceptability of utilitarian ethical decision-making.The results showed significant pedestrian placement,age,and time-to-collision(TTC)effects on participants’ethical decisions.When pedestrians were in the right lane,participants were more likely to switch lanes,indicating a utilitarian approach prioritizing pedestrian safety.Younger participants were more likely to switch lanes in general compared to older participants.The results imply that older drivers can maintain their ability to respond to ethically fraught scenarios with their tendency to switch lanes more frequently than younger counterparts,even when the tasks interacting with an automated driving system.The current findings may inform the development of decision algorithms for intelligent and connected vehicles by considering potential ethical dilemmas faced by human drivers across different age groups.

A decision-making model of gear process for green manufacturing

A decision-making model of gear process for green manufacturing is presented, which integrates the five objectives including the time, quality, cost, resource consumption and environmental impact of gear process together into the development of a strategy. Mathematical description is provided for the multi-objectives decision-making model. The expert judgment and the multi-fuzzy assessment theory are introduced to do sensible comparisons and give quantitative results. A case study on practical cutting tool selection in gear machining demonstrates that the proposed model is applicable.