Добірка наукової літератури з теми "Managing Risk by Making Ethical Decisions"

At own risk (AOR) discharge in the paediatric setting is a complex phenomenon due to the triad of patient, caregiver, and clinician’s involvement. It would cross disciplines from legal (child protection), moral (professional conducts and legal decisions), and ethical (age, condition, and nationality) perspectives in managing these situations. There are certain ethically acceptable practices that can be approached in the decision-making process such as respecting autonomy, individual’s competence, the truth, patient’s confidentiality and avoidance of paternalism, and all conflicts of interest. We should aim for a collaborative effort in decision-making to prevent AOR. Here, we illustrate a case where parent have opted for an AOR discharge to seek for alternative medical treatment. The article discusses the ethical dilemma when dealing with potentially life-saving conditions.

The purpose of this article is to present the correlation between management of an economic entity and the development of ethical accounting dilemmas in the era of high-risk business. In the globalisation era and recurring economic crises, realisation of the objectives of a company takes place under high risk conditions. It is therefore necessary to use a proper management system. The necessary condition for making all decisions is to have relevant information. The value and relevance of these decisions depend on the quality of information which they have been based on. Lack of ethics in accounting has a direct impact on the company's management, which is based on information generated by the accounting system of the company. Ethical dilemmas arising in accounting are also ethical dilemmas arising in the process of business management.

SummaryMaking potentially critical clinical decisions in complex cases with the real risk of death by suicide is a most challenging job in psychiatry. Sadly, risk assessment and management of harm to self is a largely ignored area compared with risk of harm to others. The legal and ethical challenges are more nuanced, and contemporary training schemes and textbooks on psychiatry have not always done justice to this area, where front-line clinicians require probably most assistance. This article is an attempt to integrate the seemingly disparate threads from legal, ethical and clinical realms to assist decision-making, and it introduces a set of principles for managing these in clinical practice. It refers in particular to legislation in England and Wales, but the clinical and ethical issues discussed are universal.

This scientific article is devoted to the actual topic of application of artificial intelligence for risk analysis in the securities market. The article considers the role of artificial intelligence in analyzing data, identifying potential risks and making informed investment decisions. The research methodology is based on theoretical and empirical methods, as well as the results of domestic scientific research. The results of the study emphasize the importance of understanding and managing risk in financial markets, including the concept of portfolio and systemic risk. The author analyzes various methods of risk analysis, including statistical models, fundamental analysis, technical analysis, scenario analysis, and machine learning methods. Special attention is given to the application of neural networks, genetic algorithms, and other artificial intelligence techniques to improve price forecasting, optimal portfolio determination, and risk management. The conclusion emphasizes the promising direction of using artificial intelligence in financial analytics, but notes the need to consider potential challenges and limitations, such as market volatility, data availability and quality, interpretability of models, and ethical considerations.

Crises pose significant challenges for leaders, particularly in the management of scarce resources. The objective of this study was to explore the decision-making processes of leaders across various sectors during crisis situations, focusing on how they navigate the complexities of strategic decision-making, leadership challenges, and organizational dynamics. This qualitative study employed semi-structured interviews with 20 leaders experienced in crisis management from sectors including healthcare, emergency services, business, and non-profit organizations. Data collection aimed at achieving theoretical saturation was guided by a set of pre-determined, open-ended questions allowing for in-depth exploration of individual experiences and strategies. The interviews were transcribed, coded, and analyzed to identify recurring themes and patterns. Three main themes were identified: Strategic Decision-Making, Leadership Challenges, and Organizational Dynamics. Strategic Decision-Making encompassed risk assessment, resource allocation, long-term planning, stakeholder engagement, and decision-making styles. Leadership Challenges included communication barriers, ethical dilemmas, and stress and pressure management. Organizational Dynamics covered team dynamics, change management, leadership influence, resource management, and policy and governance. Each theme and its categories highlighted specific strategies and challenges faced by leaders in managing scarce resources effectively during crises. The study highlights the critical importance of strategic decision-making, robust communication, ethical leadership, and adaptive organizational policies in crisis management. Leaders who effectively navigate these aspects are better equipped to handle crises, suggesting a need for targeted training and policy development to enhance crisis preparedness and leadership competencies.

Background: The development of society and science, especially medical science, gives rise to new moral and ethical challenges in healthcare. Research question/objectives/hypothesis: In order to respond to the contemporary challenges that require autonomous decision-making in different work contexts, a pedagogical experiment was conducted to identify the readiness and responsiveness of current organisation of nursing higher education in Slovenia. It compared the successfulness of active learning methods online (experimental group) and in the traditional classroom (control group) and their impact on the ethical competences of nursing students. The hypothesis set in the experiment, hypothesis 1 (the experimental group will be successful and will have good achievements in comprehension and application of ethical principles) was confirmed based on pre-tests and post-tests. The hypothesis tested by the questionnaire, hypothesis 2 (according to the students, the active learning methods online in the experimental group have a positive impact on the development of ethical competences) was confirmed. Research design: The pedagogical experiment was supported by a multiple-case study that enabled the in-depth analysis of the students’ attitudes towards the active learning methods in both settings. Participants and research context: The study included Slovenian first-year nursing students (N = 211) of all the enrolled students (N = 225) at the University of Ljubljana and University of Primorska in the academic year 2010/2011. Ethical considerations: Before the study ethical permission was obtained from the managements of both participating faculties. The students were given all the necessary information of the experiment before the tutorials. Findings: No significant difference was found between the two learning settings and both had a positive impact upon learning. The results of the content analysis show that the students’ active engagement with the active learning methods in the group enables the development of ethical competences and the related communicative competences, interpersonal skills, collaboration and critical thinking. Discussion: Active learning methods in the settings compared, online and the traditional classroom, enabled the development of a higher level of knowledge defined by the ability of critical thinking and reflective response, the core of ethical competences. Students develop ethical competence through active engagement in a group work, role play and discussion, and there is no difference between online or traditional learning settings. Conclusion: In the healthcare, it is crucial for providers to be capable of making autonomous decisions and managing various communication situations and contexts in which the moral attitudes and ethical sensibility are essential.

The transformational effects of artificial intelligence (AI) on auditing procedures and financial reporting accuracy are examined in this study article. This research looks at how artificial intelligence (AI) tools, such data analytics and machine learning, are changing auditing by making it more efficient, lowering the risk of human mistake, and boosting the ability to spot fraud. The study outlines the advantages and difficulties of using AI in auditing via a thorough examination of the literature and an analysis of current trends. Based on important discoveries, AI-powered audits may greatly improve the timeliness and dependability of financial reporting, enabling stakeholders to make better decisions. However, there are drawbacks to integrating AI as well, such as the need for large training and technological expenditures as well as possible ethical and security issues. In order to fully use AI in auditing while managing the related dangers, the study ends with suggestions for practitioners and policymakers. By offering insightful information to academics, business professionals, and regulators, this study adds to the continuing conversation on auditing's future in the digital era.

Background Oesophageal cancer has significant morbidity and mortality but late diagnosis is common since early signs of disease are frequently misinterpreted. Project DELTA aims to enable earlier detection and treatment through targeted screening using a novel risk prediction algorithm for oesophageal cancer (incorporating risk factors of Barrett’s oesophagus including prescriptions for acid-reducing medications (CanPredict)), together with a non-invasive, low-cost sampling device (CytospongeTM). However, there are many barriers to implementation, and this paper identifies key ethical and legal challenges to implementing these personalised prevention strategies for Barrett’s oesophagus/oesophageal cancer. Methods To identify ethical and legal issues relevant to the deployment of a risk prediction tool for oesophageal cancer into primary care, we adopted an interdisciplinary approach, incorporating targeted informal literature reviews, interviews with expert collaborators, a multidisciplinary workshop and ethical and legal analysis. Results Successful implementation raises many issues including ensuring transparency and effective risk communication; addressing bias and inequity; managing resources appropriately and avoiding exceptionalism. Clinicians will need support and training to use cancer risk prediction algorithms, ensuring that they understand how risk algorithms supplement rather than replace medical decision-making. Workshop participants had concerns about liability for harms arising from risk algorithms, including from potential bias and inequitable implementation. Determining strategies for risk communication enabling transparency but avoiding exceptionalist approaches are a significant challenge. Future challenges include using artificial intelligence to bolster risk assessment, incorporating genomics into risk tools, and deployment by non-health professional users. However, these strategies could improve detection and outcomes. Conclusions Novel pathways incorporating risk prediction algorithms hold considerable promise, especially when combined with low-cost sampling. However immediate priorities should be to develop risk communication strategies that take account of using validated risk algorithms, and to ensure equitable implementation. Resolving questions about liability for harms arising should be a longer-term objective.

Purpose: This paper seeks to define a risk taxonomy, establish meaningful controls, and create a prospective harms model for AI risks in healthcare. Currently, there is no known comprehensive definition of AI risks, as applied to industry and society. Materials and Methods: The temptation for current research, both in academia and industry, is to apply exclusively-tech-based solutions to these complex problems; however, this view is myopic, and can be remedied by establishing effective controls informed by a holistic approach to managing AI risk. Sociotechnical Systems Theory (STS) is an attractive theoretical lens for this issue, because it prevents collapsing a multifaceted problem into a one-dimensional solution. Specifically, the multidisciplinary approach—one that includes both the sciences and the humanities—reveals a multidimensional view of technology-society interaction, exemplified by the advent of AI. Findings: After advancing this risk taxonomy, this paper utilizes the risk management framework of Lean Six Sigma (LSS) to propose effective mitigating controls for the identified risks. LSS determines controls through data collection and analysis, and supports data-driven decision making for industry professionals. Implications to Theory, Practice and Policy: Instantiating the theory of STS into industry practices could be critical, then, for determining and mitigating real-world risks from AI. In summary, this paper combines the academic theory of sociotechnical systems with the industry practice of Lean Six Sigma to develop a hybrid model to fill a gap in the literature. Drawing upon both theory and practice ensures a robust, informed risk model of AI use in healthcare.

Today, businesses are operating in a VUCA environment. In the VUCA environment, Occupational Safety and Health (OSH) skills are essential for a business’s viability and sustainability since they safeguard personnel, ensure legal compliance and standards conformance, reduce operational costs, foster productivity, elevate reputation, and exhibit social responsibility. In a VUCA environment, the risk management process acts as a pillar for business viability and sustainability. With effective risk management, businesses can use it to proactively detect and reduce risks, improve adaptation and resilience, guarantee business continuity, make better decisions, and instill confidence among stakeholders. Businesses may negotiate uncertainty, grasp opportunities, and put themselves in a position for long-term success by managing risks properly. Effective risk assessors are essential to the success of risk management because they provide accurate and trustworthy assessments of potential risks. Hence, through this study, it investigates the criticality of OSH risk assessor skills in functioning in the VUCA environment; and identifies the pedagogical preferences for effective risk assessor program. A quantitative research approach is employed for this study, utilising a three (3) parts survey comprising 25 items. The study involved fifty (50) OSH practitioners as the respondents. The Relative Importance Index (RII) results for OSH risk assessor skills in a VUCA environment, assessed on a ten-point Likert scale, are as follows: applied knowledge of the subject matter (0.88), communication skills (0.87); attention to detail (0.87); risk control techniques (0.87); ethical consideration (0.87); risk assessment methodologies (0.86); analytical thinking (0.85); critical thinking (0.85); data analysis (0.84) and adaptability (0.84). Next, respondents conveyed their preferences regarding pedagogical approaches using a ten-point Likert scale. The Relative Importance Index (RII) scores for these approaches are as follows: problem-based learning (0.83); authentic assessment (0.82); inquiry-based learning (0.81); collaborative learning (0.81); technology integration (0.81); experiential learning (0.81); cultivating creativity and innovation (0.81); project-based learning (0.80); multidisciplinary and interdisciplinary approaches (0.80) and metacognitive strategies (0.79).This study contributes to the design of the OSH risk assessor programme for assisting industries in operating in the VUCA environment by helping them to understand the vision, develop situational awareness, make complex situations clear, and generate hypotheses to address potential risks, all of which lead to more informed decision-making, increased resilience, and efficient resource use.

AbstractNewborn Bloodspot Screening (NBS) enables diagnosis and early treatment of rare diseases in non-symptomatic neonates. NBS has well-documented benefits for babies, their families, and the healthcare system at large. In recent decades, rapid advances in screening technologies enabled the proliferation of testable diseases. This has led to increased discussion of both the benefits relevant to decision-making but also the health, economic and ethical challenges associated with the expansion of NBS panels. However, technological capability is not the sole driver of panel expansions, and we suggest that decisions to add a condition to the screening panel constitute exercises in risk management. Using a risk governance lens, this chapter examines procedures that govern decision-making concerning screening panel additions in several Canadian NBS programs. Specifically, we draw on an analysis of documents in the public domain and interviews with individuals associated with Canadian NBS programs to identify the risk management tools that are applied. Our analysis indicates that there is a reliance on the advice of experts and economic controls but limited public participation in decisions about screening panels. We conclude with a discussion of why democratization might strengthen decision-making and offer recommendations to practitioners and scholars regarding next steps and future research.

Whilst digitisation is far from a new concept, many assume that simply introducing automation and information systems in various forms will be enough to make their organisation’s operations more efficient. This misconception can often lead to disarray and costly mistakes. Digital Transformation: Understanding Business Goals, Risks, Processes, and Decisions shows how to avoid such issues via careful consideration of what an enterprise really needs. Unlike many other books on digital transformation, the authors do not dwell on database design or the details of implementing information systems. Instead, they emphasise the importance of a clear understanding of all aspects of an organisation in order to effectively implement and manage digital systems, from business goals and strategies to structuring information and making decisions, risk assessments, project management, organising, and procuring services and products. Organised in eleven chapters, and drawing on examples from all over the world, this book will be of interest to university students of business administration, management, information systems, and computer science, as well as practitioners seeking to better understand how to handle digital transformation in their own organisation.

AbstractArtificial intelligence (AI) has become a pervasive presence in almost every aspect of society and business: from assigning credit scores to people, to identifying the best candidates for an employment position, to ranking applicants for admission to university. One of the most striking innovations in the United States criminal justice system in the last three decades has been the introduction of risk-assessment software, powered by sophisticated algorithms, to predict whether individual offenders are likely to re-offend. The focus of this contribution is on the use of these risk-assessment tools in criminal sentencing. Apart from the broader social, ethical and legal considerations, to date, not much is known about how perceptions of technology influence cognition in decision-making, particularly in the legal context. What research does demonstrate is that humans are inclined to trust algorithms as objective, and, as such, as unobjectionable. This contribution examines two phenomena in this regard: (i) the “technology effect”—the human tendency towards excessive optimism when making decisions involving technology; and (ii) “automation bias”—the phenomenon whereby judges accept the recommendations of an automated decision-making system, and cease searching for confirmatory evidence, perhaps even transferring responsibility for decision-making onto the machine.

AbstractDefining and managing integrated urban, river basin and climate adaptation plans towards sustainable development, good ecological status as well as reduced water-related risk is challenging. Uncertainties regarding the future of cities and river basins require these plans to be adaptive. NBS are increasingly put forward as relevant measures to cope with climate related risks and challenges. However, the greening of climate adaptation planning with NBS in a context of risk, requires a well-structured decision-making process that enables the integration of NBS into national, regional and catchment planning processes and financing structures. To facilitate this integration, it is important to connect NBS with Disaster Risk Reduction (DRR), Integrated Water Resources Management (IWRM) and Climate Change Adaptation (CCA) frameworks, amongst others. Decision-making, however, is not a one-off action. To ensure the implementability of NBS, it is necessary to take key decisions in different steps of the planning, design and management phases. The use of tools and methods in these different steps can help informed decision-making, and as a result the formulation of evidence-based, reliable and well accepted solutions.

Managing clinical concerns is a reminder that the therapeutic relationship is important throughout an ethical crisis. This chapter focuses two kinds of threat assessment: suicidal threats and threats against others. It encourages mental health professionals to help students grow through the crisis and to take a developmental approach to shared decision-making while being aware of the risk factors that impair adolescent cognition. It recommends using Vygotsky’s zone of proximal development and cultural sensitivity when addressing ethical issues. Clinicians are warned about ethnocentric reactions to child discipline and to pay attention to power dynamics when working with minority families. It ends with guidance about how to create a welcome space to discuss clinician-client differences, especially due to intersectionality.

Mental health trainees are sometimes surprised by the weighty legal and ethical responsibilities they face. The purpose of this chapter is to introduce significant legal and ethical dilemmas so that trainees are not caught unaware later on. The issues addressed include maintaining professional boundaries, protecting confidentiality, managing mandatory reporting of child or elder abuse, and assessing for suicide or homicide risk. Brief case vignettes are used to illustrate some of the challenges in ethical decision-making. The consequences of ethical violations are briefly reviewed, and a suggested model to guide ethical decision-making is provided. The intersection of academic, research, and mental health ethical codes is discussed. Finally, readers are urged to pursue aspirational ethics beyond just adherence to laws and ethical codes. Aspirational ethics include advocacy for social and racial justice, as well as other social, environmental, human rights, health, or economic causes.

It is essential in today’s socio-economic environment that pipeline operators adopt and utilize a comprehensive approach to managing technical, environmental, economic and public safety risks associated with their business. Clearly, this type of approach to risk management would be integrated and include a variety of considerations. For example, one is the technical assessment of the level of safety or risk inherent within the system itself. Another, is the external view held of that system. While the physical system and its associated risk can be identified, evaluated and to some extent controlled, the external view of the risk, however, is an entirely different matter. Making important decisions about risk requires that both the external and internal views be in agreement. When this is not the case, an integrated management plan needs to include a risk communication component. Simply, risk communication is the purposeful exchange of information about the existence, nature, form, severity or acceptability of risks.1 An effective risk communication strategy will be able to gauge the political and social reaction to a project. If pipeline operators try to establish what a project’s acceptable level of risk is without a purposeful exchange of information with the community the effort will likely fail. The need to look at the “big picture” is paramount. All factors which affect the outcome of the project need to be understood and, in some way, contribute meaningfully to the final product. The most overlooked aspect in risk management is the qualitative assessment of “how does the public perceive the risk?”. Risk analysts use many basic technical assumptions in their risk assessments. They allow their training and faith in the science to be sufficient indicators of the real risk. The public, on the other hand, view risk from a completely different perspective and set of values. Consequently, when attempts are made to quantitatively determine “what is an acceptable level of risk” the outcome must be viewed as incomplete, lacking the critical external input. Experience suggests that the only ones who can truly determine what is an acceptable level of risk are those who must ultimately accept that risk. This is where the power of effective risk communication can play a significant role in the risk management process. While risk analysis can help in understanding the potential of a risk, effective risk communication and public outreach are necessary in understanding the perceptions and concerns of the community. It seems ironic that corporations dedicate tremendous resources deriving a mathematical estimate of risk that most in the community cannot comprehend much less believe what the numbers are supposed to tell them. This paper will help to explain the fundamentals of risk communication, its ethical use and methods for developing a strategy for outreach programs as part of an integrated risk management plan.

Fatigue in aviation is defined as “a physiological state of reduced mental or physical performance capability resulting from sleep loss, extended wakefulness, circadian phase, and/or workload (mental and/or physical activity) that can impair a person’s alertness and ability to perform safety-related operational duties”. Fatigue compromises human performance and is considered an identified threat to flight safety. Fatigue is inevitable within the aviation operations context. Therefore, fatigue cannot be eliminated; it must be managed. Fatigue Risk Management System (FRMS) has recently been implemented in airline operations. FRMS is “a data-driven means of continuously monitoring and managing fatigue-related safety risks, based upon scientific principles, knowledge, and operational experience that aims to ensure relevant personnel are performing at adequate levels of alertness”. Nevertheless, studies reported prominent levels of fatigue for 68.5% to 93% among professional pilots. This implies that current FRMS strategies need to be strengthened. The ever-growing and constantly changing aviation industry mandates novel complementary approaches to enhance the established FRMS. EASA has already acknowledged the potential benefits of artificial intelligence (AI) in aviation. Implementing AI applications in FRMS could benefit both flight safety and cost efficiency. AI can analyze various sources of data to enhance real-time detection and prediction. Countermeasures could, then, be employed to address pilots’ drowsiness and mental impairments and, thus, prevent fatigue-related incidents. This study provides a holistic human-centric approach regarding AI utilization in FRMS by outlining the potential benefits and challenges. Implementing AI applications in FRMS could benefit both flight safety and cost efficiency. AI can be integrated with existing FRMS and provide a more comprehensive approach to fatigue management. Given AI’s computational capacity, it can analyze vast amounts of various sourced data to enhance real-time detection and prediction. Countermeasures could, then, be employed to address pilots’ drowsiness and mental impairment and, thus, prevent fatigue-related incidents. AI applications are promising in using pilot’s data sourced through wearable devices (e.g., smartwatches, fitness, and eye trackers) for the detection of fatigue in domains such as a) Monitoring/analyzing electroencephalogram (EEG) signal; b) Yawing detection; c) Facial muscle detection; d) Drowsiness detection; e) Pupil detection and monitor pilot fatigue levels in real-time. Additionally, AI could analyze natural language during the pilot’s communication to detect signs of fatigue. Also, AI could integrate and contribute to fatigue flight data. Moreover, AI can contribute to FRMS by identifying high-risk periods for fatigue and developing customized mitigation strategies based on individual characteristics such as circadian rhythms, sleep patterns, and workload. AI can be used to develop predictive models that can forecast the likelihood of fatigue for individual crew members based on numerous factors, such as sleep patterns and workload. These models can inform scheduling decisions and other fatigue risk management strategies. AI algorithms could also optimize crew rostering to avoid last-minute unfit-for-duty reports and prevent additional costs. On the contrary, there are considerable challenges to overcome. The reliability and validity of data used by AI systems are critical to their effectiveness in predicting and managing fatigue. Methods to measure the accuracy and consistency of data must be established and continually monitored. Additionally, there is a risk that AI systems can perpetuate or even amplify existing biases and inequalities based on training data. Regulations and legal frameworks must be established to guide the use of AI in fatigue risk management. EASA is working on a structured AI integration within the aviation industry. Personalized and sensitive data should be collected for the intended purpose. Data governance should ensure privacy and security to protect individuals. Also, some ethical considerations could be raised (e.g., the responsibility for decision-making and accountability in case of errors or incidents. Moreover, it is essential to understand how AI systems can integrate with human factors and not become a source of stress or distraction for pilots. Non-intrusive wearable AI systems’ sensor integration is of utmost importance. Implementing AI systems can be costly, and the return on investment must be carefully considered. Determining the cost-effectiveness of AI systems in fatigue risk management is essential. Lastly, resistance to change by the users could be anticipated. The Purdue research case study connects the ongoing measurement of Fatigue in aviation training (Purdue SATT student pilots) using AI applications with the commercial aviation FRMS

To aid with making risk-based pipeline management decisions, a methodology is required to evaluate the cost-benefit of various pipeline operation strategies as a function of time. This methodology should provide consideration to evaluating an existing asset with active damage mechanisms and imperfections in various states of severity. In this paper, the subject of the methodology is a typical transmission pipeline with the following properties: • Transports refined liquid products; • Mid-size diameter (NPS 8 to NPS 16); • Telescoping wall thickness based on proximity to pump stations (4 to 6 mm); • High pressure (9930 kPa); • Approximately 50 years of operating history; and • Approximately 500 km long. The objective of this analysis is to determine the best operation strategy for the subject pipeline in terms of cost-effective risk management. The methodology considered four different risk management strategies: • Operate and Maintain (O&M) at 100% of Maximum Operating Pressure (MOP): ○ A maintenance strategy involving in-line inspection and defect repair based on a function of probability and consequence of failure while operating at 100% of MOP. • Operate and Maintain (O&M) at 50% of Maximum Operating Pressure (MOP): ○ Similar to the previous strategy except an additional form of mitigation is applied by reducing the operating pressure of the pipeline to 50% of MOP. • Inspect, Repair and Re-coat (IRR): ○ A maintenance strategy involving complete excavation of the entire pipeline, inspection and repair of any defects, re-coat and burial. • Pipeline Replacement: ○ A maintenance strategy where the existing asset is abandoned and replaced with a new pipeline. To complete the analysis, two predictive models to determine probability of failure (POF) and consequence of failure (COF) were created using quantitative and semi-quantitative approaches. Consideration was given to both time dependent imperfections and time independent damage mechanisms. The effects of each risk management strategy were projected in both models over a timeline of 20 years. The results were aligned to a risk matrix with defined risk thresholds to aid in determining the acceptability of each risk management strategy. To evaluate the effectiveness of each risk management strategy, a cost-benefit ratio was used. This ratio was defined as the predicted risk reduction through the implementation of each strategy over the costs required for execution. Maximizing this ratio would represent the optimal strategy at any given point in time. Completing the analysis showed that over the short term the O&M strategy was the most cost-effective methodology to mitigate risk. However, as a pipeline ages and repairs become more frequent, the replacement strategy becomes more favorable. The analysis predicted a time interval where if the subject pipeline is to be operated beyond this point in time then replacement as soon as possible is the best strategy to employ. This time interval is different between pipelines and heavily dependent on the rate and severity of damage. The results in this paper illustrate an example and utilizing the methodology discussed will produce different results on a case-by-case basis.

Effectively managing risk is crucial to successful engineering design. Formal methods offer strategies for making decisions under uncertainty and mitigating risk. However, insights from other fields such as cognitive science and behavioral economics suggest that decision-makers may exhibit behaviors in response to feedback which can undermine these strategies. This study presents results from an experiment in which participants were tasked with selecting a design factor of safety for four design prompts under objective risk conditions. Participants were randomly assigned to receive only negative or positive feedback after each decision. Results suggest that the type of feedback influenced the choice of factor of safety even though subjects were provided with the exact benefits and probabilities of all possible outcomes. This experiment suggests further study of the mechanisms by which engineering decision-makers incorporate feedback is necessary.

Based on practical experience, the article provides recommendations for the use of adaptive methods for monitoring and managing the testing process of complex samples of mechanical engineering and instrument engineering. Considering tests as a continuous process, it is necessary to take into account that in real conditions of multi-criteria and risk, there is no possibility of its continuous change. This involves the selection of discrete process nodes that can be used for a preliminary integral assessment of the quality of the test process itself. In these discrete points, it is possible to make appropriate alternative decisions, i.e. to perform adaptive optimization of the process in accordance with the adaptive planning method.

Abstract In the course of their profession, engineers must often consider not just the technical efficacy of their designs but also how their design decisions influence and are influenced by nontechnical factors. These non-technical factors can include the stated or implicit values of a company culture, the real and/or perceived social pressures from management, and individual perceptions about one’s own ethical and professional duties and responsibilities. In the field of Psychology there is a large body of research relating the internal, mental states of individuals to their external behaviors and choices. However, at this time there has been little research into how different psychological states can affect the outcome of specific engineering design decision making by individuals or teams. This study’s aim was to begin this research by conducting an experiment to simulate a common constraint in the profession of engineering: allocating a design budget to ensure the project outcome is both profitable and safe. Specifically, this study wanted to measure how the personality trait agreeableness in conjunction with a social primer consisting of a written scenario description conveying the aims of the exercise and the responsibilities of engineers related to an engineering student’s decision to favor either profit or safety in a hypothetical design scenario. A total of 141 undergraduate engineering students were recruited to participate in this experiment, which consisted of a computer-based survey and decision-making activity with a total duration of approximately 10 minutes. Results indicated that agreeableness did not relate to primer adherence in a statistically significant way; however participant beliefs about the intention of the experiment did have a statistically significant relationship with their final allocation decisions, a finding that may have implications for the management of engineering design teams, if this research can be replicated in experienced professionally practicing engineers. While not the objective of the experiment, the data show that when participants were given the opportunity to revise their selections, they most commonly revised their allocations away from profit and towards more investment in safety. Whether this is a result of simply a second attempt at the same decision with further reflection or the result of the consideration of information considered after the initial allocation remains to be determined in future research. The results of this study should serve not as conclusive evidence on the effects of trait agreeableness in engineering risk-related decision making but rather as an initial step, or model for how to investigate a potentially valuable, interdisciplinary field of inquiry. Insights from this experiment do hold useful lessons for the next phase of this research.

Abstract Sandstone reservoir failure during hydrocarbon production can cause negative impact on the oil/gas field development economics. Loss of integrity and hydrocarbon leakage due to downhole or surface erosion can decrease the risk of operational safety. Therefore, a proper understanding of the best formulation to manage and find the balance between productivity and sand risk is very important. Making decisions for the best and most economical completion design needs a full and proper sanding risk analysis driven by geomechanics modeling. The accuracy of modeling the reservoir rock mechanical behavior and the failure analysis depends on the selection of the constitutive model (failure criteria) specially to understand the failure and post failure mechanisms. Thus, an appropriate constitutive model/criterion is required as most of the current model/criteria are not developed for a weak rock material honoring the non-linearity and post failure (softening) process. Therefore, a new and novel elasto-plastic constitutive model for sandstone rock has been investigated and developed. The effort started with a sequence of triaxial tests at different confining pressures on core samples. Different types of rock have been tested during the developing and validation of the constitutive model. Comparison with other existing failure criteria was also performed. As the results, the newly developed constitutive model is better honoring the full spectrum of elasto-plastic rock mechanical behavior (softening and post-failure) which is important for oil and gas applications, specifically for sand production and drilling i.e. failure stabilization due to stress relief. The formulation and process are demonstrated with a case study for an old gas field, where a few gas wells have been shut-in due to severe sand production. The sand production predictive models have been validated with downhole pressure. The wells have been side-tracked and recompleted using the new sand failure prediction, using the new formulation resulted in restoring sand-free production at former rates. The novelty of this study would be in finding the right formula to best design the predictive model and to avoid any sand production when using the newly developed constitutive model.

Artificial Intelligence (AI) aims to replicate human behavior in socio-technical systems, with a strong focus on AI engineering to replace human decision-making. However, an overemphasis on AI system autonomy can lead to bias, unfair, non-ethical decisions, and thus a lack of trust, resulting in decreased performance, motivation, and competitiveness. To mitigate these AI threats, developers are incorporating ethical considerations, often with input from ethicists, and using technical tools like IBM's Fairness 360 and Google's What-If tool to assess and improve fairness in AI systems. These efforts aim to create more trustworthy and equitable AI technologies. Building trustworthiness in AI technology does not necessarily imply that the human user will fundamentally trust it. For humans to use technology trust must be present, something challenging when AI lacks a permanent/stable physical embodiment. It is also important to ensure humans do not over-trust resulting in AI misuse. Trustworthiness should be assessed in relation to human acceptance, performance, satisfaction, and empowerment to make design choices that grant them ultimate control over AI systems, and the extent to which the technology meets the business context of the socio-technical system where it's used. For AI to be perceived as trustworthy, it must also align with the legal, moral, ethical principles, and behavioral patterns of its human users, whilst also considering the organizational responsibility and liability associated with the socio-technical system's business objectives. Commitment to incorporating these principles to create secure and effective decision support AI systems will offer a competitive advantage to organizations that integrate them.Based on this need, the proposed framework is a synthesis of research from diverse disciplines (cybersecurity, social and behavioral sciences, ethics) designed to ensure the trustworthiness of AI-driven hybrid decision support while accommodating the specific decision support needs and trust of human users. Additionally, it aims to align with the key performance indicators of the socio-technical environment where it operates. This framework serves to empower AI system developers, business leaders offering AI-based services, as well as AI system users, such as educators, professionals, and policymakers, in achieving a more absolute form of human-AI trustworthiness. It can also be used by security defenders to make fair decisions during AI incident handling. Our framework extends the proposed NIST AI Risk Management Framework (AI-RFM) since at all stages of the trustworthiness risk management dynamic cycle (threat assessment, impact assessment, risk assessment, risk mitigation), human users are considered (e.g., their morals, ethics, behavior, IT maturity) as well as the primary business objectives of the AI socio-technical system under assessment. Co-creation and human experiment processes must accompany all stages of system management and are therefore part of the proposed framework. This interaction facilitates the execution of continuous trustworthiness improvement processes. During each cycle of trustworthiness risk mitigation, human user assessment will take place, leading to the identification of corrective actions and additional mitigation activities to be implemented before the next improvement cycle. Thus, the main objective of this framework is to help build ‘trustworthy’ AI systems that are ultimately trusted by their users.

This research presents a comprehensive framework for managing flood risk in the Kelani River basin, employing the Analytic Hierarchy Process (AHP) and spatial analysis to enhance flood risk comprehension, support informed decision-making, and facilitate effective flood management. Initially, the framework identifies key parameters influencing flood risk, which are then used to create flood hazard and vulnerability indexes through AHP. The hazard index indicates the likelihood of a flood event, while the vulnerability index assesses potential impacts. These two indexes are combined to form an overall flood risk index. Subsequently, this index is utilized to develop a web-based spatial decision support system (SDSS), enabling businesses and stakeholders to visualize and analyze flood risk information, aiding them in making well-informed decisions regarding flood mitigation and adaptation measures. This research offers valuable insights for policymakers and authorities in the Kelani River basin, fostering resilience and sustainable development in the region. Though the study acknowledges limitations related to data availability and generalization to other regions, it serves as a valuable foundation for the development of more comprehensive and effective flood risk management frameworks in the Kelani River basin and beyond.

Artificial Intelligence (AI) is a rapidly advancing field encompassing different applications across different industries. Managements of big multinational organisations and even local medium-sized enterprises are using AI for improving efficiency, productivity, decision-making, and overall business performance. Firms’ human resource management (HRM) integrates AI and other applications based on AI for managing people within organisations. Utilising AI for talent management involves leveraging artificial intelligence techniques and tools to optimise various aspects of the employee lifecycle, from recruitment and selection to employee development and engagement. leveraging AI in talent management can update recruitment processes, enhance decision-making, and enable personalised employee development. It has the potential to optimise HR operations and improve overall workforce management for organisations. While AI offers numerous benefits in talent management, challenges arise in terms of data quality and privacy, potential lack of human judgment in complex decisions, ethical considerations related to biases in AI algorithms, user acceptance and trust, and the need for a skilled and adaptable workforce. This study aims to investigate the challenges and opportunities of using AI for talent management within organisations to assist them in making informed decisions and implementing effective strategies to harness the potential of AI in optimising their talent acquisition and development efforts. Both primary and secondary data will be collected. An interview method will be applied to collect primary data from different organisations’ HR managers. Secondary data will be gathered from different organisations’ published reports and articles along with other academic reliable resources. The findings of this research will provide valuable insights for companies aiming to apply AI effectively in talent management strategies by overcoming the challenges.

This is the 14th monthly Humanitarian Evidence Summary (HUMES) to signpost FCDO and other UK government departments to the latest relevant evidence and discourse on humanitarian action to inform and support their response. It is the result of 1 day of work per month and is not intended to be a comprehensive summary of available evidence on humanitarian action but aims to make original documents easily accessible to decision-makers that, if relevant to them, they could refer to before making decisions. This summary covers publications on Enhancing protection and humanitarian access; Needs assessment and analysis; Accountability to affected populations; Cash programming; Managing risk better, preparedness and anticipation; Resilience and protracted crisis; Other and Resource Hubs.

This is the 12th monthly Humanitarian Evidence Summary (HUMES) to signpost FCDO and other UK government departments to the latest relevant evidence and discourse on humanitarian action to inform and support their response. It is the result of 1 day of work per month and is not intended to be a comprehensive summary of available evidence on humanitarian action but aims to make original documents easily accessible to decision-makers that, if relevant to them, they could refer to before making decisions. This summary covers publications on Enhancing protection and humanitarian access; Needs assessment and analysis; Accountability to affected populations; Cash programming; Managing risk better, preparedness and anticipation; Other; and Resource Hubs.

This is the 15th monthly Humanitarian Evidence Summary (HUMES) to signpost FCDO and other UK government departments to the latest relevant evidence and discourse on humanitarian action to inform and support their response. It is the result of 1 day of work per month and is not intended to be a comprehensive summary of available evidence on humanitarian action but aims to make original documents easily accessible to decision-makers that, if relevant to them, they could refer to before making decisions. This summary covers publications on Enhancing protection and humanitarian access; Needs assessment and analysis; Accountability to affected populations; Cash programming; Managing risk better, preparedness and anticipation; Resilience and protracted crisis; Other; and Resource Hubs.

This is the 11th monthly Humanitarian Evidence Summary (HUMES) to signpost FCDO and other UK government departments to the latest relevant evidence and discourse on humanitarian action to inform and support their response. It is the result of 1 day of work per month and is not intended to be a comprehensive summary of available evidence on humanitarian action but aims to make original documents easily accessible to decision-makers that, if relevant to them, they could refer to before making decisions. This summary covers publications on Enhancing protection and humanitarian access; Needs assessment and analysis; Accountability to affected populations; Cash programming; Managing risk better, preparedness and anticipation; Resilience and protracted crisis; and Resource Hubs

This is the 13th monthly Humanitarian Evidence Summary (HUMES) to signpost FCDO and other UK government departments to the latest relevant evidence and discourse on humanitarian action to inform and support their response. It is the result of 1 day of work per month and is not intended to be a comprehensive summary of available evidence on humanitarian action but aims to make original documents easily accessible to decision-makers that, if relevant to them, they could refer to before making decisions. This summary covers publications on Enhancing protection and humanitarian access; Needs assessment and analysis; Cash programming; Managing risk better, preparedness and anticipation; Resilience and protracted crisis; Other and Resource Hubs.

When carrying out professional activities, officers of the VNG of the Russian Federation are often in difficult, stressful, emotionally stressful situations associated with the use of weapons as a particularly dangerous means of destruction. The right to use a weapon by an officer makes him responsible for its use. And therefore requires the officer to make a balanced optimal decision, which is associated with the risk and transience of events, and in which no mistake can be made, since the price of it can be someone's life. It is at such a moment that it is important that the officer has stable skills in making a decision on the use of weapons, and this requires skills not only in managing subordinates or the situation,but in managing himself. The complication of the military-professional activity, manifested in the need to develop the ability to quickly and accurately make command decisions, exacerbating the problem of social responsibility of an officer who has the management of unit that leads to an understanding of his singular personal and professional responsibility, as the ability to govern themselves makes it possible to achieve a positive result of the Department for the DBA. This characterizes the need for a commander to have the ability to manage himself, as a "system" that manages others. Forming skills of self-control, patience, compassion, having mastered algorithms of making managerial decisions, the cycle of implementing managerial functions, etc., a person comes to the belief: "before effectively managing others, it is necessary to learn how to manage yourself." The required level of personal and professional maturity can be formed in a person as a result of purposeful self-management, which determines the special role of professional and personal self-management in the training of future officers.

Banco de la República is celebrating its 100th anniversary in 2023. This is a very significant anniversary and one that provides an opportunity to highlight the contribution the Bank has made to the country’s development. Its track record as guarantor of monetary stability has established it as the one independent state institution that generates the greatest confidence among Colombians due to its transparency, management capabilities, and effective compliance with the central banking and cultural responsibilities entrusted to it by the Constitution and the Law. On a date as important as this, the Board of Directors of Banco de la República (BDBR) pays tribute to the generations of governors and officers whose commitment and dedication have contributed to the growth of this institution.1 Banco de la República’s mandate was confirmed in the National Constitutional Assembly of 1991 where the citizens had the opportunity to elect the seventy people who would have the task of drafting a new constitution. The leaders of the three political movements with the most votes were elected as chairs to the Assembly, and this tripartite presidency reflected the plurality and the need for consensus among the different political groups to move the reform forward. Among the issues considered, the National Constitutional Assembly gave special importance to monetary stability. That is why they decided to include central banking and to provide Banco de la República with the necessary autonomy to use the instruments for which they are responsible without interference from other authorities. The constituent members understood that ensuring price stability is a state duty and that the entity responsible for this task must be enshrined in the Constitution and have the technical capability and institutional autonomy necessary to adopt the decisions they deem appropriate to achieve this fundamental objective in coordination with the general economic policy. In particular, Article 373 established that “the State, through Banco de la República, shall ensure the maintenance of the purchasing power of the currency,” a provision that coincided with the central banking system adopted by countries that have been successful in controlling inflation. In 1999, in Ruling 481, the Constitutional Court stated that “the duty to maintain the purchasing power of the currency applies to not only the monetary, credit, and exchange authority, i.e., the Board of Banco de la República, but also those who have responsibilities in the formulation and implementation of the general economic policy of the country” and that “the basic constitutional purpose of Banco de la República is the protection of a sound currency. However, this authority must take the other economic objectives of state intervention such as full employment into consideration in their decisions since these functions must be coordinated with the general economic policy.” The reforms to Banco de la República agreed upon in the Constitutional Assembly of 1991 and in Act 31/1992 can be summarized in the following aspects: i) the Bank was assigned a specific mandate: to maintain the purchasing power of the currency in coordination with the general economic policy; ii) the BDBR was designatedas the monetary, foreign exchange, and credit authority; iii) the Bank and its Board of Directors were granted a significant degree of independence from the government; iv) the Bank was prohibited from granting credit to the private sector except in the case of the financial sector; v) established that in order to grant credit to the government, the unanimous vote of its Board of Directors was required except in the case of open market transactions; vi) determined that the legislature may, in no case, order credit quotas in favor of the State or individuals; vii) Congress was appointed, on behalf of society, as the main addressee of the Bank’s reporting exercise; and viii) the responsibility for inspection, surveillance, and control over Banco de la República was delegated to the President of the Republic. The members of the National Constitutional Assembly clearly understood that the benefits of low and stable inflation extend to the whole of society and contribute mto the smooth functioning of the economic system. Among the most important of these is that low inflation promotes the efficient use of productive resources by allowing relative prices to better guide the allocation of resources since this promotes economic growth and increases the welfare of the population. Likewise, low inflation reduces uncertainty about the expected return on investment and future asset prices. This increases the confidence of economic agents, facilitates long-term financing, and stimulates investment. Since the low-income population is unable to protect itself from inflation by diversifying its assets, and a high proportion of its income is concentrated in the purchase of food and other basic goods that are generally the most affected by inflationary shocks, low inflation avoids arbitrary redistribution of income and wealth.2 Moreover, low inflation facilitates wage negotiations, creates a good labor climate, and reduces the volatility of employment levels. Finally, low inflation helps to make the tax system more transparent and equitable by avoiding the distortions that inflation introduces into the value of assets and income that make up the tax base. From the monetary authority’s point of view, one of the most relevant benefits of low inflation is the credibility that economic agents acquire in inflation targeting, which turns it into an effective nominal anchor on price levels. Upon receiving its mandate, and using its autonomy, Banco de la República began to announce specific annual inflation targets as of 1992. Although the proposed inflation targets were not met precisely during this first stage, a downward trend in inflation was achieved that took it from 32.4% in 1990 to 16.7% in 1998. At that time, the exchange rate was kept within a band. This limited the effectiveness of monetary policy, which simultaneously sought to meet an inflation target and an exchange rate target. The Asian crisis spread to emerging economies and significantly affected the Colombian economy. The exchange rate came under strong pressure to depreciate as access to foreign financing was cut off under conditions of a high foreign imbalance. This, together with the lack of exchange rate flexibility, prevented a countercyclical monetary policy and led to a 4.2% contraction in GDP that year. In this context of economic slowdown, annual inflation fell to 9.2% at the end of 1999, thus falling below the 15% target set for that year. This episode fully revealed how costly it could be, in terms of economic activity, to have inflation and exchange rate targets simultaneously. Towards the end of 1999, Banco de la República announced the adoption of a new monetary policy regime called the Inflation Targeting Plan. This regime, known internationally as ‘Inflation Targeting,’ has been gaining increasing acceptance in developed countries, having been adopted in 1991 by New Zealand, Canada, and England, among others, and has achieved significant advances in the management of inflation without incurring costs in terms of economic activity. In Latin America, Brazil and Chile also adopted it in 1999. In the case of Colombia, the last remaining requirement to be fulfilled in order to adopt said policy was exchange rate flexibility. This was realized around September 1999, when the BDBR decided to abandon the exchange-rate bands to allow the exchange rate to be freely determined in the market.Consistent with the constitutional mandate, the fundamental objective of this new policy approach was “the achievement of an inflation target that contributes to maintaining output growth around its potential.”3 This potential capacity was understood as the GDP growth that the economy can obtain if it fully utilizes its productive resources. To meet this objective, monetary policy must of necessity play a countercyclical role in the economy. This is because when economic activity is below its potential and there are idle resources, the monetary authority can reduce the interest rate in the absence of inflationary pressure to stimulate the economy and, when output exceeds its potential capacity, raise it. This policy principle, which is immersed in the models for guiding the monetary policy stance, makes the following two objectives fully compatible in the medium term: meeting the inflation target and achieving a level of economic activity that is consistent with its productive capacity. To achieve this purpose, the inflation targeting system uses the money market interest rate (at which the central bank supplies primary liquidity to commercial banks) as the primary policy instrument. This replaced the quantity of money as an intermediate monetary policy target that Banco de la República, like several other central banks, had used for a long time. In the case of Colombia, the objective of the new monetary policy approach implied, in practical terms, that the recovery of the economy after the 1999 contraction should be achieved while complying with the decreasing inflation targets established by the BDBR. The accomplishment of this purpose was remarkable. In the first half of the first decade of the 2000s, economic activity recovered significantly and reached a growth rate of 6.8% in 2006. Meanwhile, inflation gradually declined in line with inflation targets. That was how the inflation rate went from 9.2% in 1999 to 4.5% in 2006, thus meeting the inflation target established for that year while GDP reached its potential level. After this balance was achieved in 2006, inflation rebounded to 5.7% in 2007, above the 4.0% target for that year due to the fact that the 7.5% GDP growth exceeded the potential capacity of the economy.4 After proving the effectiveness of the inflation targeting system in its first years of operation, this policy regime continued to consolidate as the BDBR and the technical staff gained experience in its management and state-of-the-art economic models were incorporated to diagnose the present and future state of the economy and to assess the persistence of inflation deviations and expectations with respect to the inflation target. Beginning in 2010, the BDBR established the long-term 3.0% annual inflation target, which remains in effect today. Lower inflation has contributed to making the macroeconomic environment more stable, and this has favored sustained economic growth, financial stability, capital market development, and the functioning of payment systems. As a result, reductions in the inflationary risk premia and lower TES and credit interest rates were achieved. At the same time, the duration of public domestic debt increased significantly going from 2.27 years in December 2002 to 5.86 years in December 2022, and financial deepening, measured as the level of the portfolio as a percentage of GDP, went from around 20% in the mid-1990s to values above 45% in recent years in a healthy context for credit institutions.Having been granted autonomy by the Constitution to fulfill the mandate of preserving the purchasing power of the currency, the tangible achievements made by Banco de la República in managing inflation together with the significant benefits derived from the process of bringing inflation to its long-term target, make the BDBR’s current challenge to return inflation to the 3.0% target even more demanding and pressing. As is well known, starting in 2021, and especially in 2022, inflation in Colombia once again became a serious economic problem with high welfare costs. The inflationary phenomenon has not been exclusive to Colombia and many other developed and emerging countries have seen their inflation rates move away from the targets proposed by their central banks.5 The reasons for this phenomenon have been analyzed in recent Reports to Congress, and this new edition delves deeper into the subject with updated information. The solid institutional and technical base that supports the inflation targeting approach under which the monetary policy strategy operates gives the BDBR the necessary elements to face this difficult challenge with confidence. In this regard, the BDBR reiterated its commitment to the 3.0% inflation target in its November 25 communiqué and expects it to be reached by the end of 2024.6 Monetary policy will continue to focus on meeting this objective while ensuring the sustainability of economic activity, as mandated by the Constitution. Analyst surveys done in March showed a significant increase (from 32.3% in January to 48.5% in March) in the percentage of responses placing inflation expectations two years or more ahead in a range between 3.0% and 4.0%. This is a clear indication of the recovery of credibility in the medium-term inflation target and is consistent with the BDBR’s announcement made in November 2022. The moderation of the upward trend in inflation seen in January, and especially in February, will help to reinforce this revision of inflation expectations and will help to meet the proposed targets. After reaching 5.6% at the end of 2021, inflation maintained an upward trend throughout 2022 due to inflationary pressures from both external sources, associated with the aftermath of the pandemic and the consequences of the war in Ukraine, and domestic sources, resulting from: strengthening of local demand; price indexation processes stimulated by the increase in inflation expectations; the impact on food production caused by the mid-2021 strike; and the pass-through of depreciation to prices. The 10% increase in the minimum wage in 2021 and the 16% increase in 2022, both of which exceeded the actual inflation and the increase in productivity, accentuated the indexation processes by establishing a high nominal adjustment benchmark. Thus, total inflation went to 13.1% by the end of 2022. The annual change in food prices, which went from 17.2% to 27.8% between those two years, was the most influential factor in the surge in the Consumer Price Index (CPI). Another segment that contributed significantly to price increases was regulated products, which saw the annual change go from 7.1% in December 2021 to 11.8% by the end of 2022. The measure of core inflation excluding food and regulated items, in turn, went from 2.5% to 9.5% between the end of 2021 and the end of 2022. The substantial increase in core inflation shows that inflationary pressure has spread to most of the items in the household basket, which is characteristic of inflationary processes with generalized price indexation as is the case in Colombia. Monetary policy began to react early to this inflationary pressure. Thus, starting with its September 2021 session, the BDBR began a progressive change in the monetary policy stance moving away from the historical low of a 1.75% policy rate that had intended to stimulate the recovery of the economy. This adjustment process continued without interruption throughout 2022 and into the beginning of 2023 when the monetary policy rate reached 12.75% last January, thus accumulating an increase of 11 percentage points (pp). The public and the markets have been surprised that inflation continued to rise despite significant interest rate increases. However, as the BDBR has explained in its various communiqués, monetary policy works with a lag. Just as in 2022 economic activity recovered to a level above the pre-pandemic level, driven, along with other factors, by the monetary stimulus granted during the pandemic period and subsequent months, so too the effects of the current restrictive monetary policy will gradually take effect. This will allow us to expect the inflation rate to converge to 3.0% by the end of 2024 as is the BDBR’s purpose.Inflation results for January and February of this year showed declining marginal increases (13 bp and 3 bp respectively) compared to the change seen in December (59 bp). This suggests that a turning point in the inflation trend is approaching. In other Latin American countries such as Chile, Brazil, Perú, and Mexico, inflation has peaked and has begun to decline slowly, albeit with some ups and downs. It is to be expected that a similar process will take place in Colombia in the coming months. The expected decline in inflation in 2023 will be due, along with other factors, to lower cost pressure from abroad as a result of the gradual normalization of supply chains, the overcoming of supply shocks caused by the weather, and road blockades in previous years. This will be reflected in lower adjustments in food prices, as has already been seen in the first two months of the year and, of course, the lagged effect of monetary policy. The process of inflation convergence to the target will be gradual and will extend beyond 2023. This process will be facilitated if devaluation pressure is reversed. To this end, it is essential to continue consolidating fiscal sustainability and avoid messages on different public policy fronts that generate uncertainty and distrust. 1 This Report to Congress includes Box 1, which summarizes the trajectory of Banco de la República over the past 100 years. In addition, under the Bank’s auspices, several books that delve into various aspects of the history of this institution have been published in recent years. See, for example: Historia del Banco de la República 1923-2015; Tres banqueros centrales; Junta Directiva del Banco de la República: grandes episodios en 30 años de historia; Banco de la República: 90 años de la banca central en Colombia. 2 This is why lower inflation has been reflected in a reduction of income inequality as measured by the Gini coefficient that went from 58.7 in 1998 to 51.3 in the year prior to the pandemic. 3 See Gómez Javier, Uribe José Darío, Vargas Hernando (2002). “The Implementation of Inflation Targeting in Colombia”. Borradores de Economía, No. 202, March, available at: https://repositorio.banrep.gov.co/handle/20.500.12134/5220 4 See López-Enciso Enrique A.; Vargas-Herrera Hernando and Rodríguez-Niño Norberto (2016). “The inflation targeting strategy in Colombia. An historical view.” Borradores de Economía, No. 952. https://repositorio.banrep.gov.co/handle/20.500.12134/6263 5 According to the IMF, the percentage change in consumer prices between 2021 and 2022 went from 3.1% to 7.3% for advanced economies, and from 5.9% to 9.9% for emerging market and developing economies. 6 https://www.banrep.gov.co/es/noticias/junta-directiva-banco-republica-reitera-meta-inflacion-3