The University of Buckingham Press Journals
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AI and Artists: Navigating Ethics, Regulation, and the Impact of AI on Artistic Practice
Full text linkAdvances in Artificial Intelligence (AI) have captured public interest, especially with the advent of generative AI technologies like ChatGPT and Dall-E. These tools, which create text, images, and videos rapidly and often for free, promise transformative impacts on society, economy, and culture. However, for artists, generative AI raises significant practical, ethical, and philosophical questions. A 2023 survey by DACS revealed artists’ concerns about AI’s impact on their work, data privacy, and the spread of misinformation. While some see AI as a positive tool, many demand safeguards and regulations, emphasising the need for consent and compensation when AI uses their work
Operational Intelligence and the Spanish Guardia Civil’s Carteia Plan: An Exploratory Thematic Analysis of Police Officer Perceptions and Experiences
Full text linkIntroduction: This exploratory study examines the effectiveness of intelligence services in combating drug trafficking in southern Spain, with a focus on the integrated efforts of the Spanish Guardia Civil’s Carteia Plan and its Regional Analysis and Intelligence Center against Drug Trafficking (CRAIN). The purpose is to assess, through the police officers’ experience, how these initiatives enhance operational information collection and intelligence to counteract the pervasive threat of drug trafficking in the Campo de Gibraltar region.Methods: Building on previous research, a qualitative approach was employed to conduct this paper, incorporating a survey and interviews with both law enforcement and intelligence personnel. The study also involved a comprehensive review of policy documents and operational reports from the Guardia Civil and CRAIN to evaluate their integrated intelligence model.Results: The findings highlight that the integrated intelligence and operational strategies conducted by CRAIN in close collaboration with the Guardia Civil’s GAR special operation group significantly improve the efficacy of not only drug interdiction efforts, but also of any strategy against organized crime. The plan’s coordinated initiatives have led to a notable increase in drug seizures and arrests, demonstrating the effectiveness of enhanced intelligence gathering and inter-agency cooperation.Conclusions: The research concludes that an integrated intelligence framework is essential for effectively combating organized crime. The implementation of the Carteia Plan and CRAIN’s functioning underscores the importance of comprehensive and adaptive approaches. Policy recommendations include fostering stronger inter-agency collaboration and promoting a transversal intelligence culture across different operational units, essential to address the dynamic and multifaceted nature of drug trafficking
Assessing Deception Projection via OSINT: The Case of the Ukraine 2022 Counter-Offensive
Full text linkIntroduction: As the intelligence community observed the evolution of open-source intelligence (OSINT) and the development of the extensive data landscape, several new challenges to traditional approaches to warfighting emerged. One of these challenges was the increasing intensity of the illusory truth effect and its effects on operational timeline planning. How effective are these Emerging Disruptive Technologies (EDT)-driven open sources in projecting a battlespace deception, and what are the limitations and risks? To offer a substantive answer to this question, this study will use the Russian war of aggression against Ukraine as a case study specifically focusing on a projected deception using OSINT in support of the Ukrainian Kherson Offensive, which began on August 29, 2022, and the Kharkiv Offensive, which started in September 2022.Methods: The analysis aimed to identify and quantify instances where the Ukrainian deception storyline was repeated across various media outlets and social media platforms. It used an OSINT scraper to aggregate and filter the data. Then, a simple quantitative analysis was used to cross-reference the intensity of the illusory truth effect with the Russian operational timeline for troop movements, and a conclusion was drawn.Results: The number of ‘hits’ scrapped during a specific period was unexpectedly high, indicating a high level of engagement from both mobile and desktop devices. The data revealed a clear connection between increasing illusory truth intensity and Russian troop movements in the field. The study also pointed out the limitations of large-scale social media data in confidently establishing cause-and-effect relationships between influence and physical actions. It also demonstrated how the growing risk of the illusory truth effect, driven by OSINT and unrestricted military access to social media, could potentially compromise the compartmentalised operational command and control of military organisations through the personal devices of individuals involved in the command-and-control processes.
Conclusion: In an information environment enhanced by EDT, the illusory truth effect is a powerful tool for deceptive projection in the information domain. This effect is amplified if access is gained to compartmentalised operational decision-making processes within the target warfighting organisation. Consequently, from an operational security perspective, the intelligence community must address the threat of an illusory truth breach of command & control processes via OSINT collection in an EDT-enhanced information environment
Predicting Motor-Vehicle Deaths Using Machine Learning: Proposed 8E-Model
No full textThis study conducts a comprehensive time series analysis of motor-vehicle fatalities in the USA spanning from 2019 to 2021, revealing a troubling upward trajectory. Factors such as over-speeding, impaired driving, reduced road traffic enforcement during the pandemic, and instances of driving under the influence have significantly contributed to the surge in fatal crashes during this period. Utilizing the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, this research forecasts the trajectory of motor vehicle deaths in the USA. The forecast suggests a continuation of the upward trend, emphasizing the urgency of addressing the escalating fatalities. In response to the burgeoning global trend of increasing accidents and fatalities, this study advocates for the implementation of broader preventive measures worldwide. Proposed strategies encompass the crucial role of policy implementation and road safety measures in curbing the rising toll of road accidents, particularly in the USA.Furthermore, this study extends the existing 7E model (Education, Engineering, Enforcement, Exposure, Examination of Competence and Fitness, Emergency Response, and Evaluation) by introducing the eighth ‘E’—Empathy—in the context of road safety. This augmentation creates the 8E model, offering a more encompassing framework adaptable on a global scale. The inclusion of empathy underscores the significance of considering human emotions, behaviours, and societal impact in crafting effective road safety initiatives
Call to Action Industry Article: Start-up IP in Academic Private Sector Partnerships - Who Owns it Really?
Full text linkNew Global Governance and Overarching Frameworks: Reimagining the Rule of Law, AI and ESG for the Betterment of the World
Full text linkThe advancement of digital technologies, particularly in Artificial Intelligence (AI), the geopolitical fragmentation of Environment, Social, and Governance (ESG) with a lack of mandatory international governance, calls for increased global cooperation and integration in overarching central conceptual and of action frameworks. As humanity faces critical environmental challenges—such as climate extremes and biodiversity loss and wars—the disparities between rich and poor become more evident and the planet displays its illness. Addressing these challenges requires collective social change, underpinned by shared operating systems, open-source models, and quality data. Humanity’s fragmented relationshipwith nature highlights the need for a robust global governance system. As AI and ESG matters transcend national borders, there is a growing need for internationalframeworks, such as the involvement of the International Court of Justice (ICJ) to resolve disputes and the rule of law, both at national and international levels to be interconnected, ensuring that legal frameworks complement each other. A shift toward “sust-AI-nability,” grounded in human reason, science- and fact-based, with values- and risk-based must coordinate cooperation, essential for managing global challenges, foster meaningful transformation, and advance the United Nations’ Sustainable Development Goals (SDGs)
Regenerative Urbanism: Enriching Places for People and the Planet
Full text linkRegenerative urbanism enriches places for people and the planet by building upon existing strengths through meaningful community engagement. This article describes the process for achieving regenerative urbanism. This process may be applied to the United Nations’ Sustainable Development Goal 11: Sustainable Cities and Communities, and complements the methods described in Goal 17 – building global partnerships that mobilize and direct resources – for effectively realizing all the other goals
Machine Learning Models Comparison for Bankruptcy Predication for Indian Companies: A study based on India’s Insolvency and Bankruptcy Code (IBC ‘2016)
No full textIt is essential to recognize that dynamics of bankruptcy events vary across regions and legal frameworks. In this context, the paper aims to fill the critical gap in literature by presenting an analysis of machine learning (ML) models for early detection of bankruptcy probability among Indian companies operating under the Insolvency and Bankruptcy Code (IBC) of 2016. This study distinguishes itself by leveraging an extensive dataset covering the period from FY 2016 to FY 2022, encompassing 65,583 entries for 7,008 unique corporations, including 257 bankrupt entities. This paper employs various predictive variables, including traditional financial ratios, Altman Z-scores, and comprehensive financial statement data, employing a scenario-based approach over a one-year forecasting horizon. The findings support the notion that ML models, particularly XGBoost, outperform traditional logistic regression models and Altman Z-scores in accurately predicting bankruptcy among Indian corporates. These findings align with the trend in the literature favoring ML models for enhanced predictive power, offering valuable insights for financial institutions and policymakers in India’s corporate landscape
Blockchain Based Prediction Markets
Full text linkPrediction markets are a form of collective intelligence that leverage market mechanisms to incentivise large numbers of individuals to make forecasts about future uncertain events. Since their origin in the 1980’s, they have been the subject of a small but steady stream of academic research. Proponents suggest that they have several advantages over comparable information aggregation mechanisms such as polls or expert groups. More recently the rise of blockchain, cryptocurrencies and decentralised finance (DeFi) has excited new interest in prediction markets. The characteristics of this triad of technologies has particular resonances with prediction markets. This research identifies the potential impact of blockchain technology on prediction market design and performance with a view to informing a research agenda to investigate those potential impacts
Volatility Spillovers Between Financial Markets and Cryptocurrencies
No full textThis paper analyses the relationships between the volatilities of five major stock markets (S&P 500, CAC 40, DAX, FTSE 100, and Nikkei 225) and five cryptocurrencies (Bitcoin, Dash, Ethereum, Monero, and Ripple), (WTI), and gold. The GARCH model, which describes the volatility of financial assets and cryptocurrencies, was used. A significant and higher volatility spillover was observed across these market pairs. The conditional correlation between Bitcoin and other cryptocurrencies is time-varying, but the conditional correlations between crypto-currencies and gold and all assets are negative during the period (2017-2018) and positive. At the beginning of the COVID-19 crisis, the conditional correlation between cryptocurrencies, stock indices, and WTI increased, which confirms the impact of COVID-19 related contagion between them.Our findings show that cryptocurencies and gold are considered hedges for the international investors during the period 2017-2018