An Activity System-based Perspective of Generative AI: Challenges and Research Directions

With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of artificial general intelligence. To understand the challenges, potential impact, and implications associated with GAI, we adopt a socio-technical perspective to analyze them. First, we identify the key characteristics of GAI, which include content generation, generalization ability, and reinforcement learning based on human feedback. Next, we address technological, ethical, societal, economic, regulatory, and governance challenges. Finally, we deploy activity theory to explore research directions in GAI. Research questions that warrant further investigation include how GAI may impact the future of work, how GAI can collaborate effectively with humans, and how we can improve the transparency of GAI models as well as mitigate biases and misinformation in GAI to achieve ethical and responsible GAI

Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond

Artificial Intelligence Generated Content (AIGC) is one of the latest achievements in AI development. The content generated by related applications, such as text, images and audio, has sparked a heated discussion. Various derived AIGC applications are also gradually entering all walks of life, bringing unimaginable impact to people's daily lives. However, the rapid development of such generative tools has also raised concerns about privacy and security issues, and even copyright issues in AIGC. We note that advanced technologies such as blockchain and privacy computing can be combined with AIGC tools, but no work has yet been done to investigate their relevance and prospect in a systematic and detailed way. Therefore it is necessary to investigate how they can be used to protect the privacy and security of data in AIGC by fully exploring the aforementioned technologies. In this paper, we first systematically review the concept, classification and underlying technologies of AIGC. Then, we discuss the privacy and security challenges faced by AIGC from multiple perspectives and purposefully list the countermeasures that currently exist. We hope our survey will help researchers and industry to build a more secure and robust AIGC system.Comment: 43 pages, 10 figure

The Biometric Evolution of Sound and Space

Auditoria in the late 20th and 21st centuries have evolved into a series of spatial conventions that are an established and accepted norm. The relationship between space and music now exists in a decoupled condition, and music is no longer reliant on volumetric and material conditions to define its form (Glantz 2000). This thesis looks at a series of novel approaches to investigate how the links between music and space can be reconnected though evolutionary computation, parametric modelling, virtual acoustics and biometric sensing. The thesis describes in detail the experiments undertaken in developing methodologies in linking music, space and the body. The thesis will show how it is possible to develop new form finding and musical generation tools that allow new room shapes and acoustic measures to inform how new acoustic and musical forms can be developed unconsciously and objectively by a listener, in response to sound and site

Predição para o uso da inteligência artificial no agronegócio na Caatinga

A ciência e a tecnologia, em diferentes formas, sempre exerceram um papel expressivo na solução de problemas, sendo usadas para o desenvolvimento de estratégias, produtos, métodos e ferramentas. Os avanços em ciência e tecnologia têm se mostrado promissores no intuito de aprimorar setores como o agronegócio. E essa visão tem sido justificada pelo constante avanço de dispositivos tecnológicos projetados para apresentar soluções aos problemas agrícolas. Sendo assim, este estudo tem por objetivo analisar o processo de inovação no contexto da Inteligência Artificial (IA), desde a produção do conhecimento científico até a fase de predição dessa tecnologia no agronegócio na Caatinga. Do ponto de vista dos aspectos metodológicos a pesquisa é classificada como exploratória, uma vez que essa investigação leva em consideração uma área na qual há pouco conhecimento acumulado e sistematizado. Em relação à técnica de pesquisa, é caracterizada como estudo de caso. Os resultados da aplicação dos métodos da IA no agronegócio no contexto geral apresentam diferentes abordagens como o uso de Visão de Máquina por meio de Sistema Agrícola Virtual, SVM e ELM na detecção precoce do patógeno de pragas e doenças; FIS e MLP para a exploração de culturas; propagação reversa para monitoramento dos limites da fazenda; ANN e MFNN para análise de estruturas de irrigação; e Árvore da Decisão e TDNN para a vigilância do rebanho. Com os dispositivos integrados no sistema de produção agrícola os sistemas das fazendas passam a oferecer recomendações e insights mais ricos para a tomada de decisão e melhoria da cadeia de suprimentos agrícola. Em relação ao levantamento das tecnologias atuais no agronegócio na Caatinga, o contexto local apresenta abordagens bem distintas, desde a utilização de técnicas de convivência com o semiárido como os métodos de manejo do solo, aproveitamento da água da chuva e preparo de ração animal. Já a análise do uso das tecnologias, o enfoco está na viabilidade da produção, diversificação e manejo da colheita em polos integrados de grande desenvolvimento tecnológico em polos de cultivo e manejo de culturas irrigadas. A perspectiva da adoção e o desenvolvimento de IA no agronegócio na Caatinga ainda se encontram em fase inicial, com os agentes buscando nas pesquisas, conhecer as oportunidades dessa tecnologia frente aos negócios no setor agrícola. Na Caatinga, os estudos ainda são reduzidos, mas já há exemplos como rastreabilidade de carne, predição da produtividade da palma forrageira, delineamento de zonas de manejo ou mesmo na estimativa da evapotranspiração de referência. Contudo, há etapas que devem ser superadas até a integração da IA como a habilidade de entender e manusear as ferramentas com IA e a integração dos sistemas dentro da cadeia de suprimentos. Já os resultados do levantamento sistemático apresentam ações como modelagem e previsão do fluxo de água; evapotranspiração; variabilidade, avaliação de terra; previsão de época ótima de semeadura e seleção de cultivares. De modo que, os achados apresentam os diferentes usos da IA, com iniciativas de sustentabilidade habilitadas por mudanças no sistema agrícola atual.Science and technology, in different forms, have always played an expressive role in problem solving, being used for the development of strategies, products, methods and tools. Advances in science and technology have shown promise in order to improve sectors such as agribusiness. And this vision has been justified by the constant advancement of technological devices designed to present solutions to agricultural problems. Therefore, this study aims to analyze the innovation process in the context of artificial intelligence, from the production of scientific knowledge to the prediction phase of this technology in agribusiness in the Caatinga. From the point of view of methodological aspects, the research is classified as exploratory, since this investigation takes into account an area in which there is little accumulated and systematized knowledge. Regarding the research technique, it is characterized as a case study. The results of the application of AI methods in agribusiness in the general context present different approaches such as the use of Machine Vision through Virtual Agricultural System, SVM and ELM in the early detection of the pathogen of pests and diseases; FIS and MLP for the exploitation of cultures; reverse propagation for monitoring farm boundaries; ANN and MFNN for analysis of irrigation structures; and Decision Tree and TDNN for herd surveillance. With the devices integrated into the agricultural production system. farm systems now offer richer recommendations and insights for decision making and agricultural supply chain improvement. Regarding the survey of current technologies in agribusiness in the Caatinga, the local context presents very different approaches, from the use of technologies of coexistence with the semi-arid region or social techniques such as methods of soil management, use of rainwater and preparation of feed animal. Even the use of technologies themselves aimed at the viability of production, diversification and management of the harvest in integrated poles of great technological development in poles of cultivation and management of irrigated cultures. The perspective of the adoption and development of AI in agribusiness in the Caatinga is still at an early stage, with agents seeking, in research, to know the opportunities of this technology in relation to business in the agricultural sector. In the Caatinga, studies are still very limited, but there are already examples such as meat traceability, prediction of forage cactus productivity, delineation of management zones or even in the estimation of reference evapotranspiration. However, there are steps that must be overcome until the integration of AI such as the ability to understand and handle the tools with AI and the integration of systems within the supply chain. On the other hand, the results of the systematic survey present actions such as modeling and forecasting the water flow; evapotranspiration; variability, land assessment; prediction of optimal sowing time and selection of cultivars. So, the findings present the different uses of AI, with sustainability initiatives enabled by changes in the current agricultural system