REPRODUÇÃO EM NOVILHAS LEITEIRAS -/- INTRODUÇÃO -/- O principal objetivo da criação de substitutos em gado leiteiro é produzir uma novilha que tenha seu parto aos dois anos de idade (23 a 25 meses) e com um peso de 550 a 580 kg. O manejo reprodutivo das novilhas começa quando estas atingem 14 ou 15 meses de idade e um peso de 350 a 370 kg. A produção de novilhas deve ser suficiente para substituir as vacas descartadas anualmente (25 a (...) 35%), e para contribuir com o crescimento do rebanho. Espera-se que em um gado leiteiro deva haver uma população de animais de reposição, desde um dia de vida até à fase de novilha ao parto, correspondendo pelo menos a 70 % do total das vacas (figura 1). -/- Figura 1: A meta do programa de produção de substitutos ou fêmeas de reposição consiste em uma novilha que chegue ao seu primeiro parto aos 24 ou 25 meses de idade, entre um peso de 550 a 580 kg. Elaborado pelo autor. -/- A produção de novilhas depende basicamente de três fatores: da fertilidade das vacas, ou seja, do número de bezerras nascidas anualmente; da mortalidade durante a criação e desenvolvimento; e da eficiência reprodutiva das novilhas. O manejo reprodutivo moderno das novilhas é orientado para a utilização da inseminação artificial, seja em um estro natural ou sincronizado. As novilhas representam a população animal geneticamente mais avançada no rebanho, portanto, o mérito genético de suas crias obtidas por inseminação é maior do que o das crias das vacas adultas. Além disso, as crias das novilhas obtidas mediante a inseminação aceleram o avanço genético, uma vez que contribuem com uma proporção maior de substituições do rebanho em comparação com as crias das vacas de outras faixas etárias. Além disso, as novilhas são as fêmeas mais férteis do rebanho (porcentagem de concepção: 60 a 70% vs 30 a 40% em vacas), pelo que o custo do sêmen por gestação é menor em comparação com as vacas adultas, o que permite investir em melhores touros e em sêmen sexado. -/- 1. PUBERDADE -/- A puberdade é definida como a fase de desenvolvimento em que a fêmea apresenta o seu primeiro estro fértil. Regularmente as novilhas leiteiras, sob condições ótimas de manejo, chegam à puberdade entre 11 e 12 meses de idade, ou seja, antes de alavancar o peso recomendado para receber o primeiro serviço. Vale salientar que as novilhas podem ficar gestantes após a puberdade; no entanto, isto não é conveniente porque ainda não completou-se o seu desenvolvimento. Se ficarem gestantes nos primeiros ciclos estrais, as novilhas poderiam chegar ao parto com pouco desenvolvimento físico, o que provocaria distocias e baixa produção de leite (figura 2). A ativação do sistema neuroendócrino para que a bezerra atinja a puberdade é regulada principalmente pelo estado nutricional (condição corporal). A transição do anestro pré-puberal à ciclicidade puberal coincide com um aumento da condição corporal e das concentrações de insulina, IGF-I e leptina. Estes hormônios agem como sinais metabólicos no hipotálamo e hipófise que modificam a frequência de secreção das gonadotropinas, resultando na maturação folicular e ovulação. O atraso em relação à puberdade está diretamente relacionado com deficiências na alimentação; esta condição verifica-se em criações pouco tecnificadas, principalmente de pequenos e médios produtores. As novilhas que já atingiram o peso para receber o primeiro serviço e não apresentaram estro, devem ser examinadas por via retal para excluir possíveis anormalidades do desenvolvimento, tais como freemartinismo ou hipoplasia genital. -/- Figura 2: O fator mais importante que determina a puberdade é a nutrição. Bezerras bem alimentadas apresentam ciclos estrais aos 11 meses de idade e devem ser inseminadas aos 14 ou 15 meses de idade, com um peso de 350 a 370 kg. Acervo pessoal do autor. -/- 2. DETECÇÃO DE ESTRO E INSEMINAÇÃO ARTIFICIAL -/- A baixa eficiência na detecção de estros é o problema que mais afeta a eficiência reprodutiva das novilhas. De acordo com a duração do estro (8 a 18 horas), a observação das novilhas em períodos de 30 minutos durante a manhã e à tarde, permite detectar em estro até 70% das fêmeas, enquanto a observação contínua (24 horas) aumenta a eficiência na detecção até 95% (figuras 3 e 4). No manejo tradicional dos rebanhos leiteiros, as novilhas recebem pouca atenção por parte dos trabalhadores, o que resulta em baixa eficiência na detecção de estros (50 a 60%). Em diferença das vacas adultas em lactação, as novilhas estão menos expostas a fatores que diminuem a expressão do estro, portanto, com uma rotina de observação, de pelo menos duas horas na manhã (6h a 8h da manhã) e duas horas pela tarde até a noite (17h da tarde a 19h da noite), pode-se detectar até 90% das fêmeas no estro (figura 5). -/- Figura 3: O fator que mais influencia a idade ao primeiro parto é a baixa eficiência na detecção de estros, pelo que é recomendável a observação de estros com pessoal qualificado, em períodos de pelo menos duas horas pela manhã e duas à tarde. Acervo pessoal do autor. -/- Figura 4: Com a observação contínua é possível alcançar de 90 a 95% de eficiência na detecção de estros. Acervo pessoal do autor. -/- Figura 5: A inseminação deve ser realizada durante o período de receptividade sexual. Com boa eficiência na detecção de estros, a inseminação pode ser praticada no programa AM-PM e PM-AM, ou em apenas um turno de inseminação pela manhã (10:00), com bons resultados. -/- 3. TAXA DE PRENHEZ -/- O melhor indicador de eficiência reprodutiva é a taxa de prenhez. Este indicador refere-se à proporção de animais gestantes do total elegível para inseminação, num período equivalente a um ciclo estral. Como já se descreveu no trabalho Fisiologia do Estro e do Serviço na Reprodução Bovina, este indicador considera a eficiência na detecção de estros e a porcentagem de concepção, e reflete com maior objetividade a eficácia do manejo reprodutivo. Este parâmetro pode ser melhorado através de um aumento da proporção de novilhas detectadas em estro, o que se obtém aumentando o tempo de observação e aplicando técnicas de sincronização do estro (figura 6). -/- 4. INSEMINAÇÃO DE NOVILHAS COM SÊMEN SEXADO -/- A utilização de sêmen sexado é uma boa opção para a produção de novilhas de reposição. Com a nova tecnologia disponível para a separação de espermatozoides com o cromossomo x, é possível alcançar até 90% de crias fêmeas; no entanto, o processo de separação de espermatozoides tem baixa eficiência, o que limita o número de espermatozoides por palheta. As palhetas de inseminação com sêmen sexado contém de dois a três milhões de espermatozoides (doses de sêmen não sexado têm de 20 a 30 milhões). De acordo com os dados de fertilidade de gados comerciais, as novilhas inseminadas com sêmen sexado mostram de 10 a 20% menor concepção que novilhas inseminadas com sêmen não sexado, o que desencoraja o seu uso. Causas de baixa fertilidade não são conhecidas, no entanto, estão associadas com a menor concentração espermática e com alguns danos nos espermatozoides provocados pelo processo de separação. No entanto, o uso de sêmen sexado é uma opção viável para aumentar a produção de novilhas no rebanho, e com o melhoramento dos processos de separação espermática em pouco tempo se converterá em uma prática de rotina nos estábulos (figura 7). -/- Figura 6: Uma técnica que aumenta a eficiência na detecção dos estros consiste em pintar a região da grupa. Quando esta pintura desaparece ou se nota que as novilhas estão "talhadas", devem ser apalpadas via retal para determinar se existem sinais genitais de estro. Acervo pessoal do autor. -/- Figura 7: As novilhas são as fêmeas mais férteis do rebanho, por isso o custo do sêmen por gestação é menor em comparação com as vacas adultas, o que permite investir em melhores touros e em sêmen sexado. Acervo pessoal do autor. 5. MONTA DIRIGIDA -/- A monta dirigida ou direta é uma opção prática e eficaz para emprenhar as novilhas. Neste sistema se introduz um touro com um grupo de novilhas, para que ele se encarregue de encontrar as fêmeas em estro e proceder a monta. Em rebanhos comerciais, o ideal é a utilização de um touro para 25 fêmeas. No entanto, com este manejo perde-se a oportunidade de utilizar a inseminação artificial e, com isso, a possibilidade de melhoria genética. -/- 6. PROGRAMAS DE SINCRONIZAÇÃO DE ESTROS -/- Os tratamentos para sincronizar o estro das novilhas possuem os mesmos fundamentos que os utilizados nas vacas. -/- 6.1 Prostaglandina F2a -/- A PGF2α é utilizada para a sincronização de estros em grupos de novilhas, e também é utilizada para a indução do estro individualmente, nas fêmeas que são examinadas por via retal e têm um corpo lúteo. A resposta dos animais tratados é variável; em novilhas pode-se alcançar até 95% de animais em estro. O tempo de manifestação do estro após a injeção é de 48 a 120 horas. -/- 6.1.1 Dupla injeção de PGF2a -/- Além da sincronização dos animais selecionados pela presença de um corpo lúteo diagnosticado por palpação retal, existem dois programas que não incluem a palpação retal. Por exemplo, na segunda-feira, ou no dia preferido, injeta-se PGF2α em todas as novilhas que se deseja inseminar. Cerca de 50% das novilhas manifestarão estro nas próximas 48 a 120 horas. As fêmeas que não mostrarem estro receberão uma segunda injeção na segunda-feira seguinte (intervalo de sete dias). As que apresentaram estro com a primeira injeção teriam um corpo lúteo nesse momento, enquanto as que não o manifestaram estavam em estro ou em metaestro; assim, ao repetir o tratamento sete dias depois, estas últimas novilhas teriam um corpo lúteo e responderiam à PGF2α (figura 8). No outro programa, é administrada duas doses de PGF2α com 11 dias de separação/intervalo. As novilhas podem ser inseminadas no estro observado, após qualquer uma das duas injeções. Este programa oferece uma boa sincroniza- ção após a segunda injeção e é o programa de escolha na sincronização das novilhas receptoras de embriões (figura 9). -/- Figura 8: Sincronização do estro com dupla injeção de PGF2a com 7 dias de diferença/intervalo. Elaborado pelo autor. -/- Figura 9: Sincronização do estro com dupla injeção de PGF2a com 11 dias de diferença/intervalo. Elaborado pelo autor. -/- 6.2 Progestágenos -/- Existe um tratamento que consiste na inserção, na parte externa da orelha, de um implante que contém norgestomet, que permanece na região auricular por nove dias. Além disso, o tratamento é complementado com a injeção intramuscular de valerato de estradiol e norgestomet, no momento da colocação do implante. O tempo de apresentação do estro a partir da remoção do implante é de 48 a 72 horas e a proporção de animais em estro muitas vezes se torna maior do que 80%. Outro tratamento é baseado na inserção intravaginal de dispositivos de liberação de progesterona. O dispositivo pode ser utilizado durante 12 dias ou o período de exposição pode ser encurtado, desde que seja acompanhado da injeção de uma dose luteolítica de PGF2α, um dia antes ou no momento da remoção do dispositivo. A fertilidade global conseguida após o serviço no estro sincronizado é similar à obtida no estro natural; porém, algumas novilhas são menos férteis, o que está associado com alterações no desenvolvimento folicular e alterações na relação temporal entre o estro e a ovulação. Observou-se que o tratamento com implantes de norgestomet combinados com a injeção de valerato de estradiol pode induzir comportamento estral em animais que não estão ciclando normalmente. Isso ocorre porque os níveis de estradiol, administrados no primeiro dia, persistem até o momento da remoção do implante. Assim, ao remover a fonte do progestágeno e ao haver concentrações altas de estradiol se desencadeia o estro, o qual em novilhas anéstricas não é acompanhado de ovulação, enquanto que em novilhas ciclando se altera a relação temporal entre o estro, pico pré-ovulatório de LH e ovulação. Bons resultados são alcançados quando o valerato de estradiol não é administrado e é substituído por uma injeção de PGF2α no momento da remoção do implante. Outro fator que tem sido associado com baixa fertilidade é o dia do ciclo em que o tratamento começa. Observou-se que quando coincide com a presença de um corpo lúteo (diestro), a porcentagem de concepção é maior do que quando não há um corpo lúteo (proestro). Isto ocorre porque a concentração sérica do progestágeno, por si só, não é capaz de suprimir a secreção pulsátil de LH, o que faz com que o folículo dominante presente no momento de iniciar o tratamento não sofra atresia e persista até o dia da retirada do progestágeno, convertendo-se no folículo ovulatório. Com isso, o folículo já envelheceu e o ovócito já sofreu alterações que reduzem o seu potencial para desenvolver um embrião viável. Quando o tratamento coincide com a presença de um corpo lúteo, a secreção de LH é efetivamente suprimida devido ao efeito aditivo da progesterona secretada pelo corpo lúteo e do progestágeno exógeno, inserido na vaca, o que provoca a reposição folicular. Em condições de campo, a seleção das vacas pela presença de um corpo lúteo antes de iniciar o tratamento com progestágenos é impraticável, uma vez que não é possível visualizá-lo, além disso essa prática/seleção não faria sentido, já que seria mais fácil tratar estes animais com dose ou doses de PGF2α. Atualmente existem tratamentos para eliminar folículos dominantes e promover uma nova onda folicular. -/- 6.3 Progestágenos orais -/- O acetato de melengestrol (MGA) é um progestágeno administrado por via oral. Em fêmeas bovinas é utilizado para melhorar a eficiência alimentar nos currais de engorda, o que se consegue através da inibição da apresentação do estro. Como todos os progestágenos, o MGA inibe a secreção de LH, eliminando assim a maturação do folículo e a ovulação. Após a remoção do MGA, o folículo dominante termina o seu desenvolvimento e as fêmeas apresentam estro em forma sincronizada. A dose de MGA por novilha é de 0,5 a 1 mg por dia, em tratamentos que variam de 9 a 14 dias. A apresentação comercial de MGA contém 0,22 mg do hormônio por 1 g do produto. O MGA pode ser facilmente misturado com qualquer concentrado ou grão moído. Após o último dia de tratamento, o estro se apresenta de dois a seis dias. O intervalo de remoção do MGA ao estro é mais longo quando comparado com outros progestágenos. Isto deve-se ao tempo de remoção do MGA, uma vez que enquanto um implante ou dispositivo intravaginal é removido abruptamente, o MGA pode continuar a ser absorvido enquanto é removido do trato gastrointestinal. Com tratamentos de 14 dias podem-se obter porcentagens de concepção menores em comparação com o estro natural, o que se deve em grande parte à ovulação de folículos persistentes. Um tratamento eficaz, que também melhora a fertilidade, consiste na administração de MGA durante 14 dias, seguido de uma injeção de PGF2α 15 ou 17 dias após a remoção do progestágeno. Com este programa, uma alta proporção de fêmeas teriam um corpo lúteo no momento da injeção da PGF2α e apresentariam estro com boa sincronização. Outro tratamento eficaz consiste na administração do MGA durante nove dias, mais uma dose de PGF2α ao nono dia; com este programa também se obtêm bons resultados em sincronização do estro e fertilidade. Este tratamento foi avaliado com novilhas holandesas e a porcentagem de fêmeas sincronizadas é elevada (95%). A porcentagem de concepção é semelhante à obtida no estro natural. Estes resultados são comparáveis aos obtidos com outros programas, como implantes de norgestomet ou dispositivos intravaginais de liberação de progesterona, mas com um custo significativamente menor (figura 10). -/- 6.4 Sincronização da ovulação e inseminação em tempo fixo -/- Em contraste com o observado em vacas em lactação, a resposta das novilhas aos programas de sincronização da ovulação e inseminação a tempo fixo é deficiente, o que se reflete em porcentagens de concepção de 20 a 35% menores que as novilhas inseminadas no estro natural. A causa desta resposta está relacionada com diferenças no desenvolvimento folicular; assim, nas novilhas o tempo de desenvolvimento do folículo dominante é mais rápido e o tempo de domínio é mais curto do que nas vacas em lactação. Desta forma, o folículo da onda folicular sincronizada com a injeção de GnRH sofre atresia antes da injeção de PGF2α, de tal forma que quando se induz a ovulação com a segunda injeção de GnRH, as novilhas têm folículos em diferentes estádios de desenvolvimento, o que provoca assincronia entre a ovulação e a inseminação artificial. -/- Figura 10: Programa de sincronização do estro com Acetato de Melengestrol (MGA). Elaborado pelo autor. -/- 7. MANEJO DO ANESTRO -/- Uma vez que as novilhas atingem a puberdade, apresentam ciclos estrais em intervalos de 21 dias que só são interrompidos pela gestação ou por alguma patologia. O anestro patológico é raro em novilhas; no entanto, surgem casos de piometra e cistos luteinizados, que são tratados com uma dose de PGF2α. Também se observam anormalidades de desenvolvimen- to, tais como freemartinismo e hipoplasia genital, patologias que não têm tratamento; somente 8% das novilhas freemartin são férteis. O anestro funcional (as novilhas manifestam estro, mas não são detectadas) é frequen- te e está diretamente relacionado com a eficiência na detecção de estros. As novilhas com idade e peso para se integrarem no programa reprodutivo e não apresentarem sinais de estro devem ser examinadas retalmente para diagnosticar a causa do anestro. Se, durante a palpação retal, as novilhas tiverem um corpo lúteo são tratadas nesse momento com PGF2α, os animais sem corpo lúteo podem receber uma injeção de PGF2α, sete dias depois. Este programa sincroniza o estro e aumenta a probabilidade de o detectar (figura 11). -/- Figura 11: As novilhas com idade e peso para se integrarem no programa reprodutivo e não mostrarem sinais de estro devem ser verificadas via retal para diagnosticar a causa do anestro. Arquivo pessoal do autor. -/- 8. MANEJO DA NOVILHA INFÉRTIL -/- A fertilidade das vacas leiteiras diminuiu nos últimos 30 anos, enquanto a fertilidade das novilhas não se alterou; após a primeira inseminação, entre 60 e 70% das novilhas emprenham. O objetivo do programa reprodutivo é conseguir que 90% das novilhas gestem nos primeiros três serviços. Desta forma, esta proporção de animais daria à luz antes dos 25 meses de idade. É comum que 10% das novilhas se transformem em animais repetidores, ou seja, novilhas com mais de três serviços inférteis. A causa da falha na concepção de novilhas deve-se principalmente à morte embrionária precoce. Uma causa importante da falha na concepção das novilhas repetidoras são as patologias adquiridas no aparelho reprodutivo; é comum encontrar aderências ovarianas e salpingite. Provavelmente, esses problemas são consequência de alguma infecção adquirida durante a criação. Diversos tratamentos hormonais têm sido testados para resolver o problema de infertilidade em novilhas repetidoras e os resultados obtidos ainda são deficientes. Como estes tratamentos não apresentam resultados consistentes, a melhor forma de mitigar o problema de infertilidade nas novilhas é melhorando as práticas de inseminação, ou seja, o momento da inseminação, o manejo do sêmen e a técnica de inseminação empregada. Além disso, a melhor técnica para aumentar a proporção de novilhas prenhes no rebanho é aumentar a eficiência da detecção de estros. -/- 9. RESUMO -/- As novilhas devem parir aos dois anos de idade (23 a 25 meses). O peso ao parto deve ser de 550 a 580 kg. O manejo reprodutivo começa aos 14 ou 15 meses de idade, com um peso de 350 a 370 kg. As palhetas de sêmen sexado contêm de 2 a 3 milhões de espermatozoides. As doses de sêmen não sexado contêm de 20 a 30 milhões de espermatozoides. A porcentagem de concepção das novilhas inseminadas com sêmen sexado é 10 a 20% menor do que com sêmen não sexado. Com sêmen sexado se obtém entre 90 e 95% de fêmeas. A porcentagem de concepção com programas de IATF é de 20 a 35% menor que nas novilhas inseminadas no estro natural. Cerca de 90% das novilhas devem ficar prenhes nos primeiros três serviços. Devem ser produzidas novilhas para substituir as vacas que são descartadas anualmen- te (25 a 35%). Espera-se que um gado leiteiro tenha ao dispor uma população de animais de reposição, desde um dia de vida até a etapa de novilha ao parto, correspondente a, pelo menos, 70 % do total das vacas. -/- REFERÊNCIAS BIBLIOGRÁFICAS -/- AUAD, Alexander Machado et al. Manual de bovinocultura de leite. Brasília: LK Editora, 2010. BRICKELL, J. S.; MCGOWAN, M. M.; WATHES, D. C. Effect of management factors and blood metabolites during the rearing period on growth in dairy heifers on UK farms. Domestic animal endocrinology, v. 36, n. 2, p. 67-81, 2009. DE VRIES, A. et al. Exploring the impact of sexed semen on the structure of the dairy industry. Journal of Dairy Science, v. 91, n. 2, p. 847-856, 2008. Fertilidade em Vacas Leiteiras: Fisiologia e Manejo. Fisiologia do Estro e do Serviço na Reprodução Bovina. FERREIRA, A. M. Manejo reprodutivo de bovinos leiteiros: práticas corretas e incorretas, casos reais, perguntas e respostas. Edição do autor, Juiz de Fora, 2012. FERREIRA, A. de M. Reprodução da fêmea bovina: fisiologia aplicada e problemas mais comuns (causas e tratamentos). Juiz de Fora: Minas Gerais–Brasil, p. 422, 2010. GALINA, Carlos; VALENCIA, Javier. Reproducción de los animales domésticos. 2006. GONÇALVES, J. N. Manual do produtor de leite. Viçosa, MG: Aprenda Fácil, 2012. HEINRICHS, A. J. Raising dairy replacements to meet the needs of the 21st century. Journal of dairy science, v. 76, n. 10, p. 3179-3187, 1993. HOFFMAN, P. C. Optimum body size of Holstein replacement heifers. Journal of Animal Science, v. 75, n. 3, p. 836-845, 1997. NEIVA, R. S. Criação eficiente de bezerros e novilhas. Lavras: Autor, 2013. NEIVA, Rogério Santoro. Produção de bovinos leiteiros. Lavras: UFLA, 1998. PEREIRA, E. S. et al. Novilhas leiteiras. Graphiti Gráfica e Editora LTDA, Fortaleza, Ceará, 2010. CARVALHO, B. C. Manejo reprodutivo de novilhas leiteiras. In. SENAR. Curso de reprodução e genética em bovinocultura de leite. Coronel Pacheco: Senar, 2021. YOUNGQUIST, Robert S.; THRELFALL, W. R. Large animal theriogenology. 2007. (shrink)

For an artificial agent to be morally praiseworthy, its rules for behaviour and the mechanisms for supplying those rules must not be supplied entirely by external humans. Such systems are a substantial departure from current technologies and theory, and are a low prospect. With foreseeable technologies, an artificial agent will carry zero responsibility for its behavior and humans will retain full responsibility.

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...) 97.50 % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, (...) such as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a (...) ‘good AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. (...) Additionally, it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

Some of the systems used in natural language generation (NLG), a branch of applied computational linguistics, have the capacity to create or assemble somewhat original messages adapted to new contexts. In this paper, taking Bernard Williams’ account of assertion by machines as a starting point, I argue that NLG systems meet the criteria for being speech actants to a substantial degree. They are capable of authoring original messages, and can even simulate illocutionary force and speaker meaning. Background intelligence embedded in (...) their datasets enhances these speech capacities. Although there is an open question about who is ultimately responsible for their speech, if anybody, we can settle this question by using the notion of proxy speech, in which responsibility for artificial speech acts is assigned legally or conventionally to an entity separate from the speech actant. (shrink)

In their Why Machines Will Never Rule the World, Landgrebe and Smith (2023) argue that it is impossible for artificial general intelligence (AGI) to succeed, on the grounds that it is impossible to perfectly model or emulate the “complex” “human neurocognitive system”. However, they do not show that it is logically impossible; they only show that it is practically impossible using current mathematical techniques. Nor do they prove that there could not be any other kinds of theories than those (...) in current use. Even if perfect theories were impossible or unlikely, perfection may not be needed and may even be unhelpful. (shrink)

The logical problem of artificial intelligence—the question of whether the notion sometimes referred to as ‘strong’ AI is self-contradictory—is, essentially, the question of whether an artificial form of life is possible. This question has an immediately paradoxical character, which can be made explicit if we recast it (in terms that would ordinarily seem to be implied by it) as the question of whether an unnatural form of nature is possible. The present paper seeks to explain this paradoxical kind (...) of possibility by arguing that machines can share the human form of life and thus acquire human mindedness, which is to say they can be intelligent, conscious, sentient, etc. in precisely the way that a human being typically is. (shrink)

En On the Origin of Species Darwin distingue explícitamente entre tres tipos de selección: la selección natural, la artificial y la sexual. En este trabajo, a partir de un estudio más sistemático que historiográfico, se intenta encontrar la relación entre estos tres tipos de selección en la obra de Darwin. Si bien la distinción entre estos distintos mecanismos es de suma importancia en la obra de Darwin, la tesis de este trabajo es que tanto la selección artificial como (...) la sexual no son mecanismos distintos de la selección natural. Particularmente se sostiene que la selección artificial y la sexual son casos de la natural, y por esto sirven para su contrastación. (shrink)

Generative AI systems like ChatGPT and Midjourney can produce prose or images. But can they produce art? I argue that this question, though natural and intriguing, is the wrong one to ask. A better question is this: can generative AI yield distinct or novel forms of aesthetic value? And I argue that the answer is yes. Generative AI can be used to put us in contact with the artificial sublime – a type of aesthetic value that Kant famously argues (...) is impossible. Kant claims that sublimity (a fusion of trepidation and wonderment) can only arise from encounters with nature, or perhaps close artistic depiction of natural scenes. I show how generative AI can yield encounters both with incalculable profundity (Kant’s mathematical sublime) as well as overwhelming moral chaos (Kant’s dynamical sublime). There are lessons not only for art criticism, but also for the philosophical theory of value. (shrink)

Why would we want to develop artificial human-like arithmetical intelligence, when computers already outperform humans in arithmetical calculations? Aside from arithmetic consisting of much more than mere calculations, one suggested reason is that AI research can help us explain the development of human arithmetical cognition. Here I argue that this question needs to be studied already in the context of basic, non-symbolic, numerical cognition. Analyzing recent machine learning research on artificial neural networks, I show how AI studies could (...) potentially shed light on the development of human numerical abilities, from the proto-arithmetical abilities of subitizing and estimating to counting procedures. Although the current results are far from conclusive and much more work is needed, I argue that AI research should be included in the interdisciplinary toolbox when we try to explain the development and character of numerical cognition and arithmetical intelligence. This makes it relevant also for the epistemology of mathematics. (shrink)

While philosophers hold that it is patently absurd to blame robots or hold them morally responsible [1], a series of recent empirical studies suggest that people do ascribe blame to AI systems and robots in certain contexts [2]. This is disconcerting: Blame might be shifted from the owners, users or designers of AI systems to the systems themselves, leading to the diminished accountability of the responsible human agents [3]. In this paper, we explore one of the potential underlying reasons for (...) robot blame, namely the folk's willingness to ascribe inculpating mental states or "mens rea" to robots. In a vignette-based experiment (N=513), we presented participants with a situation in which an agent knowingly runs the risk of bringing about substantial harm. We manipulated agent type (human v. group agent v. AI-driven robot) and outcome (neutral v. bad), and measured both moral judgment (wrongness of the action and blameworthiness of the agent) and mental states attributed to the agent (recklessness and the desire to inflict harm). We found that (i) judgments of wrongness and blame were relatively similar across agent types, possibly because (ii) attributions of mental states were, as suspected, similar across agent types. This raised the question - also explored in the experiment - whether people attribute knowledge and desire to robots in a merely metaphorical way (e.g., the robot "knew" rather than really knew). However, (iii), according to our data people were unwilling to downgrade to mens rea in a merely metaphorical sense when given the chance. Finally, (iv), we report a surprising and novel finding, which we call the inverse outcome effect on robot blame: People were less willing to blame artificial agents for bad outcomes than for neutral outcomes. This suggests that they are implicitly aware of the dangers of overattributing blame to robots when harm comes to pass, such as inappropriately letting the responsible human agent off the moral hook. (shrink)

As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from (...) diverse fields to identify open problems, striving to synchronize research agendas and accelerate XAI in practical applications. By fostering collaborative discussion and interdisciplinary cooperation, we aim to propel XAI forward, contributing to its continued success. Our goal is to put forward a comprehensive proposal for advancing XAI. To achieve this goal, we present a manifesto of 27 open problems categorized into nine categories. These challenges encapsulate the complexities and nuances of XAI and offer a road map for future research. For each problem, we provide promising research directions in the hope of harnessing the collective intelligence of interested stakeholders. (shrink)

This paper explores the theological and philosophical implications of artificial intelligence (AI) and Neuroscience research on the Christian’s notion of the human person. The paschal mystery of Christ is the intuitive foundation of Christian anthropology. In the intellectual history of the Christianity, Platonism and Aristotelianism have been employed to articulate the Christian philosophical anthropology. The Aristotelian systematization has endured to this era. Since the modern period of the Western intellectual history, Aristotelianism has been supplanted by the positive sciences as (...) the standard scientific and philosophical interpretative framework for many. This paper argues that there is need for a new Christian anthropology based on the interpretation of the paschal mystery of Christ that is consistent with contemporary science and philosophy, especially as informed by research in AI and neuroscience. Christian anthropology today ought to be fully aware of the theological and philosophical implications of AI and neuroscience research. This paper denotes this new Christian anthropology as neuro-theological Christian anthropology. (shrink)

There is an underappreciated respect in which the widespread availability of generative artificial intelligence (AI) models poses a threat to human connection. My central contention is that human creativity is especially capable of helping us connect to others in a valuable way, but the widespread availability of generative AI models reduces our incentives to engage in various sorts of creative work in the arts and sciences. I argue that creative endeavors must be motivated by curiosity, and so they must (...) disclose the creative agent’s inquisitive self. It is through self-disclosure, including the disclosure of the inquisitive self, that we put ourselves in a position to be seen by and connect with others through our creative pursuits. Because relying on AI for certain generative tasks is less self-disclosive than the creative work such technologies supplant, this reliance threatens to weaken our connections to one another. (shrink)

In most domains of human life, we are willing to accept that there are experts with greater knowledge and competencies that distinguish them from non-experts or laypeople. Despite this fact, the very recognition of expertise curiously becomes more controversial in the case of “moral experts”. Do moral experts exist? And, if they indeed do, are there ethical reasons for us to follow their advice? Likewise, can emerging technological developments broaden our very concept of moral expertise? In this article, we begin (...) by arguing that the objections that have tried to deny the existence (and convenience) of moral expertise are unsatisfactory. After that, we show that people have ethical reasons to ask for a piece of moral advice in daily life situations. Then, we argue that some Artificial Intelligence (AI) systems can play an increasing role in human morality by becoming moral experts. Some AI-based moral assistants can qualify as artificial moral experts and we would have good ethical reasons to use them. (shrink)

Artificial agents create significant moral opportunities and challenges. Over the last two decades, discourse has largely focused on the concept of a ‘responsibility gap.’ We argue that this concept is incoherent, misguided, and diverts attention from the core issue of ‘control gaps.’ Control gaps arise when there is a discrepancy between the causal control an agent exercises and the moral control it should possess or emulate. Such gaps present moral risks, often leading to harm or ethical violations. We propose (...) a second-order ‘duty of moral control’ that mandates closing these gaps to reduce risks within acceptable moral limits. Our analysis encompasses both autonomous machines and collective agents, acknowledging their similarities and key differences in constitution and moral status. We suggest four methods to close control gaps: ensuring artificial agents attain moral agency, providing meaningful human control, implementing safety engineering, and employing social control. These methods aim to responsibly integrate artificial agents into society. We conclude that a realistic approach, which addresses the practical problems posed by control gaps, is essential. This approach provides solutions to manage the risks posed by artificial agents while maintaining acceptable moral standards, ensuring we responsibly harness their potential and address the ethical challenges they present. (shrink)

Implementationalism maintains that conventional, silicon-based artificial systems are not conscious because they fail to satisfy certain substantive constraints on computational implementation. In this article, we argue that several recently proposed substantive constraints are implausible, or at least are not well-supported, insofar as they conflate intuitions about computational implementation generally and consciousness specifically. We argue instead that the mechanistic account of computation can explain several of the intuitions driving implementationalism and noncomputationalism in a manner which is consistent with artificial (...) consciousness. Our argument provides indirect support for computationalism about consciousness and the view that conventional artificial systems can be conscious. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method (...) is suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

Which artificial intelligence (AI) systems are agents? To answer this question, I propose a multidimensional account of agency. According to this account, a system's agency profile is jointly determined by its level of goal-directedness and autonomy as well as is abilities for directly impacting the surrounding world, long-term planning and acting for reasons. Rooted in extant theories of agency, this account enables fine-grained, nuanced comparative characterizations of artificial agency. I show that this account has multiple important virtues and (...) is more informative than alternatives. More speculatively, it may help to illuminate two important emerging questions in AI ethics: 1. Can agency contribute to the moral status of non-human beings, and how? 2. When and why might AI systems exhibit power-seeking behaviour and does this pose an existential risk to humanity? (shrink)

This paper argues that the Value Sensitive Design (VSD) methodology provides a principled approach to embedding common values in to AI systems both early and throughout the design process. To do so, it draws on an important case study: the evidence and final report of the UK Select Committee on Artificial Intelligence. This empirical investigation shows that the different and often disparate stakeholder groups that are implicated in AI design and use share some common values that can be used (...) to further strengthen design coordination efforts. VSD is shown to be both able to distill these common values as well as provide a framework for stakeholder coordination. (shrink)

The application of Artificial Intelligence (AI) in healthcare and epidemiology undoubtedly has many benefits for the population. However, due to its environmental impact, the use of AI can produce social inequalities and long-term environmental damages that may not be thoroughly contemplated. In this paper, we propose to consider the impacts of AI applications in medical care from the One Health paradigm and long-term global health. From health and environmental justice, rather than settling for a short and fleeting green honeymoon (...) between health and sustainability caused by AI, it should aim for a lasting marriage. To this end, we conclude by proposing that, in the upcoming years, it could be valuable and necessary to promote more interconnected health, call for environmental cost transparency, and increase green responsibility. (shrink)

AI has strengths that humans cannot replicate, such as scalability, speed, and automation, but this must not mean that we depend entirely on AI for intellectual advancement. For a future where humans coexist with advanced AI, we must acknowledge the existence of intrinsic natural stupidity and absurdity of humans and take them into consideration. Otherwise, increasing the information and processing capabilities of AI may amplify the magnitude of humans’ poor decisions and their consequences, but not the other way around.

Recent progress in artificial intelligence (AI) has drawn attention to the technology’s transformative potential, including what some see as its prospects for causing large-scale harm. We review two influential arguments purporting to show how AI could pose catastrophic risks. The first argument — the Problem of Power-Seeking — claims that, under certain assumptions, advanced AI systems are likely to engage in dangerous power-seeking behavior in pursuit of their goals. We review reasons for thinking that AI systems might seek power, (...) that they might obtain it, that this could lead to catastrophe, and that we might build and deploy such systems anyway. The second argument claims that the development of human-level AI will unlock rapid further progress, culminating in AI systems far more capable than any human — this is the Singularity Hypothesis. Power-seeking behavior on the part of such systems might be particularly dangerous. We discuss a variety of objections to both arguments and conclude by assessing the state of the debate. (shrink)

AI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and (...) their distinctive features. We argue that, unlike comparatively low-tech affective artifacts, affective artificial agents display a specific form of agency, which prevents them from being perceived by their users as extensions of their selves. In addition to this, we claim that their functioning crucially depends on the simulation of human-like emotion-driven behavior and requires a distinctive form of transparency—we call it emotional transparency—that might give rise to ethical and normative tensions. (shrink)

Artificial gametes, derived from stem cells, have the potential to enable in vitro fertilization of embryos. Currently, artificial gametes are only being generated in laboratory animals; however, considerable efforts are underway to develop artificial gametes using human cell sources. These artificial gametes are being proposed as a means to address infertility through assisted reproductive technologies. Nonetheless, the availability of artificial gametes obtained from adult organisms can potentially expand the possibilities of reproduction. Various groups, such as (...) same-sex couples, post-menopausal women, and deceased donors, could potentially utilize artificial gametes to conceive genetically related offspring. The advent of artificial gametes raises significant bioethical questions. Should all these reproductive scenarios be accepted? How can we delineate the range of future reproductive choices? A normative bioethical framework may be necessary to establish a consensus regarding the use of human artificial gametes. This review aims to present the current state of research on the biological roadmap for generating artificial gametes, while also summarizing proposed approaches to establish a normative framework that delineates ethically acceptable paths for reproduction. (shrink)

The article reflects on where AI is headed and the world along with it, considering trust, ethics and safety. Implicit in artificial thinking and doomsday appraisals is the engineered divorce from reality of sublime human embodiment. Jeffrey White, Dietrich Brandt, Jan Soeffner, and Larry Stapleton, four scholars associated with AI & Society, address these issues, and more, in the following exchange.

Does the assumption of a weak form of computational functionalism, according to which the right form of neural computation is sufficient for consciousness, entail that a digital computational simulation of such neural computations is conscious? Or must this computational simulation be implemented in the right way, in order to replicate consciousness? From the perspective of Karl Friston’s free energy principle, self-organising systems (such as living organisms) share a set of properties that could be realised in artificial systems, but are (...) not instantiated by computers with a classical (von Neumann) architecture. I argue that at least one of these properties, viz. a certain kind of causal flow, can be used to draw a distinction between systems that merely simulate, and those that actually replicate consciousness. (shrink)

Artificial agents (AAs), particularly but not only those in Cyberspace, extend the class of entities that can be involved in moral situations. For they can be conceived of as moral patients (as entities that can be acted upon for good or evil) and also as moral agents (as entities that can perform actions, again for good or evil). In this paper, we clarify the concept of agent and go on to separate the concerns of morality and responsibility of agents (...) (most interestingly for us, of AAs). We conclude that there is substantial and important scope, particularly in Computer Ethics, for the concept of moral agent not necessarily exhibiting free will, mental states or responsibility. This complements the more traditional approach, common at least since Montaigne and Descartes, which considers whether or not (artificial) agents have mental states, feelings, emotions and so on. By focussing directly on mind-less morality we are able to avoid that question and also many of the concerns of Artificial Intelligence. A vital component in our approach is the Method of Abstraction for analysing the level of abstraction (LoA) at which an agent is considered to act. The LoA is determined by the way in which one chooses to describe, analyse and discuss a system and its context. The Method of Abstraction is explained in terms of an interface or set of features or observables at a given LoA. Agenthood, and in particular moral agenthood, depends on a LoA. Our guidelines for agenthood are: interactivity (response to stimulus by change of state), autonomy (ability to change state without stimulus) and adaptability (ability to change the transition rules by which state is changed) at a given LoA. Morality may be thought of as a threshold defined on the observables in the interface determining the LoA under consideration. An agent is morally good if its actions all respect that threshold; and it is morally evil if some action violates it. That view is particularly informative when the agent constitutes a software or digital system, and the observables are numerical. Finally we review the consequences for Computer Ethics of our approach. In conclusion, this approach facilitates the discussion of the morality of agents not only in Cyberspace but also in the biosphere, where animals can be considered moral agents without their having to display free will, emotions or mental states, and in social contexts, where systems like organizations can play the role of moral agents. The primary cost of this facility is the extension of the class of agents and moral agents to embrace AAs. (shrink)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (...) (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (shrink)

Abstract: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview of (...) the opportunities AI presents for effective leadership and the strategies required to address its associated challenges. (shrink)

Recently, I argued that human subjects in artificial wombs (AWs) “share the same moral status as newborns” and so, deserve the same treatment and protections as newborns. This thesis rests on two claims: (A) “Subjects of partial ectogenesis—those that develop in utero for at time before being transferred to AWs—are newborns,” and (B) “Subjects of complete ectogenesis—those who develop in AWs entirely—share the same moral status as newborns.” In response, Elizabeth Chloe Romanis argued that the subject in an AW (...) is “a unique human entity…rather than a fetus or a newborn.” She provides four lines of response to my essay. First, she argues that I have “misconstrued” what birth is. Once we correct that error, it becomes clear that subjects of partial ectogenesis have not been born. Second, she argues that my claims imply that non-implanted embryos (existing in vivo) “would also be ‘born.’” But that is absurd. Third, she claims I fail to “meaningfully respond” to distinctions she draws between subjects of ectogenesis and neonates. Finally, she criticizes my essay for focusing on subjects of AWs rather than focusing on pregnant persons (who should be at the “centre” of debates over AWs). I respond to each of these charges. In doing so, I reaffirm that (contra Romanis) some subjects of ectogenesis are newborns and all subjects of ectogenesis—even those that have not been born—share the same moral status as newborns. (shrink)

Cheating is a growing academic and ethical concern in higher education. This article examines the rise of artificial intelligence (AI) generative chatbots for use in education and provides a review of research literature and relevant scholarship concerning the cheating-related issues involved and their implications for pedagogy. The technological “arms race” that involves cheating-detection system developers versus technology savvy students is attracting increased attention to cheating. AI has added new dimensions to academic cheating challenges as students (as well as faculty (...) and staff) can easily access powerful systems for generating content that can be presented in assignments, exams, or published papers as their own. AI methodology is also providing some emerging anti-cheating approaches, including facial recognition and water- marking. This article provides an overview of human/AI collaboration approaches and frames some educational misuses of such AI generative systems as ChatGPT and Bard as forms of “misattributed co-authorship.” As with other kinds of collaborations, the work that students produce with AI assistance can be presented in transparent and straightforward modes or (unfortunately) in opaquer and ethically-problematic ways. However, rather than just for catching or entrapping students, the emerging varieties of technological cheating-detection strategies can be used to assist students in learning how to document and attribute properly their AI-empowered as well as human-human collaborations. Construing misuses of AI generative systems as misattributed co-authorship can recognize the growing capabilities of these tools and how stressing responsible and mindful usage by students can help prepare them for a highly collaborative, AI-saturated future. (shrink)

Artificial intelligence research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime. AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and (...) inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space. (shrink)

This paper investigates the claim that artificial Intelligence Systems cannot be held morally responsible because they do not have an ability for agential self-awareness e.g. they cannot be aware that they are the agents of an action. The main suggestion is that if agential self-awareness and related first person representations presuppose an awareness of a self, the possibility of responsible artificial intelligence systems cannot be evaluated independently of research conducted on the nature of the self. Focusing on a (...) specific account of the self from the phenomenological tradition, this paper suggests that a minimal necessary condition that artificial intelligence systems must satisfy so that they have a capability for self-awareness, is having a minimal self defined as ‘a sense of ownership’. As this sense of ownership is usually associated with having a living body, one suggestion is that artificial intelligence systems must have similar living bodies so they can have a sense of self. Discussing cases of robotic animals as examples of the possibility of artificial intelligence systems having a sense of self, the paper concludes that the possibility of artificial intelligence systems having a ‘sense of ownership’ or a sense of self may be a necessary condition for having responsibility. (shrink)

In the field of machine consciousness, it has been argued that in order to build human-like conscious machines, we must first have a computational model of qualia. To this end, some have proposed a framework that supports qualia in machines by implementing a model with three computational areas (i.e., the subconceptual, conceptual, and linguistic areas). These abstract mechanisms purportedly enable the assessment of artificial qualia. However, several critics of the machine consciousness project dispute this possibility. For instance, Searle, in (...) his Chinese room objection, argues that however sophisticated a computational system is, it can never exhibit intentionality; thus, would also fail to exhibit consciousness or any of its varieties. This paper argues that the proposed architecture mentioned above answers the problem posed by Searle, at least in part. Specifically, it argues that we could reformulate Searle’s worries in the Chinese room in terms of the three-stage artificial qualia model. And by doing so, we could see that the person doing all the translations in the room could realize the three areas in the proposed framework. Consequently, this demonstrates the actualization of self-consciousness in machines. (shrink)

In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained (...) using data set which its title is “primary tumor” and was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia Test data evaluation shows that the ANN model is able to correctly predict the tumor category with 76.67 % accuracy. (shrink)

Accountability is a cornerstone of the governance of artificial intelligence (AI). However, it is often defined too imprecisely because its multifaceted nature and the sociotechnical structure of AI systems imply a variety of values, practices, and measures to which accountability in AI can refer. We address this lack of clarity by defining accountability in terms of answerability, identifying three conditions of possibility (authority recognition, interrogation, and limitation of power), and an architecture of seven features (context, range, agent, forum, standards, (...) process, and implications). We analyse this architecture through four accountability goals (compliance, report, oversight, and enforcement). We argue that these goals are often complementary and that policy-makers emphasise or prioritise some over others depending on the proactive or reactive use of accountability and the missions of AI governance. (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI has brought to (...) the field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

There is considerable enthusiasm about the prospect that artificial intelligence (AI) will help to improve the safety and efficacy of health services and the efficiency of health systems. To realize this potential, however, AI systems will have to overcome structural problems in the culture and practice of medicine and the organization of health systems that impact the data from which AI models are built, the environments into which they will be deployed, and the practices and incentives that structure their (...) development. This perspective elaborates on some of these structural challenges and provides recommendations to address potential shortcomings. (shrink)

This paper investigates the concept of behavioral autonomy in Artificial Life by drawing a parallel to the use of teleological notions in the study of biological life. Contrary to one of the leading assumptions in Artificial Life research, I argue that there is a significant difference in how autonomous behavior is understood in artificial and biological life forms: the former is underlain by human goals in a way that the latter is not. While behavioral traits can be (...) explained in relation to evolutionary history in biological organisms, in synthetic life forms behavior depends on a design driven by a research agenda, further shaped by broader human goals. This point will be illustrated with a case study on a synthetic life form. Consequently, the putative epistemic benefit of reaching a better understanding of behavioral autonomy in biological organisms by synthesizing artificial life forms is subject to doubt: the autonomy observed in such artificial organisms may be a mere projection of human agency. Further questions arise in relation to the need to spell out the relevant human aims when addressing potential social or ethical implications of synthesizing artificial life forms. (shrink)

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where (...) it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. -/- Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime. (shrink)

While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new (...) AI methods could be adapted for feminist purposes and what role new technologies might play in addressing concerns raised by feminist epistemologists and theorists about algorithmic systems. In particular, we highlight distributed and federated learning as providing partial solutions to the power-oriented concerns that have stymied efforts to make machine learning systems more representative and pluralist. (shrink)

Moral reasoning traditionally distinguishes two types of evil: moral and natural. The standard view is that ME is the product of human agency and so includes phenomena such as war, torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE. Recently, as a result of developments in autonomous agents in cyberspace, (...) a new class of interesting and important examples of hybrid evil has come to light. In this paper, it is called artificial evil and a case is made for considering it to complement ME and NE to produce a more adequate taxonomy. By isolating the features that have led to the appearance of AE, cyberspace is characterised as a self-contained environment that forms the essential component in any foundation of the emerging field of Computer Ethics. It is argued that this goes some way towards providing a methodological explanation of why cyberspace is central to so many of CE’s concerns; and it is shown how notions of good and evil can be formulated in cyberspace. Of considerable interest is how the propensity for an agent’s action to be morally good or evil can be determined even in the absence of biologically sentient participants and thus allows artificial agents not only to perpetrate evil but conversely to ‘receive’ or ‘suffer from’ it. The thesis defended is that the notion of entropy structure, which encapsulates human value judgement concerning cyberspace in a formal mathematical definition, is sufficient to achieve this purpose and, moreover, that the concept of AE can be determined formally, by mathematical methods. A consequence of this approach is that the debate on whether CE should be considered unique, and hence developed as a Macroethics, may be viewed, constructively, in an alternative manner. The case is made that whilst CE issues are not uncontroversially unique, they are sufficiently novel to render inadequate the approach of standard Macroethics such as Utilitarianism and Deontologism and hence to prompt the search for a robust ethical theory that can deal with them successfully. The name Information Ethics is proposed for that theory. It is argued that the uniqueness of IE is justified by its being non-biologically biased and patient-oriented: IE is an Environmental Macroethics based on the concept of data entity rather than life. It follows that the novelty of CE issues such as AE can be appreciated properly because IE provides a new perspective. In light of the discussion provided in this paper, it is concluded that Computer Ethics is worthy of independent study because it requires its own application-specific knowledge and is capable of supporting a methodological foundation, Information Ethics. (shrink)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, (...) we critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

Although virtue ethics has repeatedly been proposed as a suitable framework for the development of artificial moral agents, it has been proven difficult to approach from a computational perspective. In this work, we present the first technical implementation of artificial virtuous agents in moral simulations. First, we review previous conceptual and technical work in artificial virtue ethics and describe a functionalistic path to AVAs based on dispositional virtues, bottom-up learning, and top-down eudaimonic reward. We then provide the (...) details of a technical implementation in a moral simulation based on a tragedy of the commons scenario. The experimental results show how the AVAs learn to tackle cooperation problems while exhibiting core features of their theoretical counterpart, including moral character, dispositional virtues, learning from experience, and the pursuit of eudaimonia. Ultimately, we argue that virtue ethics provides a compelling path toward morally excellent machines and that our work provides an important starting point for such endeavors. (shrink)

Moral reasoning traditionally distinguishes two types of evil:moral (ME) and natural (NE). The standard view is that ME is the product of human agency and so includes phenomena such as war,torture and psychological cruelty; that NE is the product of nonhuman agency, and so includes natural disasters such as earthquakes, floods, disease and famine; and finally, that more complex cases are appropriately analysed as a combination of ME and NE. Recently, as a result of developments in autonomous agents in cyberspace, (...) a new class of interesting and important examples of hybrid evil has come to light. In this paper, it is called artificial evil (AE) and a case is made for considering it to complement ME and NE to produce a more adequate taxonomy. By isolating the features that have led to the appearance of AE, cyberspace is characterised as a self-contained environment that forms the essential component in any foundation of the emerging field of Computer Ethics (CE). It is argued that this goes someway towards providing a methodological explanation of why cyberspace is central to so many of CE's concerns; and it is shown how notions of good and evil can be formulated in cyberspace. Of considerable interest is how the propensity for an agent's action to be morally good or evil can be determined even in the absence of biologically sentient participants and thus allows artificial agents not only to perpetrate evil (and fort that matter good) but conversely to `receive' or `suffer from' it. The thesis defended is that the notion of entropy structure, which encapsulates human value judgement concerning cyberspace in a formal mathematical definition, is sufficient to achieve this purpose and, moreover, that the concept of AE can be determined formally, by mathematical methods. A consequence of this approach is that the debate on whether CE should be considered unique, and hence developed as a Macroethics, may be viewed, constructively,in an alternative manner. The case is made that whilst CE issues are not uncontroversially unique, they are sufficiently novel to render inadequate the approach of standard Macroethics such as Utilitarianism and Deontologism and hence to prompt the search for a robust ethical theory that can deal with them successfully. The name Information Ethics (IE) is proposed for that theory. Itis argued that the uniqueness of IE is justified by its being non-biologically biased and patient-oriented: IE is an Environmental Macroethics based on the concept of data entity rather than life. It follows that the novelty of CE issues such as AE can be appreciated properly because IE provides a new perspective (though not vice versa). In light of the discussion provided in this paper, it is concluded that Computer Ethics is worthy of independent study because it requires its own application-specific knowledge and is capable of supporting a methodological foundation, Information Ethics. (shrink)

A 2017 Nature report was widely touted as hailing the arrival of the artificial womb. But the scientists involved claim their technology is merely an improvement in neonatal care. This raises an under-considered question: what differentiates neonatal incubation from artificial womb technology? Considering the nature of gestation—or metaphysics of pregnancy—(a) identifies more profound differences between fetuses and neonates/babies than their location (in or outside the maternal body) alone: fetuses and neonates have different physiological and physical characteristics; (b) characterizes (...) birth as a physiological, mereological and topological transformation as well as a (morally relevant) change of location; and (c) delivers a clear distinction between neonatal incubation and ectogestation: the former supports neonatal physiology; the latter preserves fetal physiology. This allows a detailed conceptual classification of ectogenetive and ectogestative technologies according to which the 2017 system is not just improved neonatal incubation, but genuine ectogestation. But it is not an artificial womb, which is a term that is better put to rest. The analysis reveals that any ethical discussion involving ectogestation must always involve considerations of possible risks to the mother as well as her autonomy and rights. It also adds a third and potentially important dimension to debates in reproductive ethics: the physiological transition from fetus/gestateling to baby/neonate. (shrink)

The concept of artificial intelligence is not new nor is the notion that it should be granted legal protections given its influence on human activity. What is new, on a relative scale, is the notion that artificial intelligence can possess citizenship—a concept reserved only for humans, as it presupposes the idea of possessing civil duties and protections. Where there are several decades’ worth of writing on the concept of the legal status of computational artificial artefacts in the (...) USA and elsewhere, it is surprising that law makers internationally have come to a standstill to protect our silicon brainchildren. In this essay, it will be assumed that future artificial entities, such as Sophia the Robot, will be granted citizenship on an international scale. With this assumption, an analysis of rights will be made with respect to the needs of a non-biological intelligence possessing legal and civic duties akin to those possessed by humanity today. This essay does not present a full set of rights for artificial intelligence—instead, it aims to provide international jurisprudence evidence aliunde ab extra de lege lata for any future measures made to protect non-biological intelligence. (shrink)