50 years of artificial intelligence: a neuronal approach

Recently, the 50th anniversary of the birth of Artificial Intelligence (AI) has been celebrated worldwide, and about 65 years ago (1943) its foundational works on Biocybernetics and Bionics were published due to movements led by McCulloch and Pitts and Wiener

"Let us make ROBOT in our image, according to our likeness" : an examination of robots in several science fiction films through the christian concept of the "image of God"

The paper examines representations of robots in several films: Bicentennial Man (1999), Star Trek: Nemesis (2002) and Chappie (2015) in the light of the Christian concept of imago Dei. According to Victoria Nelson, in the last 50 years artificial intelligence in pop-culture works has frequently been presented as holiness. Her interpretation can be linked with the outcome of research of scholars, who revealed that the Euro-American view on technology is deeply rooted in Christian thought. The author’s main line of argument is embedded in Noreen Herzfeld’s observation, which demonstrated the striking similarities between the relational approach to research into artificial intelligence and the relational interpretation of the notion of imago Dei by Karl Barth. Herzfeld suggests that the robots in the examined films can be viewed through a relational approach to the concept of imago Dei, which entails a relational definition of intelligence

Artificial Intelligence acceptance : morphological elements of the acceptance of Artificial Intelligence

Inteligência Artificial tem-se desenvolvido muito rapidamente ao longo dos últimos anos, há medida que os algoritmos de machine learning vão evoluindo e ficando mais complexos, os robôs ficam cada vez mais autónomos, levando a um desenvolvimento mais rápido e à aparição de mais chatbots no suporte a variados serviços e assistentes pessoais como a Cortana e a Siri. Esta rápida evolução permite que as empresas que adotam estas tecnologias possam vir a ganhar uma vantagem competitiva. No entanto, para que estas tecnologias se traduzam numa melhoria da performance das empresas, é de elevada importância que a Inteligência Artificial seja aceite e incentivada pelos colaboradores das empresas em questão. Neste sentido, estudámos as teorias de aceitação da tecnologia existentes, adaptando o UTAUT para chegar a um novo modelo que permite compreender a aceitação de Inteligência Artificial. O instrumento de recolha de dados utilizado foi um questionário online que foi respondido por 321 pessoas com uma média de idades de aproximadamente 29 anos, sendo que cerca de 50% da amostra corresponde a pessoas com idades compreendidas entre os 22 e os 35 anos. Os resultados obtidos foram bastante positivos, mostrando que a maioria das pessoas parece estar recetiva a esta tecnologia e achar que se trata de uma ferramenta útil.Artificial Intelligence is experiencing a fast progress in the last years, as machine learning algorithms evolve into more complex algorithms, robots gain autonomy, leading to a faster development of chatbots in the support to several services and personal assistants, such as Cortana and Siri. This rapid evolution allows companies to obtain competitive advantages by adopting this type of technologies. However, in order for these technologies to improve the companies’ performance, employers, managers and employees have to accept Artificial Intelligence and foster the usage of these programs. In this sense, we studied the existent technology acceptance theories, adapting the UTAUT to develop a model to study the acceptance of Artificial Intelligence. The instrument for collecting data used was an online questionnaire, that was answered by 321 people with an average of ages of approximately 29 years and 50% of the sample had ages between 22 and 35 years. The results were very positive, showing that the generality of people seemed to be receptive to this technology, while thinking it can be an useful tool

Artificial Intelligence Systems and problems of the concept of author. Reflections on a recent book

The publication of the book Beta Writer. 2019. Lithium-Ion Batteries. A Machine-Generated Summary of Current Research. New York, NY: Springer, produced with Artificial Intelligence software prompts analysis and reflections in several areas. First of all, on what Artificial Intelligence systems are able to do in the production of informative texts. This raises the question if and how an Artificial Intelligence software system can be treated as the author of a text it has produced. Evaluating whether this is correct and possible leads to re-examine the current conception for which it is taken for granted that the author is a person. This, in turn, when faced with texts produced by Artificial Intelligence systems necessarily raises the question of whether they, like the author-person, are endowed with agency. The article concludes that Artificial Intelligence systems are characterized by a distributed agency, shared with those who designed them and make them work, and that in the wake of the reflections of 50 years ago by Barthes and Foucault, it is necessary to define and recognize a new type of author

Double-reading mammograms using artificial intelligence technologies: A new model of mass preventive examination organization

BACKGROUND: In recent years, the availability of medical datasets and technologies for software development based on artificial intelligence technology has resulted in a growth in the number of solutions for medical diagnostics, particularly mammography. Registered as a medical device, this program can interpret digital mammography, significantly saving time, material, and human resources in healthcare while ensuring the quality of mammary gland preventive studies. AIM: This study aims to justify the possibility and effectiveness of artificial intelligence-based software for the first interpretation of digital mammograms while maintaining the practice of a radiologists second description of X-ray images. MATERIALS AND METHODS: A dataset of 100 digital mammography studies (50 absence of target pathology and 50 ― presence of target pathology, with signs of malignant neoplasms) was processed by software based on artificial intelligence technology that was registered as a medical device in the Russian Federation. Receiver operating characteristic analysis was performed. Limitations of the study include the values of diagnostic accuracy metrics obtained for software based on artificial intelligence technology versions, relevant at the end of 2022. RESULTS: When set to 80.0% sensitivity, artificial intelligence specificity was 90.0% (95% CI, 81.798.3), and accuracy was 85.0% (95% CI, 78.092.0). When set to 100% specificity, artificial intelligence demonstrated 56.0% sensitivity (95% CI, 42.269.8) and 78.0% accuracy (95% CI, 69.986.1). When the sensitivity was set to 100%, the artificial intelligence specificity was 54.0% (95% CI, 40.267.8), and the accuracy was 77.0% (95% CI, 68.885.2). Two approaches have been proposed, providing an autonomous first interpretation of digital mammography using artificial intelligence. The first approach is to evaluate the X-ray image using artificial intelligence with a higher sensitivity than that of the double-reading mammogram by radiologists, with a comparable level of specificity. The second approach implies that artificial intelligence-based software will determine the mammogram category (absence of target pathology or presence of target pathology), indicating the degree of confidence in the obtained result, depending on the corridor into which the predicted value falls. CONCLUSIONS: Both proposed approaches for using artificial intelligence-based software for the autonomous first interpretation of digital mammograms can provide diagnostic quality comparable to, if not superior to, double-image reading by radiologists. The economic benefit from the practical implementation of this approach nationwide can range from 0.6 to 5.5 billion rubles annually