scholarly journals Artificial Intuition in Tech Journalism on AI: Imagining the Human Subject

2021 ◽  
Vol 2 ◽  
pp. 173-190
Author(s):  
Jacob Johanssen ◽  
Xin Wang

Artificial intuition (AI acting intuitively) is one trend in artificial intelligence. This article analyzes how it is discussed by technology journalism on the internet. The journalistic narratives that were analyzed claim that intuition can make AI more efficient, autonomous, and human. Some commentators also write that intuitive AI could execute tasks better than humans themselves ever could (e.g., in digital games); therefore, it could ultimately surpass human intuition. Such views do not pay enough attention to biases as well as transparency and explainability of AI. We contrast the journalistic narratives with philosophical understandings of intuition and a psychoanalytic view of the human. Those perspectives allow for a more complex view that goes beyond the focus on rationality and computational perspectives of tech journalism.

Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.


Author(s):  
William B. Rouse

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.


2021 ◽  
Vol 27 (4) ◽  
Author(s):  
Francisco Lara

AbstractCan Artificial Intelligence (AI) be more effective than human instruction for the moral enhancement of people? The author argues that it only would be if the use of this technology were aimed at increasing the individual's capacity to reflectively decide for themselves, rather than at directly influencing behaviour. To support this, it is shown how a disregard for personal autonomy, in particular, invalidates the main proposals for applying new technologies, both biomedical and AI-based, to moral enhancement. As an alternative to these proposals, this article proposes a virtual assistant that, through dialogue, neutrality and virtual reality technologies, can teach users to make better moral decisions on their own. The author concludes that, as long as certain precautions are taken in its design, such an assistant could do this better than a human instructor adopting the same educational methodology.


2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.


Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 539 ◽  
Author(s):  
Arun Kumar Sangaiah ◽  
Ali Asghar Rahmani Hosseinabadi ◽  
Morteza Babazadeh Shareh ◽  
Seyed Yaser Bozorgi Rad ◽  
Atekeh Zolfagharian ◽  
...  

The Internet of Things (IoT) is a distributed system that connects everything via internet. IoT infrastructure contains multiple resources and gateways. In such a system, the problem of optimizing IoT resource allocation and scheduling (IRAS) is vital, because resource allocation (RA) and scheduling deals with the mapping between recourses and gateways and is also responsible for optimally allocating resources to available gateways. In the IoT environment, a gateway may face hundreds of resources to connect. Therefore, manual resource allocation and scheduling is not possible. In this paper, the whale optimization algorithm (WOA) is used to solve the RA problem in IoT with the aim of optimal RA and reducing the total communication cost between resources and gateways. The proposed algorithm has been compared to the other existing algorithms. Results indicate the proper performance of the proposed algorithm. Based on various benchmarks, the proposed method, in terms of “total communication cost”, is better than other ones.


2015 ◽  
Vol 47 (1) ◽  
pp. 5-17
Author(s):  
Jolanta Korycka-Skorupa

Abstract The author discuss effectiveness of cartographic presentations. The article includes opinions of cartographers regarding effectiveness, readability and efficiency of a map. It reminds the principles of map graphic design in order to verify them using examples of small-scale thematic maps. The following questions have been asked: Is the map effective? Why is the map effective? How do cartographic presentation methods affect effectiveness of the cartographic message? What else can influence effectiveness of a map? Each graphic presentation should be effective, as its purpose is to complete written word, draw the recipients’ attention, make text more readable, expose the most important information. Such a significant role of graphics results in the fact that graphic presentations (maps, diagrams) require proper preparation. Users need to have a chance to understand the graphics language in order to draw correct conclusions about the presented phenomenon. Graphics should demonstrate the most important elements, some tendencies, and directions of changes. It should generalize and present a given subject from a slightly different perspective. There are numerous examples of well-edited and poorly edited small-scale thematic maps. They include maps, which are impossible to interpret correctly. They are burdened with methodological defects and they cannot fulfill their task. Cartography practice indicates that the principles related to graphic design of cartographic presentation are frequently omitted during the process of developing small-scale thematic maps used – among others – in the press and on the Internet. The purpose of such presentations is to quickly interpret them. On such maps editors’ problems with the selection of an appropriate symbol and graphic variable (fig. 1A, 9B) are visible. Sometimes they use symbols which are not sufficiently distinguishable nor demonstrative (fig. 11), it does not increase their readability. Sometime authors try too hard to reflect presented phenomenon and therefore the map becomes more difficult to interpret (fig. 4A,B). The lack of graphic sense resulting in the lack of graphic balance and aesthetics constitutes a weak point of numerous cartographic presentations (fig. 13). Effectiveness of cartographic presentations consists of knowledge and skills of the map editor, as well as the recipients’ perception capabilities and their readiness to read and interpret maps. The qualifications of the map editor should include methodological qualifications supported by the knowledge of the principles for cartographic symbol design, as well as relevant technical qualifications, which allow to properly use the tools to edit a map. Maps facilitate the understanding of texts they accompany and they present relationships between phenomenon better than texts, appealing to the senses.


2011 ◽  
Vol 130-134 ◽  
pp. 2047-2050 ◽  
Author(s):  
Hong Chun Qu ◽  
Xie Bin Ding

SVM(Support Vector Machine) is a new artificial intelligence methodolgy, basing on structural risk mininization principle, which has better generalization than the traditional machine learning and SVM shows powerfulability in learning with limited samples. To solve the problem of lack of engine fault samples, FLS-SVM theory, an improved SVM, which is a method is applied. 10 common engine faults are trained and recognized in the paper.The simulated datas are generated from PW4000-94 engine influence coefficient matrix at cruise, and the results show that the diagnostic accuracy of FLS-SVM is better than LS-SVM.


Author(s):  
A.S. Travov ◽  

This article provides an overview of the decision to improve the field storage of sugar beet. The purpose of development is to preserve the crop. Methods of monitoring volumes of piles and microclimate inside them are considered. The method for obtaining data on volumes of piles and the further use thereof for optimizing the storage process is described.


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