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Добірка наукової літератури з теми "Other Artificial Intelligence"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 21 лютого 2023

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Статті в журналах з теми "Other Artificial Intelligence"

VerWey, John. "The Other Artificial Intelligence Hardware Problem." Computer 55, no. 1 (January 2022): 34–42. http://dx.doi.org/10.1109/mc.2021.3113271.

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LAWRENCE, DAVID R., CÉSAR PALACIOS-GONZÁLEZ, and JOHN HARRIS. "Artificial Intelligence." Cambridge Quarterly of Healthcare Ethics 25, no. 2 (March 9, 2016): 250–61. http://dx.doi.org/10.1017/s0963180115000559.

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Abstract:It seems natural to think that the same prudential and ethical reasons for mutual respect and tolerance that one has vis-à-vis other human persons would hold toward newly encountered paradigmatic but nonhuman biological persons. One also tends to think that they would have similar reasons for treating we humans as creatures that count morally in our own right. This line of thought transcends biological boundaries—namely, with regard to artificially (super)intelligent persons—but is this a safe assumption? The issue concerns ultimate moral significance: the significance possessed by human persons, persons from other planets, and hypothetical nonorganic persons in the form of artificial intelligence (AI). This article investigates why our possible relations to AI persons could be more complicated than they first might appear, given that they might possess a radically different nature to us, to the point that civilized or peaceful coexistence in a determinate geographical space could be impossible to achieve.

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Iliescu, Dragos, Samuel Greiff, Matthias Ziegler, and Marjolein Fokkema. "Artificial Intelligence, Machine Learning, and Other Demons." European Journal of Psychological Assessment 38, no. 3 (May 2022): 163–64. http://dx.doi.org/10.1027/1015-5759/a000713.

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Forghani, Reza. "Machine Learning and Other Artificial Intelligence Applications." Neuroimaging Clinics of North America 30, no. 4 (November 2020): i. http://dx.doi.org/10.1016/s1052-5149(20)30067-8.

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Takama, Yasufumi. "Web Intelligence and Artificial Intelligence." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 1 (January 20, 2017): 25–30. http://dx.doi.org/10.20965/jaciii.2017.p0025.

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This paper briefly summarizes the progress of artificial intelligence (AI) and web intelligence (WI) in the last two decades. The reason why we mention AI and WI together is because those have strong relationship with each other. This paper first summarizes the history of AI, and then gives brief description of supervised learning, which I think has played a major role in AI in the last two decades. As most history of WI is in the target decades, this paper first briefly describes major WI topics, and then gives more detailed description about information recommendation, which I think one of more successful and necessary technologies in practical use.

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Tasioulas, John. "Artificial Intelligence, Humanistic Ethics." Daedalus 151, no. 2 (2022): 232–43. http://dx.doi.org/10.1162/daed_a_01912.

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Анотація:

Abstract Ethics is concerned with what it is to live a flourishing life and what it is we morally owe to others. The optimizing mindset prevalent among computer scientists and economists, among other powerful actors, has led to an approach focused on maximizing the fulfilment of human preferences, an approach that has acquired considerable influence in the ethics of AI. But this preference-based utilitarianism is open to serious objections. This essay sketches an alternative, “humanistic” ethics for AI that is sensitive to aspects of human engagement with the ethical often missed by the dominant approach. Three elements of this humanistic approach are outlined: its commitment to a plurality of values, its stress on the importance of the procedures we adopt, not just the outcomes they yield, and the centrality it accords to individual and collective participation in our understanding of human well-being and morality. The essay concludes with thoughts on how the prospect of artificial general intelligence bears on this humanistic outlook.

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A, Kasianenko, and Fedotov V. "Manifestation of artificial intelligence in human life." Artificial Intelligence 27, jai2022.27(1) (June 20, 2022): 183–92. http://dx.doi.org/10.15407/jai2022.01.183.

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Анотація:

Today, in many areas of science and social life, machines, or so-called robots, are entrusted with tasks that previously could only be performed by humans, and this is what led to the creation of artificial intelligence and further stimulates its development and improvement. Automated machines, which are endowed with artificial intelligence, are thus able to relieve a person from routine activities, in particular. Thus, systems based on artificial intelligence are increasingly used in technology, for example, cars endowed with artificial intelligence, or, for example, robots involved in production. That is, the purpose of creating artificial intelligence is primarily to improve human life. However, any system has its shortcomings and problems that need to be explored for further improvement and effective development. It can be stated that scientists identify many problems in the field of artificial intelligence and this list is not exhaustive and with the development of society there will be other debatable issues, however, in my opinion the central problem is the lack of unambiguous opinion on scientific discourse. basic concepts, such as "thinking", "consciousness", "intelligence". And in view of the above, there is an urgent need for a common understanding of these concepts, so that in the future it is possible to qualitatively solve the already mentioned legal and moral problems in the field of artificial intelligence. A large number of domestic researchers are studying issues related to artificial intelligence and looking for ways to overcome problems or at least reduce the number of problems in this area. These include: Karchevsky MV Nikolskny, Yu. V., Pasichnyk VV, Shcherbyna Yu. M., Stefanchuk RO, Pozova DD ,. Radutny OE and others.

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Berrar, Daniel, Naoyuki Sato, and Alfons Schuster. "Quo Vadis, Artificial Intelligence?" Advances in Artificial Intelligence 2010 (February 24, 2010): 1–12. http://dx.doi.org/10.1155/2010/629869.

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Анотація:

Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervous systems of biological organisms and systems biology with its longing to comprehend, holistically, the multitude of complex interactions in biological systems are two such fields. They target ideals artificial intelligence has dreamt about for a long time including the computer simulation of an entire biological brain or the creation of new life forms from manipulations of cellular and genetic information in the laboratory. The scope for artificial intelligence in neuroscience and systems biology is extremely wide. This article investigates the standing of artificial intelligence in relation to neuroscience and systems biology and provides an outlook at new and exciting challenges for artificial intelligence in these fields. These challenges include, but are not necessarily limited to, the ability to learn from other projects and to be inventive, to understand the potential and exploit novel computing paradigms and environments, to specify and adhere to stringent standards and robust statistical frameworks, to be integrative, and to embrace openness principles.

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Bátfai, Norbert. "A játékok és a mesterséges intelligencia mint a kultúra jövője – egy kísérlet a szubjektivitás elméletének kialakítására." Információs Társadalom 18, no. 2 (July 31, 2018): 28. http://dx.doi.org/10.22503/inftars.xviii.2018.2.2.

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A cikk célja a mesterséges intelligencia kutatásokat az emberi önmegismerés szolgálatába állítani. Ehhez egyrészt filozófiai hátteret biztosítani, másrészt a mesterséges intelligencia társadalmi elfogadottságát megalapozni. Tézisünk, hogy az emberi kultúra fenntartásához és fejlesztéséhez a játékokon és a mesterséges intelligencián keresztül vezet az út. E tézis alátámasztásnak támogatására kísérletet teszünk a szubjektivitás elméletének megalapozására. --- Games and artificial intelligence as the future of culture: an attempt to develop a theory of subjectivity The goal of this paper is to use artificial intelligence research to acquire more extensive knowledge of ourselves. On the one hand, we provide a philosophical background to facilitate this, and on the other hand, we try to improve the social acceptance of artificial intelligence. We argue that the way to maintain and further develop human culture is through gaming and artificial intelligence. In support of this thesis we make an attempt to create a theory of subjectivity. Keywords: artificial intelligence, complexity, entropy, meme, computer games, esport

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Beenish Zahra. "ARTIFICIAL INTELLIGENCE AND CYC." Lahore Garrison University Research Journal of Computer Science and Information Technology 1, no. 4 (December 29, 2017): 29–36. http://dx.doi.org/10.54692/lgurjcsit.2017.010412.

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Since 1984, it is enormous work going on for the accomplishing of the project Cyc (‗Saik‘). This work is based on knowledge of ―Artificial Intelligence‖ which is developed by the Cycorpcompany and by Douglas Lenat at MCC. It‘s a Microelectronics and Computer Technology Corporation (MCC) part for so long. The dominant aim of Cycorp to develop this system is to just clarify anything in semantical determination rather than syntactically determination of words commands by the machine in which Cyc is installed to do some job. The other objective was in the building of Cyc is to codify, in a form which is usable by the machine, where knowledge‘s millions piece that composes common sense of a normal human or the common sense made in the human brain. Cyc presents a proprietary schema of knowledge representation that utilized first-order relationships. The relationships that presents between first-order logic (FOL) and first-order theory (FOT). After a long time, in1986, Cyc’s developer (Douglas Lenat) estimate that the total effort required to complete Cyc project would be 250,000 rules and 350 man-years. In 1994, Cyc Project was the reason behind creating independency into Cycorp, in Austin, Texas. As it is a common phrase that "Every tree is a plant" and "Plants die eventually" so that why by the mean of this some knowledge representing pieces which are in the database are like trees and plants like structures. The engine is known as an inference engine, able to draw the obvious results and answer the questions correctly on asking that whether trees die. The Knowledge Base (KB) system, which is included in Cyc, contains more than one million humans like assertions, rules or commonsense ideas. These ideas, rules, and human-defined assertions are describing or formatted in the language known as CycL. They are based on the predication of calculus and many otherhuman-based sciences, which has syntax similar to that of the language ―LISP‖. Though some extend the work on the Cyc project continues as a ―Knowledge Engineering‖, which represents some facts about the world, and implementing effective mechanisms which are derived after reaching the basic level conclusion on that knowledge. As Cyc include the firstorder logic and first order theory, which exist in some relationship; so it definitely uses and handle some other branches for human-interaction like mathematics, philosophy, and linguistics. However, increasingly, the other aim of Cycorp while developing Cyc is involvingan ability, which is given to the Cyc system that it can communicate with end users, by use of CycL, processing of natural language, and can assist with the knowledge formation process through the machine learning.

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Більше джерел

Дисертації з теми "Other Artificial Intelligence"

Vaseigaran, Ajanth, and Gobi Sripathy. "Artificial Intelligence in Healthcare." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-296643.

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Healthcare systems play a critical role in ensuring people's health. Establishing accurate diagnoses is a vital element of this process. As sources highlight misdiagnoses and missed diagnoses as a common issue, a solution must be sought. Diagnostic errors are common in the emergency departments, which has been recognized as a stressful work environment. Today's industries are forced to deal with rapidly changing technological advances that result in reshaped systems, products, and services. Artificial Intelligence (AI) is one of such technologies that can work as a solution to diagnosis issues but comes with technical, ethical and legal challenges. Hence, the thesis intends to investigate how AI can affect the accuracy of diagnosis as well as how its integration in healthcare relates to the technical, ethical and legal aspects. The thesis begins with a literature review, which serves as a theoretical foundation and allows for a conceptual framework to be formed. The conceptual framework is used to select interviewees, which results in 12 interviews with professors, researchers, doctors and politicians. In addition, a survey is conducted to obtain the general public’s opinion on the matter. The findings present that AI is already mature enough to make more accurate diagnoses than doctors as well as release burden from medical practitioners in the form of administrative tasks. One obstacle is the incomplete data available since laws hinder sharing of patient data. Furthermore, the AI algorithms must be fit for all social minorities and not demonstrate racial discrimination. The European AI Alliance was established in 2018 with the aim to keep the technology in check. Similar initiatives can be created on a national- and regional level to maintain some form of control over its proper use.
Sjukvårdssystem utgör en avgörande roll för att säkerställa människors välmående och hälsa. Att fastställa korrekta diagnoser är en viktig del av denna process. Enligt källor är feldiagnoser och uteblivna diagnoser ett vanligt problem och bör därför lösas. Diagnostiska fel är vanligt förekommande på akutmottagningar, vilka karaktäriseras som en stressig arbetsmiljö. Dagens industrier tvingas hantera snabbt föränderliga tekniska framsteg som resulterar i omformade system, produkter och tjänster. Artificiell Intelligens (AI) är en av sådana tekniker som kan fungera som en lösning på diagnosfrågor. Dock kommer den med tekniska, etiska och legala utmaningar. Examensarbetet avser därför att undersöka hur AI kan påverka diagnosens precision samt hur integrationen i vården relaterar till de tekniska, etiska och legala aspekterna. Rapporten inleds med en litteraturstudie, vilket fungerar som en teoretisk grund och bidrar till att skapa ett konceptuellt ramverk. Det konceptuella ramverket används för att välja intervjupersoner, vilket resulterar i 12 intervjuer med professorer, forskare, läkare och politiker. Dessutom genomförs en enkätundersökning för att få allmänhetens åsikt i frågan. Rapportens resultat visar att AI redan är tillräckligt utvecklad för att göra en mer precisionssäker diagnos än en läkare samt kan avlasta läkare i form av administrativa uppgifter. Ett hinder är att den data som finns tillgänglig är ofullständig på grund av lagar som hindrar delning av patientdata. AI-algoritmerna måste dessutom vara lämpliga för alla sociala minoriteter och inte leda till rasdiskriminering. European AI Alliance grundades 2018 med målet att hålla tekniken i schack i förhållande till de etiska och legala aspekterna. Liknande initiativ kan skapas på nationell och regional nivå för att bibehålla någon form av kontroll över dess korrekta användning.

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Micael, Frideros. "Artificial Intelligence : Progress in business and society." Thesis, Blekinge Tekniska Högskola, Institutionen för industriell ekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16483.

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This thesis investigates the progress of corporate implementations of Artificial Intelligence and discusses the effects that this might have on the corporate sector as well as some implications on a societal level. The analysis is based on data from surveys conducted by Accenture, Bain & Company, Capgemini Digital Transformation Institute, Deloitte, Gartner Inc., McKinsey Global Institute and MIT Sloan Management Review & Boston Consulting Group. Over the last 3 years the adoptions of Artificial Intelligence have increased 2-3 times and the trend is expected to continue in the coming years as well, since 40-55 % of the surveyed companies are in the initial stages of AI adoption. Further, the growth rate in AI investments has been even more radical and increased 15-20 times over the last 7 years. Companies who have implemented AI report significant benefits and companies with a proactive strategy for Artificial Intelligence report higher profit margins than their industry competitors. Further the data indicates that companies that are successful in implementing AI have better general organizational capabilities, higher data & skills readiness and more AI focus in leadership and strategic planning. Another result in the study is that most managers in companies implementing AI expect that the technology will enable them to enter new markets and also that new competitors will enter their market. This will probably lead to increased competition and the results from other technology transitions indicate that this might force more companies to adopt AI to stay competitive. Regarding competence strategy some theorists have argued that companies without AI experience should compensate by acquiring a high tech start-up with the needed technology and competence. However, the data indicates that the most limiting factors for companies without AI experience are related to leadership and technical capabilities, not access to competence. It is only in later stages of the adoption process that access to competence becomes the primary limiting factor. The data gives mixed indications on AI consequences on employment. Half of the companies implementing AI expect job losses in the organization in the coming 3 years, while almost a third expects AI to lead to new jobs. However, the data also suggests that existing employees will need to change their skill sets. Therefor both the public and private sector will need to adapt and find ways to support employees that need to re-educate themselves.

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Ramsahai, Roland Ryan. "Causal inference with instruments and other supplementary variables." Thesis, University of Oxford, 2008. http://ora.ox.ac.uk/objects/uuid:df2961da-0843-421f-8be4-66a92e6b0d13.

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Instrumental variables have been used for a long time in the econometrics literature for the identification of the causal effect of one random variable, B, on another, C, in the presence of unobserved confounders. In the classical continuous linear model, the causal effect can be point identified by studying the regression of C on A and B on A, where A is the instrument. An instrument is an instance of a supplementary variable which is not of interest in itself but aids identification of causal effects. The method of instrumental variables is extended here to generalised linear models, for which only bounds on the causal effect can be computed. For the discrete instrumental variable model, bounds have been derived in the literature for the causal effect of B on C in terms of the joint distribution of (A,B,C). Using an approach based on convex polytopes, bounds are computed here in terms of the pairwise (A,B) and (A,C) distributions, in direct analogy to the classic use but without the linearity assumption. The bounding technique is also adapted to instrumental models with stronger and weaker assumptions. The computation produces constraints which can be used to invalidate the model. In the literature, constraints of this type are usually tested by checking whether the relative frequencies satisfy them. This is unsatisfactory from a statistical point of view as it ignores the sampling uncertainty of the data. Given the constraints for a model, a proper likelihood analysis is conducted to develop a significance test for the validity of the instrumental model and a bootstrap algorithm for computing confidence intervals for the causal effect. Applications are presented to illustrate the methods and the advantage of a rigorous statistical approach. The use of covariates and intermediate variables for improving the efficiency of causal estimators is also discussed.

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Zhao, Haixiang. "Artificial Intelligence Models for Large Scale Buildings Energy Consumption Analysis." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00658767.

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Анотація:

The energy performance in buildings is influenced by many factors, such as ambient weather conditions, building structure and characteristics, occupancy and their behaviors, the operation of sub-level components like Heating, Ventilation and Air-Conditioning (HVAC) system. This complex property makes the prediction, analysis, or fault detection/diagnosis of building energy consumption very difficult to accurately and quickly perform. This thesis mainly focuses on up-to-date artificial intelligence models with the applications to solve these problems. First, we review recently developed models for solving these problems, including detailed and simplified engineering methods, statistical methods and artificial intelligence methods. Then we simulate energy consumption profiles for single and multiple buildings, and based on these datasets, support vector machine models are trained and tested to do the prediction. The results from extensive experiments demonstrate high prediction accuracy and robustness of these models. Second, Recursive Deterministic Perceptron (RDP) neural network model is used to detect and diagnose faulty building energy consumption. The abnormal consumption is simulated by manually introducing performance degradation to electric devices. In the experiment, RDP model shows very high detection ability. A new approach is proposed to diagnose faults. It is based on the evaluation of RDP models, each of which is able to detect an equipment fault.Third, we investigate how the selection of subsets of features influences the model performance. The optimal features are selected based on the feasibility of obtaining them and on the scores they provide under the evaluation of two filter methods. Experimental results confirm the validity of the selected subset and show that the proposed feature selection method can guarantee the model accuracy and reduces the computational time.One challenge of predicting building energy consumption is to accelerate model training when the dataset is very large. This thesis proposes an efficient parallel implementation of support vector machines based on decomposition method for solving such problems. The parallelization is performed on the most time-consuming work of training, i.e., to update the gradient vector f. The inner problems are dealt by sequential minimal optimization solver. The underlying parallelism is conducted by the shared memory version of Map-Reduce paradigm, making the system particularly suitable to be applied to multi-core and multiprocessor systems. Experimental results show that our implementation offers a high speed increase compared to Libsvm, and it is superior to the state-of-the-art MPI implementation Pisvm in both speed and storage requirement.

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Nordahl, Per. "Attitudes to decision-making under risk supported by artificial intelligence and humans : Perceived risk, reliability and acceptance." Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-29384.

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Анотація:

The purpose of this investigation was to explore how decision situations with varying degrees of perceived risk affect people’s attitudes to human and artificial intelligence (AI) decision-making support. While previous studies have focused on the trust, fairness, reliability and fear of artificial intelligence, robots and algorithms in relation to decision support, the risk inherent in the decision situation has been largely ignored. An online survey with a mixed approach was conducted to investigate artificial intelligence and human decision support in risky situations. Two scenarios were presented to the survey participants. In the scenario where the perceived situational risk was low, selecting a restaurant, people expressed a positive attitude towards relying on and accepting recommendations provided by an AI. In contrast, in the perceived high-risk scenario, purchasing a home, people expressed an equal reluctance to rely on or accept both AI and human recommendations. The limitations of this investigation are primarily related to the challenges of creating a common understanding of concepts such as AI and a relatively homogenous survey group. The implication of this study is that AI may currently be best applied to situations characterized by perceived low risk if the intention is to convince people to rely on and accept AI recommendations, and in the future if AI becomes autonomous, to accept decisions.

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Dittmar, George William. "Object Detection and Recognition in Natural Settings." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/926.

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Анотація:

Much research as of late has focused on biologically inspired vision models that are based on our understanding of how the visual cortex processes information. One prominent example of such a system is HMAX [17]. HMAX attempts to simulate the biological process for object recognition in cortex based on the model proposed by Hubel & Wiesel [10]. This thesis investigates the ability of an HMAX-like system (GLIMPSE [20]) to perform object-detection in cluttered natural scenes. I evaluate these results using the StreetScenes database from MIT [1, 8]. This thesis addresses three questions: (1) Can the GLIMPSE-based object detection system replicate the results on object-detection reported by Bileschi using HMAX? (2) Which features computed by GLIMPSE lead to the best object-detection performance? (3) What effect does elimination of clutter in the training sets have on the performance of our system? As part of this thesis, I built an object detection and recognition system using GLIMPSE [20] and demonstrate that it approximately replicates the results reported in Bileschi's thesis. In addition, I found that extracting and combining features from GLIMPSE using different layers of the HMAX model gives the best overall invariance to position, scale and translation for recognition tasks, but comes with a much higher computational overhead. Further contributions include the creation of modified training and test sets based on the StreetScenes database, with removed clutter in the training data and extending the annotations for the detection task to cover more objects of interest that were not in the original annotations of the database.

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Liliequist, Erik. "Artificial Intelligence - Are there any social obstacles? : An empirical study of social obstacles." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229506.

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Анотація:

Artificial Intelligence is currently one of the most talked about topics with regard to technical development. The possibilities are enormous and it might revolutionize how we live our lives. There are talk of robots and AI removing the need for human workers. At the same time there are also those who view this as deeply troublesome. Either from an individual perspective, asking the question what we should do once we do not need to work more? Or from an existential perspective, raising issues of what responsibilities we have as humans and what it means to be human? This study does not aim to answer these grand questions, but rather shift the focus to the near future of three to five years. Yet, there is still a focus on the social aspects of the development of AI. What are the perceived greatest social issues and obstacles for a continued implementation of AI solutions in society? To answer these question interviews have been conducted with representatives for the Swedish society, ranging from politicians, union and employers’ organizations to philosophers and AI researchers. Further a literature study has been made of similar studies, comparing and reflecting their findings with the views of the interviewees. In short, the interviewees have a very positive view of AI in the near future, believing that a continued implementation would go relatively smoothly. Yet, they pointed to a few key obstacles that might need to be addressed. Mainly there is a risk of increased polarization of wages and power due to AI, although stressed that it depends on how we use the technology rather than the technology itself. Another obstacle was connected to individual uncertainty of the development of AI, causing a fear of what might happen. Further, several different ethical issues were raised. There was an agreement that we need to address these as soon as possible, but they did not view this as an obstacle.

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Mendonca, Sean Christopher. "WRITING FOR EACH OTHER: DYNAMIC QUEST GENERATION USING IN SESSION PLAYER BEHAVIORS IN MMORPG." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2146.

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Анотація:

Role-playing games (RPGs) rely on interesting and varied experiences to maintain player attention. These experiences are often provided through quests, which give players tasks that are used to advance stories or events unfolding in the game. Traditional quests in video games require very specific conditions to be met, and for participating members to advance them by carrying out pre-defined actions. These types of quests are generated with perfect knowledge of the game world and are able to force desired behaviors out of the relevant non-player characters (NPCs). This becomes a major issue in massive multiplayer online (MMO) when other players can often disrupt the conditions needed for quests to unfold in a believable and immersive way, leading to the absence of a genuine multiplayer RPG experience. Our proposed solution is to dynamically create quests from real-time information on the unscripted actions of other NPCs and players in a game. This thesis shows that it is possible to create logical quests without global information knowledge, pre-defined story-trees, or prescribed player and NPC behavior. This allows players to become involved in storylines without having to perform any specific actions. Results are shown through a game scenario created from the Panoptyk Engine, a game engine in early development designed to test AI reasoning with information and the removal of the distinction between NPC and human players. We focus on quests issued by the NPC faction leaders of several in-game groups known as factions. Our generated quests are created logically from the pre-defined personality of each NPC leader, their memory of previous events, and information given to them by in-game sources. Long-spanning conflicts are seen to emerge from factions issuing quests against each other; these conflicts can be represented in a coherent narrative. A user study shows that players felt quests were logical, that players were able to recognize quests were based on events happening in the game, and that players experienced follow-up consequences from their actions in quests.

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McCullough, Kevin. "EXPLORING THE RELATIONSHIP OF THE CLOSENESS OF A GENETIC ALGORITHM’S CHROMOSOME ENCODING TO ITS PROBLEM SPACE." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/247.

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For historical reasons, implementers of genetic algorithms often use a haploid binary primitive type for chromosome encoding. I will demonstrate that one can reduce development effort and achieve higher fitness by designing a genetic algorithm with an encoding scheme that closely matches the problem space. I will show that implicit parallelism does not result in binary encoded chromosomes obtaining higher fitness scores than other encodings. I will also show that Hamming distances should be understood as part of the relationship between the closeness of an encoding to the problem instead of assuming they should always be held constant. Closeness to the problem includes leveraging structures that are intended to model a specific aspect of the environment. I will show that diploid chromosomes leverage abeyance to benefit their adaptability in dynamic environments. Finally, I will show that if not all of the parts of the GA are close to the problem, the benefits of the parts that are can be negated by the parts that are not

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Ates, Mehmet. "Artificial intelligence in banking : A case study of the introduction of a virtual assistant into customer service." Thesis, Högskolan i Jönköping, Internationella Handelshögskolan, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-41144.

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The usage of artificial intelligence in banking is an important theme within entrepreneurial research. The purpose of the study was to analyse the motivations, challenges and opportunities for Swedish banking institutes to implement artificial intelligence based solutions into their customer service process. The research is based on a case study of the Swedish banking institute Swedbank AB, who introduced an AI based virtual assistant (Nina) to deal with customer requests. For the qualitative study, interviews with Swedish banking customer and experts were conducted. Further, to understand the managerial motivations of Swedbank, a theory of Moore (2008) regarding innovation management was applied. The findings display that Nina improved the service spectrum of Swedbank with the potential of decreasing costs, while maintaining customer satisfaction. Further, the results displayed a high acceptance of new technologies from the customer perspective. This provides the foundation for Swedbank to introduce further artificial intelligence based services. Banking institutes and other service oriented organisations with high customer interaction can use the implications of the thesis when considering to more effectively handle customer requests.

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Книги з теми "Other Artificial Intelligence"

Jaillant, Lise, ed. Archives, Access and Artificial Intelligence. Bielefeld, Germany: Bielefeld University Press / transcript Verlag, 2022. http://dx.doi.org/10.14361/9783839455845.

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Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets.

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American Nuclear Society Topical Meeting on Artificial Intelligence and Other Innovative Computer Applications (1987 Snowbird, Utah). Artificial intelligence and other innovative computer applications in the nuclear industry. New York: Plenum Press, 1988.

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Majumdar, M. Catherine, Debu Majumdar, and John I. Sackett, eds. Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9.

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Majumdar, M. Catherine. Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Boston, MA: Springer US, 1988.

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Holmes, Dawn E. Data Mining: Foundations and Intelligent Paradigms: Volume 3: Medical, Health, Social, Biological and other Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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1970-, Timmis Jonathan, ed. Artificial immune systems: A new computational intelligence approach. London: Springer, 2002.

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Joseph, Williams. BOTS and other Internet beasties. Indianapolis, IN: Sams.net, 1996.

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John, Mylopoulos, Reiter Ray, Australian Computer Society. National Committee on Artificial Intelligence and Expert Systems, and International Joint Conferences on Artificial Intelligence., eds. IJCAI-91: Proceedings of the Twelfth International Conference on Artificial Intelligence, Darling Harbour, Sydney, Australia, 24-30 August 1991 ; sponsored by the International Joint Conferences on Artificial Intelligence, Inc. (IJCAII) ; co-sponsored and hosted by the National Committee on Artificial Intelligence and Expert Systems (NCAIES of the Australian Computer Society (ACS) ; with support and cooperation from the Australian Government and other Australian corporations and institutions. [S.l.]: IJCAII, 1991.

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International Conference on Computer Vision (8th 2001 Vancouver, British Columbia). Eighth IEEE International Conference on Computer Vision: July 7-14, 2001, Vancouver, British Columbia, Canada. Los Alamitos, Calif: IEEE Computer Society, 2001.

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Rezaul, Begg, and Palaniswami Marimuthu, eds. Computational intelligence for movement sciences: Neural networks, support vector machines, and other emerging technologies. Hershey, PA: Idea Group Pub., 2006.

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Частини книг з теми "Other Artificial Intelligence"

Michalewicz, Zbigniew. "Evolution Strategies and Other Methods." In Artificial Intelligence, 127–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-662-02830-8_9.

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Thomason, Richmond H. "Modeling the Beliefs of other Agents." In Logic-Based Artificial Intelligence, 375–403. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-1567-8_17.

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Ventura, Dan. "Can a Computer be Lucky? And Other Ridiculous Questions Posed by Computational Creativity." In Artificial General Intelligence, 208–17. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09274-4_20.

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Meda, Lakshmi N. K., and Hamid Jahankhani. "Artificial Intelligence Based Malicious Traffic Detection." In Blockchain and Other Emerging Technologies for Digital Business Strategies, 21–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98225-6_2.

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Baum, Seth D., Robert de Neufville, Anthony M. Barrett, and Gary Ackerman. "Lessons for Artificial Intelligence from Other Global Risks." In The Global Politics of Artificial Intelligence, 103–32. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9780429446726-5.

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Finkel, Raphael, Victor W. Marek, and Mirosλaw Truszczyński. "Constraint Lingo: A Program for Solving Logic Puzzles and Other Tabular Constraint Problems." In Logics in Artificial Intelligence, 513–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45757-7_44.

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Dhar, Vasant. "A Comparison of GLOWER and Other Machine Learning Methods for Investment Decision Making." In Progress in Artificial Intelligence, 5. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45329-6_3.

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Stein Smith, Sean. "ESG & Other Emerging Technology Applications." In Blockchain, Artificial Intelligence and Financial Services, 175–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29761-9_14.

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Colombo, Moreno, Edy Portmann, and Pascal Kaufmann. "Artificial Intelligence – The Mindfire Foundation and Other Initiatives." In Cognitive Computing, 67–85. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-27941-7_3.

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Mündemann, Friedhelm. "Fuzzy concepts for predicting the behaviour of other drivers on a highway." In Fuzzy Logic in Artificial Intelligence, 165–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-56920-0_18.

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Тези доповідей конференцій з теми "Other Artificial Intelligence"

"Constrained Artificial Intelligence - Program." In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2022. http://dx.doi.org/10.1109/percomworkshops53856.2022.9767285.

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Bruce, George, and Farshid Khalili. "Assessment of The Future Demolition of Ships Using Artificial Intelligence." In Recycling of Ships and Other Marine Structures. RINA, 2005. http://dx.doi.org/10.3940/rina.rcy.2005.09.

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"Constrained Artificial Intelligence - Welcome and Committees." In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops). IEEE, 2022. http://dx.doi.org/10.1109/percomworkshops53856.2022.9767268.

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"Other reviewers." In 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT). IEEE, 2021. http://dx.doi.org/10.1109/gcaiot53516.2021.9692945.

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Montañez, George D. "Detecting Intelligence - The Turing Test and Other Design Detection Methodologies." In 8th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005823705170523.

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Lučić, Sonja. "VEŠTAČKA INTELIGENCIJA I PATENTNO PRAVO." In XVIII Majsko savetovanje. University of Kragujevac, Faculty of Law, 2022. http://dx.doi.org/10.46793/xviiimajsko.479l.

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Artificial intelligence is a field of technology that is developing intensively. Along with the development of artificial intelligence, the issue of its patent protection has become topical. Artificial intelligence systems are based on highly developed algorithms and mathematical models, phenomena with which patent law is traditionally in conflict. This issue is not just a national or European problem. There is also an intensive debate in the United States about the patentability of artificially intelligent systems. The author deals with the question of whether artificially intelligent systems can enjoy patent protection. The paper analyzes the case of "DABUS" which refers to an international patent application in which the artificially intelligent system DABUS is listed as the inventor. Numerous intellectual property offices around the world (eg American, British, German, Australian, EPO) have rejected such a patent application. On the other hand, the Federal Court of Australia has ruled that under the Australian Patent Act AI could be listed as the inventor. Recognition of AI as the inventor (not the owner) of inventions generated by artificial intelligence can have certain consequences, including in the field of copyright.

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Villata, Serena. "Artificial Argumentation for Humans." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/818.

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The latest years have seen an increasing interest in the topic of Artificial Intelligence (AI), the challenges it is facing, and the recent advances it has achieved, e.g., intelligent personal assistants. Differently from the past, where research on AI was mainly confined in research labs, the topic is now attracting interest from a wider audience, including policy-makers, information technology companies, and philosophers. Alas, these advances have also raised a number of concerns on AI’s social, economic, and legal impact. Hence, the definition of design principles and automated methods to support transparent intelligent machine deliberation is highly desirable. Argumentation is important for handling conflicting beliefs, assumptions, opinions, goals, and many other mental attitudes. Argumentation pervades human intelligent behavior, and I believe that it is a mandatory element to conceive autonomous artificial machines that can exploit argumentation models and tools in the cognitive tasks they are required to carry out. Results in this area will allow reducing the gap between humans and machines towards a good AI hybrid society.

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Hanada, Eisuke, Koki Wada, Koji Oda, Kouki Nishi, and Koutaro Kawazoe. "Practical use of Artificial Intelligence for Clinical Staff Other than Physicians." In 2018 IEEE 8th International Conference on Consumer Electronics - Berlin. IEEE, 2018. http://dx.doi.org/10.1109/icce-berlin.2018.8576166.

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Amanatidis, Georgios, Georgios Birmpas, Aris Filos-Ratsikas, Alexandros Hollender, and Alexandros A. Voudouris. "Maximum Nash Welfare and Other Stories About EFX." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/4.

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We consider the classic problem of fairly allocating indivisible goods among agents with additive valuation functions and explore the connection between two prominent fairness notions: maximum Nash welfare (MNW) and envy-freeness up to any good (EFX). We establish that an MNW allocation is always EFX as long as there are at most two possible values for the goods, whereas this implication is no longer true for three or more distinct values. As a notable consequence, this proves the existence of EFX allocations for these restricted valuation functions. While the efficient computation of an MNW allocation for two possible values remains an open problem, we present a novel algorithm for directly constructing EFX allocations in this setting. Finally, we study the question of whether an MNW allocation implies any EFX guarantee for general additive valuation functions under a natural new interpretation of approximate EFX allocations.

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Nam, Hyunwoo, Suyeong Kwak, and Chulmin Jun. "Comparison of Improved Floor Field Model and Other Models." In 8th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005658700950101.

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Звіти організацій з теми "Other Artificial Intelligence"

Rudd, Ian. Leveraging Artificial Intelligence and Robotics to Improve Mental Health. Intellectual Archive, July 2022. http://dx.doi.org/10.32370/iaj.2710.

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Artificial Intelligence (AI) is one of the oldest fields of computer science used in building structures that look like human beings in terms of thinking, learning, solving problems, and decision making (Jovanovic et al., 2021). AI technologies and techniques have been in application in various aspects to aid in solving problems and performing tasks more reliably, efficiently, and effectively than what would happen without their use. These technologies have also been reshaping the health sector's field, particularly digital tools and medical robotics (Dantas & Nogaroli, 2021). The new reality has been feasible since there has been exponential growth in the patient health data collected globally. The different technological approaches are revolutionizing medical sciences into dataintensive sciences (Dantas & Nogaroli, 2021). Notably, with digitizing medical records supported the increasing cloud storage, the health sector created a vast and potentially immeasurable volume of biomedical data necessary for implementing robotics and AI. Despite the notable use of AI in healthcare sectors such as dermatology and radiology, its use in psychological healthcare has neem models. Considering the increased mortality and morbidity levels among patients with psychiatric illnesses and the debilitating shortage of psychological healthcare workers, there is a vital requirement for AI and robotics to help in identifying high-risk persons and providing measures that avert and treat mental disorders (Lee et al., 2021). This discussion is focused on understanding how AI and robotics could be employed in improving mental health in the human community. The continued success of this technology in other healthcare fields demonstrates that it could also be used in redefining mental sicknesses objectively, identifying them at a prodromal phase, personalizing the treatments, and empowering patients in their care programs.

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Hunt, Will, and Owen Daniels. Sustaining and Growing the U.S. Semiconductor Advantage: A Primer. Center for Security and Emerging Technology, June 2022. http://dx.doi.org/10.51593/20220006.

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As an integral player in advanced semiconductor supply chains, the United States enjoys advantages over China in producing and accessing chips for artificial intelligence and other leading-edge computing technologies. However, a lack of domestic production capacity threatens U.S. semiconductor access. The United States can strengthen its advantages by working with allies and partners to prevent China from producing leading-edge chips and by reshoring its own domestic chipmaking capacity.

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Cary, Dakota. China’s CyberAI Talent Pipeline. Center for Security and Emerging Technology, July 2021. http://dx.doi.org/10.51593/2020ca017.

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To what extent does China’s cultivation of talent in cybersecurity and AI matter in terms of competitiveness with other countries? Right now, it seems to have an edge: China’s 11 World-Class Cybersecurity Schools offer more classes on artificial intelligence and machine learning than do the 20 U.S. universities certified as Centers of Academic Excellence in Cyber Operations. This policy brief recommends tracking 13 research grants from the National Science Foundation that attempt to integrate AI into cybersecurity curricula.

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Phinisee, Eri, Autumn Toney, and Melissa Flagg. AI and Industry: Postings and Media Portrayals. Center for Security and Emerging Technology, May 2021. http://dx.doi.org/10.51593/20200059.

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Artificial intelligence is said to be transforming the global economy and society in what some dub the “fourth industrial revolution.” This data brief analyzes media representations of AI and the alignments, or misalignments, with job postings that include the AI-related skills needed to make AI a practical reality. This potential distortion is important as the U.S. Congress places an increasing emphasis on AI. If government funds are shifted away from other areas of science and technology, based partly on the representations that leaders and the public are exposed to in the media, it is important to understand how those representations align with real jobs across the country.

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Lewis, Dustin, ed. A Compilation of Materials Apparently Reflective of States’ Views on International Legal Issues pertaining to the Use of Algorithmic and Data-reliant Socio-technical Systems in Armed Conflict. Harvard Law School Program on International Law and Armed Conflict, December 2020. http://dx.doi.org/10.54813/cawz3627.

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This document is a compilation of materials that at least appear to be reflective of one or more states’ views on international legal issues pertaining to the actual or possible use of algorithmic and data-reliant socio-technical systems in armed conflict. In September of 2018, the Harvard Law School Program on International Law and Armed Conflict (HLS PILAC) commenced a project titled “International Legal and Policy Dimensions of War Algorithms: Enduring and Emerging Concerns.”[1] The project builds on the program’s earlier research and policy initiative on war-algorithm accountability. A goal of the current project is to help strengthen international debate and inform policymaking on the ways that artificial intelligence and complex computer algorithms are transforming war, as well as how international legal and policy frameworks already govern, and might further regulate, the design, development, and use of those technologies. The project is financially supported by the Ethics and Governance of Artificial Intelligence Fund. In creating this compilation, HLS PILAC seeks in part to provide a resource through which the positions of states with divergent positions on certain matters potentially of international public concern can be identified. Legal aspects of war technologies are more complex than some governments, scholars, and advocates allow. In the view of HLS PILAC, knowledge of the legal issues requires awareness of the multiple standpoints from which these arguments are fashioned. An assumption underlying how we approach these inquiries is that an assessment concerning international law in this area ought to take into account the perspectives of as many states (in addition to other relevant actors) as possible.

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Chen, Maggie, and Christian Volpe Martincus. Digital Technologies and Globalization: A Survey of Research and Policy Applications. Inter-American Development Bank, March 2022. http://dx.doi.org/10.18235/0004117.

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In recent years, the world has witnessed the rise of multiple specific digital technologies, including online trade platforms, robotics, artificial intelligence (AI), 3D printing, cloud computing, blockchain, and financial technology (fintech). These digital technologies are fundamentally transforming the ways that firms and individualsas both workers and consumerscommunicate, search, trade, and invest. They are also substantially changing how governments design and implement trade and investment policies and programs and, in so doing, how they interact with firms, individuals, and each other. This paper reviews the growing empirical literature on the trade, investment, and broader development effects of the adoption of specific digital technologies. It also describes the policy applications of these technologies and discusses the incipient empirical literature on the impacts thereof. Based on this review, it identifies several open questions and avenues of future research that may be useful for deepening our understanding of digital technologies and their policy implications.

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Kriegel, Francesco. Optimal Fixed-Premise Repairs of EL TBoxes (Extended Version). Technische Universität Dresden, 2022. http://dx.doi.org/10.25368/2022.321.

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Reasoners can be used to derive implicit consequences from an ontology. Sometimes unwanted consequences are revealed, indicating errors or privacy-sensitive information, and the ontology needs to be appropriately repaired. The classical approach is to remove just enough axioms such that the unwanted consequences vanish. However, this is often too rough since mere axiom deletion also erases many other consequences that might actually be desired. The goal should not be to remove a minimal number of axioms but to modify the ontology such that only a minimal number of consequences is removed, including the unwanted ones. Specifically, a repair should rather be logically entailed by the input ontology, instead of being a subset. To this end, we introduce a framework for computing fixed-premise repairs of $\mathcal{EL}$ TBoxes. In the first variant the conclusions must be generalizations of those in the input TBox, while in the second variant no such restriction is imposed. In both variants, every repair is entailed by an optimal one and, up to equivalence, the set of all optimal repairs can be computed in exponential time. A prototypical implementation is provided. In addition, we show new complexity results regarding gentle repairs. This is an extended version of an article accepted at the 45th German Conference on Artificial Intelligence (KI 2022).

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Borrett, Veronica, Melissa Hanham, Gunnar Jeremias, Jonathan Forman, James Revill, John Borrie, Crister Åstot, et al. Science and Technology for WMD Compliance Monitoring and Investigations. The United Nations Institute for Disarmament Research, December 2020. http://dx.doi.org/10.37559/wmd/20/wmdce11.

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The integration of novel technologies for monitoring and investigating compliance can enhance the effectiveness of regimes related to weapons of mass destruction (WMD). This report looks at the potential role of four novel approaches based on recent technological advances – remote sensing tools; open-source satellite data; open-source trade data; and artificial intelligence (AI) – in monitoring and investigating compliance with WMD treaties. The report consists of short essays from leading experts that introduce particular technologies, discuss their applications in WMD regimes, and consider some of the wider economic and political requirements for their adoption. The growing number of space-based sensors is raising confidence in what open-source satellite systems can observe and record. These systems are being combined with local knowledge and technical expertise through social media platforms, resulting in dramatically improved coverage of the Earth’s surface. These open-source tools can complement and augment existing treaty verification and monitoring capabilities in the nuclear regime. Remote sensing tools, such as uncrewed vehicles, can assist investigators by enabling the remote collection of data and chemical samples. In turn, this data can provide valuable indicators, which, in combination with other data, can inform assessments of compliance with the chemical weapons regime. In addition, remote sensing tools can provide inspectors with real time two- or three-dimensional images of a site prior to entry or at the point of inspection. This can facilitate on-site investigations. In the past, trade data has proven valuable in informing assessments of non-compliance with the biological weapons regime. Today, it is possible to analyse trade data through online, public databases. In combination with other methods, open-source trade data could be used to detect anomalies in the biological weapons regime. AI and the digitization of data create new ways to enhance confidence in compliance with WMD regimes. In the context of the chemical weapons regime, the digitization of the chemical industry as part of a wider shift to Industry 4.0 presents possibilities for streamlining declarations under the Chemical Weapons Convention (CWC) and for facilitating CWC regulatory requirements.

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Gehlhaus, Diana, and Ilya Rahkovsky. U.S. AI Workforce: Labor Market Dynamics. Center for Security and Emerging Technology, April 2021. http://dx.doi.org/10.51593/20200086.

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A lack of good data on the U.S. artificial intelligence workforce limits the potential effectiveness of policies meant to increase and cultivate this cadre of talent. In this issue brief, the authors bridge that information gap with new analysis on the state of the U.S. AI workforce, along with insight into the ongoing concern over AI talent shortages. Their findings suggest some segments of the AI workforce are more likely than others to be experiencing a supply-demand gap.

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Jones, Emily, Beatriz Kira, Anna Sands, and Danilo B. Garrido Alves. The UK and Digital Trade: Which way forward? Blavatnik School of Government, February 2021. http://dx.doi.org/10.35489/bsg-wp-2021/038.

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The internet and digital technologies are upending global trade. Industries and supply chains are being transformed, and the movement of data across borders is now central to the operation of the global economy. Provisions in trade agreements address many aspects of the digital economy – from cross-border data flows, to the protection of citizens’ personal data, and the regulation of the internet and new technologies like artificial intelligence and algorithmic decision-making. The UK government has identified digital trade as a priority in its Global Britain strategy and one of the main sources of economic growth to recover from the pandemic. It wants the UK to play a leading role in setting the international standards and regulations that govern the global digital economy. The regulation of digital trade is a fast-evolving and contentious issue, and the US, European Union (EU), and China have adopted different approaches. Now that the UK has left the EU, it will need to navigate across multiple and often conflicting digital realms. The UK needs to decide which policy objectives it will prioritise, how to regulate the digital economy domestically, and how best to achieve its priorities when negotiating international trade agreements. There is an urgent need to develop a robust, evidence-based approach to the UK’s digital trade strategy that takes into account the perspectives of businesses, workers, and citizens, as well as the approaches of other countries in the global economy. This working paper aims to inform UK policy debates by assessing the state of play in digital trade globally. The authors present a detailed analysis of five policy areas that are central to discussions on digital trade for the UK: cross-border data flows and privacy; internet access and content regulation; intellectual property and innovation; e-commerce (including trade facilitation and consumer protection); and taxation (customs duties on e-commerce and digital services taxes). In each of these areas the authors compare and contrast the approaches taken by the US, EU and China, discuss the public policy implications, and examine the choices facing the UK.

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