Digital Commons Network^™

Human-Machine Teaming And Its Legal And Ethical Implications, Jim Q. Chen, Thomas Wingfield

Military Cyber Affairs

Humans rely on machines in accomplishing missions while machines need humans to make them more intelligent and more powerful. Neither side can go without the other, especially in complex environments when autonomous mode is initiated. Things are becoming more complicated when law and ethical principles should be applied in these complex environments. One of the solutions is human-machine teaming, as it takes advantage of both the best humans can offer and the best that machines can provide. This article intends to explore ways of implementing law and ethical principles in artificial intelligence (AI) systems using human-machine teaming. It examines the …

Automating Autism: Disability, Discourse, And Artificial Intelligence, Os Keyes

The Journal of Sociotechnical Critique

As Artificial Intelligence (AI) systems shift to interact with new domains and populations, so does AI ethics: a relatively nascent subdiscipline that frequently concerns itself with questions of “fairness” and “accountability.” This fairness-centred approach has been criticized for (amongst other things) lacking the ability to address discursive, rather than distributional, injustices. In this paper I simultaneously validate these concerns, and work to correct the relative silence of both conventional and critical AI ethicists around disability, by exploring the narratives deployed by AI researchers in discussing and designing systems around autism. Demonstrating that these narratives frequently perpetuate a dangerously dehumanizing model …

An Artificial Intelligence-Based, Personalized Smartphone App To Improve Childhood Immunization Coverage And Timelines Among Children In Pakistan: Protocol For A Randomized Controlled Trial, Abdul Momin Kazi, Saad Ahmed Qazi, Sadori Khawaja, Nazia Ahsan, Rao Moueed Ahmed, Muhammad Ayub Khan Mughal, Hussain Kalimuddin, Yasir Rauf, Mehreen Raza, Saima Jamal

Department of Paediatrics and Child Health

Background: The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI.
Objective: The primary objectives of this study are to …

A Comparative Study On Artificial Intelligence Curricula, Li Li

Electronic Thesis and Dissertation Repository

This research is a comparative analysis of four K-12 AI curricula to recognize and interpret their basic elements and pedagogical approaches. Guided by (socio) constructivist and constructionist theories as the theoretical framework, qualitative document analysis is applied as the research methodology. Schwab’s four commonplaces serve as the initial analytical framework. A (socio) constructivism and constructionism lens is also used to compare the curricula. The major findings are 1. The four curricula are different in their coverage of subject matters with the curriculum from the UK covering the widest and most balanced range of subject matters. 2. The four curricula apply, …

Digital Transformation Of Corporate Governance In Uzbekistan: Current State, Challenges And Perspectives, E. Khoshimov Phd, F. Makhmudaliev

International Finance and Accounting

Corporate Governance is a concept that will regulate the correctness and effectiveness of the company operations. Currently the world trends are indicating upgraded version of the management – Corporate Governance 3.0, which entails the usage of well-balanced Board of Directors as well as employment of digital technologies in the managing of the companies. This article provides an analysis of the contemporary conditions related to corporate governance in Uzbekistan and provides a list of recommendations to tackle the shortcomings. The setting of the Board of directors using competence based balanced approach, employing tokenization for financial asset emission and use of artificial …

Price Prediction And Valuation Using Data Mining In Dubai Real Estate Market, Abdulla Alhathboor

Theses

The purpose of this study is to find out the impact of data mining in predicting prices and values of real estate units in the Dubai real estate market. This market has always been one of the biggest markets in the economy of any nation worldwide and has always been considered one of the biggest indicators on the health of any economy. After the devastating crash of the world economy in 2008, many real estate projects were halted and economies are still recovering from that incident. Real estate brokers and agents found it difficult to sell any property during that …

Algorithmic Opacity, Private Accountability, And Corporate Social Disclosure In The Age Of Artificial Intelligence, Sylvia Lu

Vanderbilt Journal of Entertainment & Technology Law

Today, firms develop machine-learning algorithms to control human decisions in nearly every industry, creating a structural tension between commercial opacity and democratic transparency. In many of their commercial applications, advanced algorithms are technically complicated and privately owned, which allows them to hide from legal regimes and prevents public scrutiny. However, they may demonstrate their negative effects—erosion of democratic norms, damages to financial gains, and extending harms to stakeholders—without warning. Nevertheless, because the inner workings and applications of algorithms are generally incomprehensible and protected as trade secrets, they can be completely shielded from public surveillance. One of the solutions to this …

Imparting 3d Representations To Artificial Intelligence For A Full Assessment Of Pressure Injuries., Sofia Zahia

Electronic Theses and Dissertations

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning …

Computational Cognition And Deep Learning, Andy Malinsky

The Compass

No abstract provided.

Innovation And New Technologies In Spine Surgery, Circa 2020: A Fifty-Year Review., G. Bryan Cornwall, Andrea Davis, William R. Walsh, Ralph J. Mobbs, Alexander Vaccaro

Rothman Institute Faculty Papers

Spine surgery (lumbar, cervical, deformity, and entire spine) has increased in volume and improved in outcomes over the past 50 years because of innovations in surgical techniques and introduction of new technologies to improve patient care. Innovation is described as a process to add value or create change in an enterprise's economic or social potential. This mini review will assess two of three assessments of innovation in spine surgery: scientific publications and patents issued. The review of both scientific publications and issued patents is a unique assessment. The third assessment of innovation: regulatory clearances of medical devices and equipment for …

Features Of Intelligent Models In The Theory Of Robotic And Mechatronic Systems, Kh.N. Nazarov, N.R. Matyokubov, T.O. Rakhimov

Chemical Technology, Control and Management

The article discusses the features of intelligent models and tasks in the theory of mechatronic and robotic systems, the algebraic model of artificial intelligence, formalized types of intellectual tasks, intelligent models of the problem area, which are distinguished by their versatility and clarity. Intellectual models and tasks in the field of the theory of robotic systems are formally presented. As part of a set of inference rules, intelligent models as universal rules use rules of substitution and conclusion, similar to the deductive rules of inference in propositional and predicate calculus, and the rules of meaning. The systematization of t the …

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …

Notes On Artificial Intelligence, Brian Meyer

Current Issues in Emerging eLearning

From leveraging insights in data-driven marketing, to utilizing machine-learning algorithms for medicine, artificial intelligence has been seamlessly integrated in industry to optimize professional performance. While AI technologies attract their fair share of critics, their prevalence in the public domain attests to their profound potential, both as a tool for corporate transformation, and, more recently, as a means to enhance current, pedagogical practice. These notes explore coverage in the current literature regarding both concerns related to and the potential value of integrating AI technologies into the classroom to customize the learning experience through data-driven insights, to facilitate a more efficient allocation …

Comparison Of Transfer Learning And Conventional Machine Learning Applied To Structural Brain Mri For The Early Diagnosis And Prognosis Of Alzheimer's Disease, Loris Nanni, Matteo Interlenghi, Sheryl Brahnam, Christian Salvatore, Sergio Papa, Raffaello Nemni, Isabella Castiglioni

College of Business

Alzheimer's Disease (AD) is the most common neurodegenerative disease, with 10% prevalence in the elder population. Conventional Machine Learning (ML) was proven effective in supporting the diagnosis of AD, while very few studies investigated the performance of deep learning and transfer learning in this complex task. In this paper, we evaluated the potential of ensemble transfer-learning techniques, pretrained on generic images and then transferred to structural brain MRI, for the early diagnosis and prognosis of AD, with respect to a fusion of conventional-ML approaches based on Support Vector Machine directly applied to structural brain MRI. Specifically, more than 600 subjects …

Reforming U.S. Patent Law To Enable Access To Essential Medicines In The Era Of Artificial Intelligence, Elif Kavusturan

Northwestern Journal of Technology and Intellectual Property

The patent system has long been criticized for limiting access to pharmaceuticals. Patents grant inventors a limited period of exclusivity with an attempt to allow recoupment of investments in the invention process. In the pharmaceutical industry, this exclusivity and the resulting lack of competition leads to exorbitant prices. High prices limit access to potentially life-saving medicines and hinder achievement of the “highest attainable standard of health,” which several international instruments recognize as a human right.

The pharmaceutical industry claims patents are essential to encourage innovation in risky, lengthy and costly research and development (R&D) processes. But it has yet to …

Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker

Research Collection School Of Computing and Information Systems

Android as an operating system is now increasingly being adopted in industrial information systems, especially with Cyber-Physical Systems (CPS). This also puts Android devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by the increasing number of polymorphic and metamorphic malicous applications targeting the platform. The existence of such malware threats therefore call for more accurate identification and surveillance of sensitive Android app behaviors, which is essential to the security of CPS and IoT devices powered by Android. Nevertheless, achieving dynamic app behavior monitoring and identification on real CPS powered by Android …

A Bibliometric Survey On The Reliable Software Delivery Using Predictive Analysis, Jalaj Pachouly, Swati Ahirrao, Ketan Kotecha

Library Philosophy and Practice (e-journal)

Delivering a reliable software product is a fairly complex process, which involves proper coordination from the various teams in planning, execution, and testing for delivering software. Most of the development time and the software budget's cost is getting spent finding and fixing bugs. Rework and side effect costs are mostly not visible in the planned estimates, caused by inherent bugs in the modified code, which impact the software delivery timeline and increase the cost. Artificial intelligence advancements can predict the probable defects with classification based on the software code changes, helping the software development team make rational decisions. Optimizing the …

The Invisible Web At Work: Artificial Intelligence And Electronic Surveillance In The Workplace, Richard A. Bales, Katherine Vw Stone

AI-DR Collection

Employers and others who hire or engage workers to perform services use a dizzying array of electronic mechanisms to make personnel decisions about hiring, worker evaluation, compensation, discipline, and retention. These electronic mechanisms include electronic trackers, surveillance cameras, metabolism monitors, wearable biological measuring devices, and implantable technology. These tools enable employers to record their workers’ every movement, listen in on their conversations, measure minute aspects of performance, and detect oppositional organizing activities. The data collected is transformed by means of artificial intelligence (A-I) algorithms into a permanent electronic resume that can identify and predict an individual’s performance as well as …

Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong

Faculty and Staff Scholarship

To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …

Medical Civil Liability Without Deterrence: Preliminary Remarks For Future Research, Emiliano Marchisio

Journal of Civil Law Studies

The traditional deterrence-based paradigm of civil liability may be understood as indirect market regulation, as the risk of incurring liability for damages provides an incentive to invest in safety. Such an approach, however, has proven to be inappropriate in medical civil liability. Extensive literature shows that the increase in the asymmetric protection of patients by extending medical civil liability beyond a certain limit does not improve safety; instead, that strategy determines the adoption of “defensive” techniques (the so-called “defensive medicine”). Paradoxically, this approach leads to a reduction in market efficiency and overall patient safety. The traditional paradigm of medical civil …

Research On Geographical Battlefield Environment Model Facing Autonomous Platform, You Xiong, Jiangpeng Tian

Journal of System Simulation

Abstract: Battlefield environment model is an abstraction and description of the complex battlefield environment for specific needs. It supports the research and application of the nature and evolution of the battlefield environment. However, the existing battlefield environment model is mainly oriented to human war activities to describe the battlefield environment,and lacks the design for unmanned autonomous platforms. A multi-level battlefield environment model structure which couples the advantages of humans and machines is proposed, which can give full play to the machine's rapid numerical calculation capabilities at the geometric and feature levels, as well as human cognitive experience at the element, …

Automatic Traffic Monitoring And Management For Pedestrian And Cyclist Safety Using Deep Learning And Artificial Intelligence, Mohammad Pourhomayoun

Mineta Transportation Institute

In this project, we have designed and developed an effective end-to-end system based on advanced Artificial Intelligence (AI), machine learning, and computer vision to automatically monitor, detect, track, and count pedestrians and bicyclists. The main objective of this project is to improve the safety of pedestrians and bicyclists, by applying self-sensed and AI-powered systems to monitor and control the flow of pedestrians/bicyclists. The developed system includes algorithms for detecting the pedestrians and bicyclists, as well as algorithms for tracking and counting the pedestrians. We evaluated the developed system on real videos captured by actual traffic cameras in the city of …

An Ecosystem Approach To Ethical Ai And Data Use: Experimental Reflections, Mark Findlay, Josephine Seah

Research Collection Yong Pung How School Of Law

While we have witnessed a rapid growth of ethics documents meant to guide artificial intelligence (AI) development, the promotion of AI ethics has nonetheless proceeded with little input from AI practitioners themselves. Given the proliferation of AI for Social Good initiatives, this is an emerging gap that needs to be addressed in order to develop more meaningful ethical approaches to AI use and development. This paper offers a methodology-a 'shared fairness' approach-aimed at identifying AI practitioners' needs when it comes to confronting and resolving ethical challenges and to find a third space where their operational language can be married with …

Artificial Intelligence For Rapid Meta-Analysis: Case Study On Ocular Toxicity Of Hydroxychloroquine., Matthew Michelson, Tiffany Chow, Neil A Martin, Mike Ross, Amelia Tee Qiao Ying, Steven Minton

Articles, Abstracts, and Reports

BACKGROUND: Rapid access to evidence is crucial in times of an evolving clinical crisis. To that end, we propose a novel approach to answer clinical queries, termed rapid meta-analysis (RMA). Unlike traditional meta-analysis, RMA balances a quick time to production with reasonable data quality assurances, leveraging artificial intelligence (AI) to strike this balance.

OBJECTIVE: We aimed to evaluate whether RMA can generate meaningful clinical insights, but crucially, in a much faster processing time than traditional meta-analysis, using a relevant, real-world example.

METHODS: The development of our RMA approach was motivated by a currently relevant clinical question: is ocular toxicity and …

The Law Of Black Mirror - Syllabus, Yafit Lev-Aretz, Nizan Packin

Open Educational Resources

Using episodes from the show Black Mirror as a study tool - a show that features tales that explore techno-paranoia - the course analyzes legal and policy considerations of futuristic or hypothetical case studies. The case studies tap into the collective unease about the modern world and bring up a variety of fascinating key philosophical, legal, and economic-based questions.

Collaborative Economy, Tourist Accommodation And Their Impact In The Context Of Sustainable Urban Development: Is Artificial Intelligence A Possible Answer?, Juli Ponce

Journal of Comparative Urban Law and Policy

No abstract provided.

Artificial Intelligence Create Value To Investors, Jing-Yang Huang

Marriott Student Review

Artificial intelligence provides personalized assistance and solves tedious tasks in our daily lives. One of the applications of this technology is about investing. This article summarizes some basic knowledge of artificial intelligence and how it assists investors to create value.

Application Of Artificial Intelligence And Geographic Information System For Developing Automated Walkability Score, Md Mehedi Hasan

Dissertations

Walking is considered as one of the major modes of active transportation, which contributes to the livability of cities. It is highly important to ensure walk friendly sidewalks to promote human physical activities along roads. Over the last two decades, different walk scores were estimated in respect to walkability measures by applying different methods and approaches. However, in the era of big data and machine learning revolution, there is still a gap to measure the composite walkability score in an automated way by applying and quantifying the activityfriendliness of walkable streets. In this study, a street-level automated walkability score was …

Predictive Insights For Improving The Resilience Of Global Food Security Using Artificial Intelligence, Meng Leong How, Yong Jiet Chan, Sin Mei Cheah

Research Collection Lee Kong Chian School Of Business

Unabated pressures on food systems affect food security on a global scale. A human-centric artificial intelligence-based probabilistic approach is used in this paper to perform a unified analysis of data from the Global Food Security Index (GFSI). The significance of this intuitive probabilistic reasoning approach for predictive forecasting lies in its simplicity and user-friendliness to people who may not be trained in classical computer science or in software programming. In this approach, predictive modeling using a counterfactual probabilistic reasoning analysis of the GFSI dataset can be utilized to reveal the interplay and tensions between the variables that underlie food affordability, …

Application Of Machine Learning Technologies For Detection Of Proximal Lesions In Intraoral Digital Images: In Vitro Study., Rohit Vadlamani

Electronic Theses and Dissertations

Background: Interpretation of bitewing radiographs is influenced by factors such as acquisition parameters (e.g. exposure, type of sensor), clinical technique, visualization (e.g. monitor type and calibration) and the observer (e.g. experience and fatigue bias). We hypothesized that the use of artificial intelligence (AI) will reduce visualization and observer factor in bitewing interpretation and improve diagnostic accuracy. Objective: The purpose of the present study was to evaluate the use of AI in the form of a machine-learning algorithm to detect and quantify proximal lesions compared with human trained observers. Methods: 16,000 anonymized, digital bitewings of patients were hand searched and non-bitewing, …