THE COST OF THE KYOTO PROTOCOL TO U.S. CROP PRODUCTION: MEASURING CROP PRICE, REGIONAL ACREAGE, WELFARE, AND INPUT SUBSTITUTION EFFECTS

This study analyzes the impact of implementing carbon permit trading considered under the Kyoto Protocol, and the subsequent expected increase in energy and resource prices on U.S. crop production. The focus is on input substitution, net farm income, regional crop acreage, and crop prices. The analysis is carried out with a calibrated mathematical programming model which covers the major crops produced in the 48 contiguous states on a regional basis. The model accounts for both the variable inputs and the allocatable inputs of land and irrigation water, and it permits input substitution when farmers are faced with external shocks. The results suggest that when energy prices increase, the net cost to the crop-producing sector depends on the farmerÂ’'s ability to substitute crop inputs and the elasticity of demand for the crops. The impacts of carbon tax cost increases differ significantly among crops and regions. Overall, crop acreage and output decrease, total net revenues increase in most regions, and consumer surplus declines.Environmental Economics and Policy,

Philosophical foundations for digital ethics and AI Ethics: a dignitarian approach

AI Ethics is a burgeoning and relatively new field that has emerged in response to growing concerns about the impact of artificial intelligence (AI) on human individuals and their social institutions. In turn, AI ethics is a part of the broader field of digital ethics, which addresses similar concerns generated by the development and deployment of new digital technologies. Here, we tackle the important worry that digital ethics in general, and AI ethics in particular, lack adequate philosophical foundations. In direct response to that worry, we formulate and rationally justify some basic concepts and principles for digital ethics/AI ethics, all drawn from a broadly Kantian theory of human dignity. Our argument, which is designed to be relatively compact and easily accessible, is presented in ten distinct steps: (1) what "digital ethics" and "AI ethics" mean, (2) refuting the dignity-skeptic, (3) the metaphysics of human dignity, (4) human happiness or flourishing, true human needs, and human dignity, (5) our moral obligations with respect to all human real persons, (6) what a natural automaton or natural machine is, (7) why human real persons are not natural automata/natural machines: because consciousness is a form of life, (8) our moral obligations with respect to the design and use of artificial automata or artificial machines, aka computers, and digital technology more generally, (9) what privacy is, why invasions of digital privacy are morally impermissible, whereas consensual entrances into digital privacy are either morally permissible or even obligatory, and finally (10) dignitarian morality versus legality, and digital ethics/AI ethics. We conclude by asserting our strongly-held belief that a well-founded and generally-accepted dignitarian digital ethics/AI ethics is of global existential importance for humanity

Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

In the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers' workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd's research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd

A high-level overview of AI ethics

Artificial intelligence (AI) ethics is a field that has emerged as a response to the growing concern regarding the impact of AI. It can be read as a nascent field and as a subset of the wider field of digital ethics, which addresses concerns raised by the development and deployment of new digital technologies, such as AI, big data analytics, and blockchain technologies. The principle aim of this article is to provide a high-level conceptual discussion of the field by way of introducing basic concepts and sketching approaches and central themes in AI ethics. The first part introduces concepts by noting what is being referred to by “AI” and “ethics”, etc.; the second part explores some predecessors to AI ethics, namely engineering ethics, philosophy of technology, and science and technology studies; the third part discusses three current approaches to AI ethics namely, principles, processes, and ethical consciousness; and finally, the fourth part discusses central themes in translating ethics in to engineering practice. We conclude by summarizing and noting the inherent interdisciplinary future directions and debates in AI ethics

The interrelation between data and AI ethics in the context of impact assessments

In the growing literature on artificial intelligence (AI) impact assessments, the literature on data protection impact assessments is heavily referenced. Given the relative maturity of the data protection debate and that it has translated into legal codification, it is indeed a natural place to start for AI. In this article, we anticipate directions in what we believe will become a dominant and impactful forthcoming debate, namely, how to conceptualise the relationship between data protection and AI impact. We begin by discussing the value canvas i.e. the ethical principles that underpin data and AI ethics, and discuss how these are instantiated in the context of value trade-offs when the ethics are applied. Following this, we map three kinds of relationships that can be envisioned between data and AI ethics, and then close with a discussion of asymmetry in value trade-offs when privacy and fairness are concerned

Do It Right The First Time - A Review Of An Ethylene Plant Turbomachinery Commissioning Test.

LecturePg. 113-122Every user would like to check the mechanical integrity of rotating equipment in the field before startup. In the case of large compressor trains with steam turbine drives, running a mechanical string test with associated piping and auxiliaries provides positive check outs for compressor, driver, and all auxiliary equipment. The benefits of planning, preparation, and execution of such a program are described

Algorithm Auditing: Managing the Legal, Ethical, and Technological Risks of Artificial Intelligence, Machine Learning, and Associated Algorithms

Algorithms are becoming ubiquitous. However, companies are increasingly alarmed about their algorithms causing major financial or reputational damage. A new industry is envisaged: auditing and assurance of algorithms with the remit to validate artificial intelligence, machine learning, and associated algorithms

Phacoemulsification compared with phacotrabeculectomy surgery: a within-person observational cohort study.

AIM: To compare reduction in intraocular pressure (IOP) and gain in visual acuity (VA) following phacotrabeculectomy (PT) and phacoemulsification(phaco) in Tanzanian patients with primary open angle glaucoma(POAG). SETTING: CCBRT Hospital, Dar es Salaam, Tanzania. DESIGN: Within-person observational cohort study. METHODS: Within each patient, one eye had PT and the other phaco. Patients were followed for up to 5-1/2 years, and IOP and VA in each eye were assessed. For a small group of patients, two additional postoperative time points were compared. RESULTS: 52 patients (34 male) with a mean age of 70 years (SD 8 years) were enrolled in the study. For those with 250 days or more follow-up, both operations resulted in lower IOPs and improved VA (p<0.001). The average drop in IOP was 50% (95%CI 45% to 55%) for PT and 41% (95% CI 36% to 46%) for phaco. Mean IOP was lower in the PT group 12.9 mm Hg vs 16.8 mm Hg (p=0.004). Extended follow-up in nine patients showed a rise in IOP of 1.8 mm Hg for PT and 4.2 mm Hg for phaco eyes between first (mean, 337 days) and second (mean 1482 days) follow-up (p=0.18). CONCLUSION: In this small study in African patients, PT resulted in lower IOPs than phacoemulsification alone but the difference between the procedures was relatively small. Phacoemulsification alone was effective in reducing IOP and improving VA for several years in this population. Given the relative simplicity of phacoemulsification, it is a therapeutic option worthy of consideration in some settings

The interplay between subsidiary internal embeddedness and strategic options: evidence from top information technology multinational enterprises

Extending subsidiary embeddedness and strategy literature, we conceptualise the role of subsidiary ‘multiple’ internal embeddedness in determining different subsidiary strategic options. Building on the notion of ‘structural’ embeddedness found in prior research, we distinguish three levels of ‘internal’ subsidiary embeddedness (corporate, network, and self-reliant) using measures of hierarchy. We also identify three types of subsidiary strategy (horizontal integration, lateral integration, and diversification) in the context of information technology (IT) Multinational Enterprises (MNEs) to examine in-depth whether and how levels of internal embeddedness interacts and leads to distinctively different subsidiary strategies. Subsequently, we offer a conceptual model, at the subsidiary level, to illustrate how these relationships are interplayed, based on a sample of 1866 subsidiaries of the eight largest global IT MNEs across four continents (Europe, North America, Asia, and Africa). Subsidiary location is also found to be an important moderator of the interplay. Implications for future research on the relationship between multiple subsidiary internal embeddedness and subsidiary strategies are discussed and managerial implications are outlined

Scoring a forced-choice image-based assessment of personality: A comparison of machine learning, regression, and summative approaches

Recent years have seen rapid advancements in the way that personality is measured, resulting in a number of innovative predictive measures being proposed, including using features extracted from videos and social media profiles. In the context of selection, game- and image-based assessments of personality are emerging, which can overcome issues like social desirability bias, lack of engagement and low response rates that are associated with traditional self-report measures. Forced-choice formats, where respondents are asked to rank responses, can also mitigate issues such as acquiescence and social desirability bias. Previously, we reported on the development of a gamified forced-choice image-based assessment of the Big Five personality traits created for use in selection, using Lasso regression for the scoring algorithms. In this study, we compare the machine-learning-based Lasso approach to ordinary least squares regression, as well as the summative approach that is typical of forced-choice formats. We find that the Lasso approach performs best in terms of generalisability and convergent validity, although the other methods have greater discriminate validity. We recommend the use of predictive Lasso regression models for scoring forced-choice image-based measures of personality over the other approaches. Potential further studies are suggested