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

A derivatives trading recommendation system: The mid‐curve calendar spread case

Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work is aimed to develop a trading recommendation system, and to apply this system to the so‐called Mid‐Curve Calendar Spread (MCCS) trade. To suggest that such approach is feasible, we used a list of 35 different types of MCCSs; a total of 11 predictive and 4 benchmark models. Our results suggest that linear regression with l1‐regularisation (Lasso) compared favourably to other approaches from a predictive and interpretability point of views

Automatic synthesis of fuzzy systems: An evolutionary overview with a genetic programming perspective

Studies in Evolutionary Fuzzy Systems (EFSs) began in the 90s and have experienced a fast development since then, with applications to areas such as pattern recognition, curve‐fitting and regression, forecasting and control. An EFS results from the combination of a Fuzzy Inference System (FIS) with an Evolutionary Algorithm (EA). This relationship can be established for multiple purposes: fine‐tuning of FIS's parameters, selection of fuzzy rules, learning a rule base or membership functions from scratch, and so forth. Each facet of this relationship creates a strand in the literature, as membership function fine‐tuning, fuzzy rule‐based learning, and so forth and the purpose here is to outline some of what has been done in each aspect. Special focus is given to Genetic Programming‐based EFSs by providing a taxonomy of the main architectures available, as well as by pointing out the gaps that still prevail in the literature. The concluding remarks address some further topics of current research and trends, such as interpretability analysis, multiobjective optimization, and synthesis of a FIS through Evolving methods

Floral Diversity in Different Types of Honey

Many different types of honey are available in the Brazilian market. They vary in color, flavor, smell, thereby increasing interest in honey characterization relating to botanical origin. A total of 155 honey samples belonging to Brazilian flora were examined on the pollen analysis; sampling is made in a span of one year. The preparation followed melisso palynological analysis based on the specific botanical variety. The pollen spectra revealed 60 pollen types belonging to 27 plant families and Myrtaceae, Fabaceae and Asteraceae were the dominant plant families. Few pollen types were found in most samples of honey. The families that showed major richness of pollen types were Fabaceae and Asteraceae. Only six floral sources of pollen plants and three floral sources of nectar plants appeared in the category of predominant pollen. The unifloral honeys were slightly more frequent than polyfloral, and wild floral species dominated most of the honey samples. These floral sources, even in minor parts in the honeys samples, are also part of the biological feature of theses honeys. The honeys from natural fields cannot be completely accounted by the term unifloral honeys

Unimodal optimization using a genetic-programming-based method with periodic boundary conditions

This article describes a new genetic-programming-based optimization method using a multi-gene approach along with a niching strategy and periodic domain constraints. The method is referred to as Niching MG-PMA, where MG refers to multi-gene and PMA to parameter mapping approach. Although it was designed to be a multimodal optimization method, recent tests have revealed its suitability for unimodal optimization. The definition of Niching MG-PMA is provided in a detailed fashion, along with an in-depth explanation of two novelties in our implementation: the feedback of initial parameters and the domain constraints using periodic boundary conditions. These ideas can be potentially useful for other optimization techniques. The method is tested on the basis of the CEC’2015 benchmark functions. Statistical analysis shows that Niching MG-PMA performs similarly to the winners of the competition even without any parametrization towards the benchmark, indicating that the method is robust and applicable to a wide range of problems

The Interleukin-6 inflammation pathway from cholesterol to aging – Role of statins, bisphosphonates and plant polyphenols in aging and age-related diseases

We describe the inflammation pathway from Cholesterol to Aging. Interleukin 6 mediated inflammation is implicated in age-related disorders including Atherosclerosis, Peripheral Vascular Disease, Coronary Artery Disease, Osteoporosis, Type 2 Diabetes, Dementia and Alzheimer's disease and some forms of Arthritis and Cancer. Statins and Bisphosphonates inhibit Interleukin 6 mediated inflammation indirectly through regulation of endogenous cholesterol synthesis and isoprenoid depletion. Polyphenolic compounds found in plants, fruits and vegetables inhibit Interleukin 6 mediated inflammation by direct inhibition of the signal transduction pathway. Therapeutic targets for the control of all the above diseases should include inhibition of Interleukin-6 mediated inflammation