Rapidly developing artificial intelligence technologies are expected to help us in various sectors of life, but their applications also entail certain risks.

The paper depicts some negative consequences of the attempts of history comprehension. In the light of the settlements of the contemporary psychology such attempts lead to the biases in historical cognition results.

In this article, authors analyze methods of the analysis of data integrity, security and availability loss results for business processes. Assessing those results, one can judge the importance of a process in organization; thus, determine which business process requires more attention. The importance of those processes can be determined with Business Impact Analysis (BIA). In article, first phase of BIA is presented – in specific, a construction of Business Impact Category Tables, Loss Levels and process weight calculation methods. A variety of weight calculating methods is presented. Authors also present their proposed method – square sum percentage – as a solution eliminating problems of other weight calculation methods in business impact analysis.

The paper depicts the relations between historian person and history cognition, especially the influence of his mind inclinations to cognitive biases on narrative.

Low-cost Micro-Electromechanical System (MEMS) gyroscopes are known to have a smaller size, lower weight, and less power consumption than their more technologically advanced counterparts. However, current low-grade MEMS gyroscopes have poor performance and cannot compete with quality sensors in high accuracy navigational and guidance applications. The main focus of this paper is to investigate performance improvements by fusing multiple homogeneous MEMS gyroscopes. These gyros are transformed into a virtual gyro using a feedback weighted fusion algorithm with dynamic sensor bias correction. The gyroscope array combines eight homogeneous gyroscope units on each axis and divides them into two layers of differential configuration. The algorithm uses the gyroscope array estimation value to remove the gyroscope bias and then correct the gyroscope array measurement value. Then the gyroscope variance is recalculated in real time according to the revised measurement value and the weighted coefficients and state estimation of each gyroscope are deduced according to the least square principle. The simulations and experiments showed that the proposed algorithm could further reduce the drift and improve the overall accuracy beyond the performance limitations of individual gyroscopes. The maximum cumulative angle error was - 2:09 degrees after 2000 seconds in the static test, and the standard deviation (STD) of the output fusion value of the proposed algorithm was 0.006 degrees/s in the dynamic test, which was only 1.7% of the STD value of an individual gyroscope.

The Theory of Bounded Ethicality postulates that in situations involving consequences for self and/or others people make ethical decisions that bring self- -oriented motivational forces to bear on decision-making. These ethical decisions are biased by a stubborn view of oneself, as moral, competent, and deserving and thus, not susceptible to conflicts of interest. People unconsciously favor this particular vision of the self being unaware of data that may contradict it. This conception of ethical decision making seems to imply that self-oriented motivation plays a dominant role in regulation of human behavior. But there are good theoretical reasons for questioning this view. In the paper, I describe three different research programs that may illustrate operation of the three different motivational systems – only one of them seems to corresponds with the Bounded Ethicality model. It means that that “bounded ethicality“ may appear in pure form in specific situations – when self system is activated by specific egxogenous and endogenous factors while other systems are not remain in the latent state.

The impact of complexity within government and societal systems is considered relative to the limitations of human cognitive bandwidth, and the resulting reliance on cognitive biases and systems of automation when that bandwidth is exceeded. Examples of how humans and societies have attempted to cope with the growing difference between the rate at which the complexity of systems and human cognitive capacities increase respectively are considered. The potential of and urgent need for systems capable of handling the existing and future complexity of systems, utilizing greater cognitive bandwidth through scalable AGI, are also considered, along with the practical limitations and considerations in how those systems may be deployed in real-world conditions. Several paradoxes resulting from the influence of prolific Narrow Tool AI systems manipulating large portions of the population are also noted