A democratic way of controlling artificial general intelligence

The problem of controlling an artificial general intelligence (AGI) has fascinated both scientists and science-fiction writers for centuries. Today that problem is becoming more important because the time when we may have a superhuman intelligence among us is within the foreseeable future. Current average estimates place that moment to before 2060. Some estimates place it as early as 2040, which is quite soon. The arrival of the first AGI might lead to a series of events that we have not seen before: rapid development of an even more powerful AGI developed by the AGIs themselves. This has wide-ranging implications to the society and therefore it is something that must be studied well before it happens. In this paper we will discuss the problem of limiting the risks posed by the advent of AGIs. In a thought experiment, we propose an AGI which has enough human-like properties to act in a democratic society, while still retaining its essential artificial general intelligence properties. We discuss ways of arranging the co-existence of humans and such AGIs using a democratic system of coordination and coexistence. If considered a success, such a system could be used to manage a society consisting of both AGIs and humans. The democratic system where each member of the society is represented in the highest level of decision-making guarantees that even minorities would be able to have their voices heard. The unpredictability of the AGI era makes it necessary to consider the possibility that a population of autonomous AGIs could make us humans into a minority

Alihankkijoiden arviointi kuljetusyrityksessä analyyttisen hierarkiaprosessin avulla

Siirretty Doriast

Contributions to measurement-based dynamic MIMO channel modeling and propagation parameter estimation

Multiantenna (MIMO) transceivers are a key technology in emerging broadband wireless communication systems since they facilitate achieving the required high data rates and reliability. In order to develop and study the performance of MIMO systems, advanced channel modeling that captures also the spatial characteristics of the radio wave propagation is required. This thesis introduces several contributions in the area of measurement-based modeling of wireless MIMO propagation channels. Measurement based modeling provides realistic characterization of the space, time and frequency dependency of the physical layer for both MIMO transceiver design and network planning. The focus in this thesis is on modeling and parametric estimation of mobile MIMO radio propagation channels. First, an overview of MIMO channel modeling approaches is given. A hybrid model for characterizing the spatio-temporal structure of measured MIMO channels consisting of a superposition of double-directional, specular-like propagation paths, and a stochastic process describing the diffuse scattering is formulated. State-space modeling approach is introduced in order to capture the dynamic channel properties from mobile channel sounding measurements. Extended Kalman filter (EKF) is employed for the sequential estimation problem and also statistical hypothesis testing for adjusting the model order are introduced. Due to the improved dynamic model of the mobile radio channel, the EKF approach outperforms maximum likelihood (ML) based batch solutions both in terms of lower estimation error as well as computational complexity. Finally, tensor representation for modeling multidimensional MIMO channels is considered and a novel sequential unfolding SVD (SUSVD) tensor decomposition is introduced. The SUSVD is an orthogonal tensor decomposition having several important applications in signal processing. The advantages of applying the SUSVD instead of other well known tensor models such as parallel factorization and Tucker-models, are illustrated using application examples in channel sounding data processing

Risk of adult-onset asthma increases with the number of allergic multimorbidities and decreases with age

Background The aim was to study the association between allergic multimorbidity and adult-onset asthma considering the number of allergic diseases and the age effect. Methods We used population-based data from Finnish national registers including 1205 adults over 30 years of age with recently diagnosed asthma (age range: 30-93), matched for gender, age, and living region with one or two controls (n = 2050). Allergic rhinitis (AR), allergic conjunctivitis (AC), and allergic dermatitis (AD) were defined from self-completed questionnaire. Conditional logistic regression adjusted on potential confounders (smoking, growing in countryside, childhood hospitalized infection/pneumonia, parental asthma/allergy, parental smoking, education level, professional training, number of siblings, and birth order) was applied to estimate the asthma risk associated with allergic multimorbidity. Results A total of 1118 cases with asthma and 1772 matched controls were included [mean (SD, min-max) 53 (11, 31-71) years, 37% men)]. AR, AC, and AD were reported by 50.2%, 39.6%, and 33.8%, respectively, among subjects with asthma and 26.1%, 20.0%, and 23.5%, respectively, among controls. Compared to nonatopics, adult-onset asthma increased with the number of allergic diseases; adjusted OR for asthma [95% CI] associated with 1, 2, and 3 allergic diseases was 1.95 [1.52-2.49], 2.87 [2.19-3.77], and 4.26 [3.07-5.90], respectively. The association between adult-onset asthma and >= 1 allergic multimorbidity decreased with increasing age (3.52 [2.51-4.94], 2.44 [1.74-3.42], and 1.68 [1.04-2.71]) in subjects 62 years, respectively (p for age*>= 1 allergic multimorbidity interaction, 0.002). Conclusions Adult-onset asthma was positively associated with the number of allergic diseases, and this association decreases with age.Peer reviewe