What if: robots create novel goals? Ethics based on social value systems

Future personal robots might possess the capability to autonomously generate novel goals that exceed their initial programming as well as their past experience. We discuss the ethical challenges involved in such a scenario, ranging from the construction of ethics into such machines to the standard of ethics we could actually demand from such machines. We argue that we might have to accept those machines committing human-like ethical failures if they should ever reach human-level autonomy and intentionality. We base our discussion on recent ideas that novel goals could be originated from agents’ value system that express a subjective goodness of world or internal states. Novel goals could then be generated by extrapolating what future states would be good to achieve. Ethics could be built into such systems not just by simple utilitarian measures but also by constructing a value for the expected social acceptance of a the agent’s conduct

From social interaction to ethical AI: a developmental roadmap

AI and robot ethics have recently gained a lot of attention because adaptive machines are increasingly involved in ethically sensitive scenarios and cause incidents of public outcry. Much of the debate has been focused on achieving highest moral standards in handling ethical dilemmas on which not even humans can agree, which indicates that the wrong questions are being asked. We suggest to address this ethics debate strictly through the lens of what behavior seems socially acceptable, rather than idealistically ethical. Learning such behavior puts the debate into the very heart of developmental robotics. This paper poses a roadmap of computational and experimental questions to address the development of socially acceptable machines. We emphasize the need for social reward mechanisms and learning architectures that integrate these while reaching beyond limitations of plain reinforcement learning agents. We suggest to use the metaphor of “needs” to bridge rewards and higher level abstractions such as goals for both communication and action generation in a social context. We then suggest a series of experimental questions and possible platforms and paradigms to guide future research in the area

Impacts of stratospheric sulfate geoengineering on global solar photovoltaic and concentrating solar power resource

In recent years, the idea of geoengineering, artificially modifying the climate to reduce global temperatures, has received increasing attention due to the lack of progress in reducing global greenhouse gas emissions. Stratospheric sulfate injection (SSI) is a geoengineering method proposed to reduce planetary warming by reflecting a proportion of solar radiation back into space that would otherwise warm the surface and lower atmosphere. We analyze results from the HadGEM2-CCS climate model with stratospheric emissions of 10 Tg yr-1 of SO2, designed to offset global temperature rise by around 1°C. A reduction in concentrating solar power (CSP) output of 5.9% on average over land is shown under SSI compared to a baseline future climate change scenario (RCP4.5) due to a decrease in direct radiation. Solar photovoltaic (PV) energy is generally less affected as it can use diffuse radiation, which increases under SSI, at the expense of direct radiation. Our results from HadGEM2-CCS are compared to the GEOSCCM chemistry-climate model from the Geoengineering Model Intercomparison Project (GeoMIP), with 5 Tg yr-1 emission of SO2. In many regions, the differences predicted in solar energy output between the SSI and RCP4.5 simulations are robust, as the sign of the changes for both the HadGEM2-CCS and GEOSCCM models agree. Furthermore, the sign of the total and direct annual mean radiation changes evaluated by HadGEM2-CCS agree with the sign of the multi-model mean changes of an ensemble of GeoMIP models over the majority of the world

Natural head movement for HRI with a muscular-skeletal head and neck robot

This paper presents a study of the movements of a humanoid head-and-neck robot called Eddie. Eddie has a musculo-skeletal structure similar to that found in human necks enabling it to perform head movements that are comparable with human head movements. This study compares the movements of Eddie with those of a more conventional robotic neck structure and with those of a human head. Results show that Eddie’s movements are perceived as significantly more natural and by trend more lifelike than the conventional head’s. No differences were found with respect to the impression of humanlikeness, consciousness, and elegance

Evidence of plasmonic effects in random orientation silver nanowire meshes on silicon

In this work silver nanowires were used as the transparent conductive electrode on a crystalline silicon solar cell in place of the commonly used screen printed grid. Light transmission and surface characterisation of the cells displays an average of 22% more light transmission than the physical non-AgNW shaded area of the cell surface. Further to this it is observed that plasmonic effects result in an increased scattering of incoming light into the cell, which also reduced the amount of light reflected from the cell’s front plane. The cells with silver nanowire electrodes did not, however, show improved current–voltage characteristics compared to cells without a front electrode. This is attributed to the overall low light transmission as a result of silver nanoparticles present in the electrodes and poor electrical connection between silicon cell and electrode. Finally, a large reduction in the mass of silver used for the nanowire electrodes was observed when compared to standard screen printed grid fingers

An all-sky radiative transfer method to predict optimal tilt and azimuth angle of a solar collector

This paper describes a radiative transfer method for calculating radiances in all-sky conditions and performing an integration over the view hemisphere of an arbitrary plane to calculate tilted irradiance. The advantage of this method is the combination of cloud parameters inside the radiative transfer model with a tilt procedure. For selected locations this method is applied with cloud, ozone, water vapour and aerosol input data to determine tilted irradiance, horizontal irradiance and optimal tilt angle. A validation is performed for horizontal and tilted irradiance against high-quality pyranometer data. For 27 sites around the world, the annual horizontal irradiation predicted by our model had a mean bias difference of +0.56% and a root-mean-squared difference of 6.69% compared to ground measurements. The difference between the annual irradiation estimates from our model and the measurements from one site that provides tilted irradiance were within ±6% for all orientations except the north-facing vertical plane. For European and African sites included in the validation, the optimal tilt from our model is typically a few degrees steeper than predictions from the popular PVGIS online tool. Our model is generally applicable to any location on the earth’s surface as the satellite cloud and atmosphere data and aerosol climatology data are available globally. Furthermore, all of the input data are standard variables in climate models and so this method can be used to predict tilted irradiance in future climate experiments

Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations

The statistics of clear-sky index can be used to determine solar irradiance when the theoretical clear sky irradiance and the cloud cover are known. In this paper, observations of hourly clear-sky index for the years of 2010--2013 at 63 locations in the UK are analysed for over 1 million data hours. The aggregated distribution of clear-sky index is bimodal, with strong contributions from mostly-cloudy and mostly-clear hours, as well as a lower number of intermediate hours. The clear-sky index exhibits a distribution of values for each cloud cover bin, measured in eighths of the sky covered (oktas), and also depends on solar elevation angle. Cloud cover is measured either by a human observer or automatically with a cloud ceilometer. Irradiation (time-integrated irradiance) values corresponding to human observations of "cloudless" skies (0 oktas) tend to agree better with theoretical clear-sky values, which are calculated with a radiative transfer model, than irradiation values corresponding to automated observations of 0 oktas. It is apparent that the cloud ceilometers incorrectly categorise more non-cloudless hours as cloudless than human observers do. This leads to notable differences in the distributions of clear-sky index for each okta class, and between human and automated observations. Two probability density functions---the Burr (type III) for mostly-clear situations, and generalised gamma for mostly-cloudy situations---are suggested as analytical fits for each cloud coverage, observation type, and solar elevation angle bin. For human observations of overcast skies (8 oktas) where solar elevation angle exceeds 10°, there is no significant difference between the observed clear-sky indices and the generalised gamma distribution fits

A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration

Residential photovoltaic (PV) technology is expected to have mass global deployment. With widespread PV in the electricity distribution grids, the variable nature of the solar resource must be understood to facilitate reliable operation. This research demonstrates that synthetic, 1-min resolution irradiance time series that vary on a spatial dimension can be generated based on the following inputs: mean hourly meteorological observations of okta, wind speed, cloud height and atmospheric pressure. The synthetic time series temporally validate against observed 1-min irradiance data for four locations—Cambourne, UK; Lerwick, UK; San Diego, CA USA; and Oahu, HI USA—when analysing 4 metrics of variability indices, ramp-rate size, irradiance magnitude frequency and clear-sky index frequency. Each metric is calculated for the modelled and observed data at each location and CDF profile correlation compared as well as applying the Kolmogorov-Smirnov (K–S) test with 99% confidence limits. CDF correlation coefficients of each metric are all above R⩾0.908, and a minimum of 90.96% of daily irradiance time series passed the K–S test. A spatial validation was performed comparing the model outputs to real observation data. The spatial correlation coefficient regression with site separation was successfully recreated with MAPE = 0.865%, RMSE = 0.01 and R=0.955. The spatial instantaneous correlation was shown to behave anisotropically when using fixed cloud direction, with different correlation in along and cross wind directions. Cloud cover states of 40–60% showed the most spatial decorrelation while 0% and 100% had the least. The model outputs are applied to a distribution grid impact model using the IEEE-8500 node test feeder. PV scenarios of 25%,50%, and 75% uptake were modelled across a 1.5×1.5 km grid. The magnitude and frequency of severe tap changing events are found to be significantly higher when using a single irradiance time series for all PV systems versus individually assigning spatially decorrelating time series

Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)

An assessment of roof-mounted PV capacity over a local region can be accurately calculated by established roof segmentation algorithms using high-resolution light detection and ranging (LiDAR) datasets. However, over larger city regions often only low-resolution LiDAR data is available where such algorithms prove unreliable for small rooftops. A methodology optimised for low-resolution LiDAR datasets is presented, where small and large buildings are considered separately. The roof segmentation algorithm for small buildings, which are typically residential properties, assigns a roof profile to each building from a catalogue of common profiles after identifying LiDAR points within the building footprint. Large buildings, such as warehouses, offer a more diverse range of roof profiles but geometric features are generally large, so a direct approach is taken to segmentation where each LiDAR point within the building footprint contributes a separate roof segment. The methodology is demonstrated by application to the city region of Leeds, UK. Validation by comparison to aerial photography indicates that the assignment of an appropriate roof profile to a small building is correct in 81% of cases