We discuss the properties of controllability and complexity in novel object enrichment, their definition and present a critique of previous work related to them. We address the relationship between control and complexity, the evolutionary basis of their attractiveness and suggest that the acquisition of control may be a more enriching process than its execution. We propose that, although little work has been directed at separating their relative contributions to enrichment, controllability appears more important than complexity. We discuss the ways in which objects can be responsive both in terms of the predictability of the response and the ‘grade’ of actor-object interaction.

This paper investigates the responses of European moles (Talpa europaea) to mechanical mole scarers. The three devices tested emitted vibrations in the frequency range 0 to 20kHz. Vibrations of this frequency are rapidly attenuated when passing through soil. Moles fitted with radio transmitters gave no indication of being repelled by the mechanical devices.

As part of a study into the effects of human activities on the welfare of free-living wildlife, the relative scale and severity of welfare problems in wild mammals and birds in Europe were investigated. Major cases were described and compared in terms of the nature and level of harm (pain, stress and fear) they cause, the duration of these effects and the number of individuals affected. The use of anticoagulant rodenticides, myxomatosis in rabbits, the poisoning of wildfowl by ingested lead shot, the contamination of seabirds with fuel oil, the effects of shooting, injuries due to collisions with road traffic and prédation by domestic cats all severely compromise the welfare of large numbers of animals. Practical approaches to the alleviation and prevention of some of these welfare problems are discussed. We suggest that in assessing the environmental impact of new developments and technologies prior to their implementation, possible consequences to wildlife welfare should always be considered.

The development of exoskeletons is currently a lengthy process full of challenges. We are proposing a framework to accelerate the process and make the resulting exoskeletons more user-centered. The needed accomplishments in science are described in an effort to lay the foundation for future research projects. Since the early 2000s, exoskeletons have been discussed as an emerging technology in industrial, medical, or military applications. Those systems are designed to support people during manual tasks. At first, those systems lacked broad acceptance. Many models found their niches in ongoing developments and more diverse systems entering the market. There are still applications that are in dire need of such assistance. Due to the lack of experience with body-worn robotics, the development of such systems has been shaped by trial and error. The lack of legacy products results in longer development times. In this paper, a process to generate a framework is presented to display the required research to enable future exoskeleton designers. Owing to their proximity to the user’s body, exoskeletons are highly complex systems that need sophisticated subsystems, such as kinematic, control, interaction design, or actuators, to be accepted by users. Due to the wide variety of fields and high user demands, a synchronized multidisciplinary effort is necessary. To achieve this, a process to develop a modular framework for exoskeleton design is proposed. It focuses on user- and use-case-centered solutions for matching kinematics, actuation, and control. To ensure the usefulness of the framework, an evaluation of the incorporated solutions is required.

We claim that understanding human decisions requires that both automatic and deliberate processes be considered. First, we sketch the qualitative differences between two hypothetical processing systems, an automatic and a deliberate system. Second, we show the potential that connectionism offers for modeling processes of decision making and discuss some empirical evidence. Specifically, we posit that the integration of information and the application of a selection rule are governed by the automatic system. The deliberate system is assumed to be responsible for information search, inferences and the modification of the network that the automatic processes act on. Third, we critically evaluate the multiple-strategy approach to decision making. We introduce the basic assumption of an integrative approach stating that individuals apply an all-purpose rule for decisions but use different strategies for information search. Fourth, we develop a connectionist framework that explains the interaction between automatic and deliberate processes and is able to account for choices both at the option and at the strategy level.

This article provides a brief introduction to a research program which has been under way since 2007 to examine, using data from a large-sample panel survey, whether jobs in Australia are becoming more or less skilful over time. It redefines the debate on deskilling which ran through the 1970s and 1980s by expanding the focus beyond simple job quality to issues of current policy interest, notably the contribution of skill to innovation and productivity. To map this kind of dynamism it is necessary to use a metric capable of capturing change over short periods. This is achieved by adding a third dimension, skill-intensity, to Spenner’s classic definition of skill in terms of two loosely related constructs, worker autonomy/control and substantive job complexity. Data drawn from the first eight waves of HILDA are analysed to demonstrate that this metric is capable of capturing statistically significant change in the average skill content of jobs over much shorter periods than was possible with the metrics used in earlier decades. The broadly parallel aggregate trendlines for skill-intensity and autonomy/control suggest that these two dimensions are linked in the way Spenner suggests, even though major discrepancies appear between them in some industries and occupations.

The ultimate aim of this paper is to study and discuss a central dilemma within inspection of animal welfare. On the one hand, it may be argued that controllers should check only whether farmers comply or not with animal welfare regulation. Here, the key value is the rule of law, and that all offenders should be treated equally. On the other hand, it may be argued that an important component of inspections is to enter into dialogue with farmers. This may be based on a more forward-looking view aimed at motivating farmers to look after the welfare of the animals in their care. In European countries, authorities try to enforce animal welfare legislation through inspections followed up by penalties in instances where a lack of compliance is found. However, the fairness and efficiency, and ultimately the public acceptance of the system, critically depend on the performance of the individual inspector. This paper presents the results of an interview-study into how Danish animal welfare inspectors view their own role and tasks. In the main results, a theme of disagreement presented itself and revealed different attitudes in terms of the possibility of engaging in a dialogue with the farmers. The first theme focused on the preventive aspect. The second had its focus on compliance and on the avoidance of engaging in dialogue with the farmer regarding the reasons for the regulations. Moreover, a theme of agreement showed interpretation as unavoidable. We discuss how the points of view or strategies of the inspectors may affect the outcome of animal welfare inspections, both on a short- and long-term basis. We argue that this study can initiate a necessary and more open discussion of the aforementioned dilemma.

Individuals are often ambiguity-averse when choosing among purely chance-based prospects (Ellsberg, 1961). However, they often prefer apparently ambiguous ability-based prospects to unambiguous chance-based prospects. According to the competence hypothesis (Heath & Tversky, 1991), this pattern derives from favorable perceptions of one’s competence. In most past tests of the competence hypothesis, ambiguity is confounded with personal controllability and the source of the ambiguity (e.g., chance vs. missing information). We unconfound these factors in three experiments and find strong evidence for independent effects of both ambiguity aversion and competence. In Experiment 1, participants preferred an unambiguous chance-based option to an ambiguous ability-based option when the ambiguity derived from chance rather than uncertainty about one’s own ability. In Experiments 2 and 3, which used different operationalizations of ambiguity in choice contexts with actual consequences, participants attempted to avoid both ambiguity and chance insofar as they could. These findings support and extend the competence hypothesis by demonstrating ambiguity aversion independent of personal controllability and source of ambiguity.

Many natural decisions contain an element of skill. Modern conceptions of the skill component include control (Goodie, 2003) and competence (Heath & Tversky, 1991). The control hypothesis states that a task's skill component (the sensitivity of the task to skill) affects decision making; the competence hypothesis states decision making is affected only if the participant possesses the skill. Three experiments compared risk taking patterns between two groups. One group faced bets on random events, and another group faced bets on their answers to general knowledge questions, which is a task characterized by control. In Experiment 1, control increased risk taking markedly with all statistical properties held constant. In Experiment 2, decisions made in domains of varying difficulty, and by individuals of varying ability, yielded further qualified support for the role of competence. In Experiment 3, the role of control was replicated, and participants’ perceptions of the differences in group treatments aligned more with the implications of the control hypothesis than with the competence hypothesis. Results offered support for the control hypothesis across a range of competence.

This study analysed the free use of phrases related to animal-based and resource-based measures of animal welfare in Swedish state animal welfare inspection reports on conventional (C) and organic (O) farms. From 244 reports by 35 inspectors, 88 were analysed as matched pairs of C and O farms (same inspector, species and size of farm). They were analysed ‘blind’ for negative comments referring to the animals or to the resources (buildings and facilities). The most commonly reported deficiencies were poor body and hoof condition and dirty animals, accounting for a total of 79% of all animal-based remarks. Deficiencies in measures and equipment or excessively high stocking density together accounted for 78% of all resource-based remarks. The total number of general (non-compulsory) comments was similar for O and C farms. But the number of (compulsory) requirements for change to comply with legislation was almost twice as high for O than C. There were significantly more comments about body condition and hooves in C than O but a tendency for the opposite to be the case for animal health. Despite this, the number of requirements for change was greater for O-farms regarding their animals. There was no difference in number of comments on resources, but once more a tendency for more requirements for change was seen on O-farms. The study demonstrates that the analysis of inspection reports can be useful in terms of identifying where, in practice, animal welfare problems lie as well as further developing the methodology of animal welfare control.

Assistive forces transmitted from wearable robots to the robot’s users are often defined by controllers that rely on the accurate estimation of the human posture. The compliant nature of the human–robot interface can negatively affect the robot’s ability to estimate the posture. In this article, we present a novel algorithm that uses machine learning to correct these errors in posture estimation. For that, we recorded motion capture data and robot performance data from a group of participants (n = 8; 4 females) who walked on a treadmill while wearing a wearable robot, the Myosuit. Participants walked on level ground at various gait speeds and levels of support from the Myosuit. We used optical motion capture data to measure the relative displacement between the person and the Myosuit. We then combined this data with data derived from the robot to train a model, using a grading boosting algorithm (XGBoost), that corrected for the mechanical compliance errors in posture estimation. For the Myosuit controller, we were particularly interested in the angle of the thigh segment. Using our algorithm, the estimated thigh segment’s angle RMS error was reduced from 6.3° (2.3°) to 2.5° (1.0°), mean (standard deviation). The average maximum error was reduced from 13.1° (4.9°) to 5.9° (2.1°). These improvements in posture estimation were observed for all of the considered assistance force levels and walking speeds. This suggests that ML-based algorithms provide a promising opportunity to be used in combination with wearable-robot sensors for an accurate user posture estimation.

Fiduciary agents and trust-based institutions are increasingly proposed and considered in legal, regulatory, and ethical discourse as an alternative or addition to a control-based model of data management. Instead of leaving it up to the citizen to decide what to do with her data and to ensure that her best interests are met, an independent person or organization will act on her behalf, potentially also taking into account the general interest. By ensuring that these interests are protected, the hope is that citizens’ willingness to share data will increase, thereby allowing for more data-driven projects. Thus, trust-based models are presented as a win–win scenario. It is clear, however, that there are also apparent dangers entailed with trust-based approaches. Especially one model, that of data trusts, may have far-reaching consequences.