As AI is integrated into the workplace, organisations increasingly face allocation decisions between human and machine workers. These decisions are increasingly made or assisted by algorithms, creating a Reverse Turing Test dynamic wherein the machine is now the judge. In addition, human and machine workers may ``compete'' for a given task, reproducing aspects of adversarial games. This raises new methodological questions about assessing task suitability between humans and machines. The criteria often used to assess people (e.g., education, experience, references) cannot (...) feasibly scale to AI systems; conversely, AI evaluation methods (benchmarks, red teaming, leaderboards) cannot be easily applied to human workers or yield comparable metrics. In this position paper, we argue that suitability evaluations for task-assignment should be profile-driven -- that is, based on assessments that infer latent constructs such as capabilities and propensities from observed performance. This approach places humans and AI systems on shared scales, supporting comparisons that are predictive of novel-task performance, explanatory of why agents succeed or fail, and auditable. We outline the core features of this approach, discuss its practical implications, and compare it with alternative frameworks for human-machine workplace allocation. (shrink)

Even with obvious deficiencies, large prompt-commanded multimodal models are proving to be flexible cognitive tools representing an unprecedented generality. But the directness, diversity, and degree of user interaction create a distinctive “human-centred generality” (HCG), rather than a fully autonomous one. HCG implies that —for a specific user— a system is only as general as it is effective for the user’s relevant tasks and their prevalent ways of prompting. A human-centred evaluation of general-purpose AI systems therefore needs to reflect the personal (...) nature of interaction, tasks and cognition. We argue that the best way to understand these systems is as highly-coupled cognitive extenders, and to analyse the bidirectional cognitive adaptations between them and humans. In this paper, we give a formulation of HCG, as well as a high-level overview of the elements and trade-offs involved in the prompting process. We end the paper by outlining some essential research questions and suggestions for improving evaluation practices, which we envision as characteristic for the evaluation of general artificial intelligence in the future. (shrink)

The military metaverse integrates immersive digital technologies, virtual worlds, artificial intelligence (AI), extended reality (XR), and digital twins to enhance capabilities across the defence enterprise. Within this framework, Digital Human Twins (DHTs) function as dynamic digital representations of military personnel and sometimes “things”, supporting training, mission planning, operational decision-making, health monitoring, equipment design and acquisition, and human–machine teaming. DHTs can be considered “actors” on a metaverse “stage”. This paper explores the role of DHTs in defence, categorising them into real human-derived, (...) artificial, hybrid, and anthropomorphic twins, each serving one or more military functions. DHTs offer significant advantages in adaptive training, career development, operational effectiveness, and equipment optimisation, but also present challenges related to data security, AI reliability, ethical concerns, and trust in autonomous decision-support systems. To address these complexities, we propose an extended version of the Digital Twin Capability Periodic Table (CPT), originally developed for engineering digital twins, by incorporating ethical considerations, psychological fidelity, social interaction, and autonomy levels. This structured framework can support the development and governance of DHTs across defence and other domains. By adopting a comprehensive approach to DHT implementation, including interoperability, data governance, and ethical oversight, organisations can unify their human data and maximise operational benefits whilst mitigating risks. The paper concludes with strategic recommendations for implementation, emphasising research investment and trials, AI governance policies, exploiting the extended CPT, and cross-sector collaboration to refine and standardise DHT deployment. (shrink)

This paper explores the interwoven lives of donkeys and the people who depend on them for their livelihoods in central Ethiopia. Drawing on data from 12 participatory workshops, insights were elicited into the ways human co-workers value and treat their donkey co-workers. Methodologically, Participatory Rural Appraisal (PRA) and Appreciative Inquiry (AI) techniques were merged to explore the complex and multi-dimensional contributions donkeys make to participants’ lives. Findings reveal working with donkeys can make the difference between destitution and modest survival, but (...) societal perception of donkeys as low-status animals has an impact on their owners’ lives and donkey wellbeing. This research contributes empirical insights on the valuing of donkeys and enables a deepened understanding of human-donkey relations. The combination of PRA and AI in the methodology demonstrates how to formulate a compassionate and empathetic approach for exploring donkey value and wellbeing with marginalized groups. (shrink)

The German invasion of the Soviet Union in June of 1941 has long been attributed to errors by Joseph Stalin, yet a revisionist position known as the Icebreaker hypothesis has also emerged alleging that Stalin is not to blame. This essay examines why the Icebreaker theory is erroneous based on its lack of concrete facts. The reasons why Operation Barbarossa was so effective are also examined, leading to the conclusion that Stalin should still shoulder most of the blame for Soviet (...) disorganization prior to the invasion. (shrink)

Critically examining popular ESL textbooks, this accessible and engaging book uncovers gender and ethnic representations that impact young English language learners in US public schools and provides equitable, egalitarian alternatives.

We present a one per cent measurement of the cosmic distance scale from the detections of the baryon acoustic oscillations in the clustering of galaxies from the Baryon Oscillation Spectroscopic Survey, which is part of the Sloan Digital Sky Survey III. Our results come from the Data Release 11 sample, containing nearly one million galaxies and covering approximately 8500 square degrees and the redshift range 0.2 < z < 0.7. We also compare these results with those from the publicly released (...) DR9 and DR10 samples. Assuming a concordance Λ cold dark matter cosmological model, the DR11 sample covers a volume of 13 Gpc3 and is the largest region of the Universe ever surveyed at this density. We measure the correlation function and power spectrum, including density-field reconstruction of the BAO feature. The acoustic features are detected at a significance of over 7σ in both the correlation function and power spectrum. Fitting for the position of the acoustic features measures the distance relative to the sound horizon at the drag epoch, rd, which has a value of rd,fid = 149.28 Mpc in our fiducial cosmology. We find DV = at z = 0.32 and DV = at z = 0.57. At 1.0 per cent, this latter measure is the most precise distance constraint ever obtained from a galaxy survey. Separating the clustering along and transverse to the line of sight yields measurements at z = 0.57 of DA = and H =. Our measurements of the distance scale are in good agreement with previous BAO measurements and with the predictions from cosmic microwave background data for a spatially flat CDM model with a cosmological constant. © 2014 The Author Published by Oxford University Press on behalf of the Royal Astronomical Society. (shrink)