Towards Establishing Criteria for the Ethical Analysis of Artificial Intelligence

Science and Engineering Ethics - Ethical reflection on Artificial Intelligence (AI) has become a priority. In this article, we propose a methodological model for a comprehensive ethical analysis of...     

Outliers and Influential Observations in Exponential Random Graph Models

We discuss measuring and detecting influential observations and outliers in the context of exponential family random graph (ERG) models for social networks. We focus on the level of the nodes of the network and consider those nodes whose removal would result in changes to the model as extreme or “central” with respect to the structural features that “matter”. We construe removal in terms of two case-deletion strategies: the tie-variables of an actor are assumed to be unobserved, or the node is removed resulting in the induced subgraph. We define the difference in inferred model resulting from case deletion from the perspective of information theory and difference in estimates, in both the natural and mean-value parameterisation, representing varying degrees of approximation. We arrive at several measures of influence and propose the use of two that do not require refitting of the model and lend themselves to routine application in the ERGM fitting procedure. MCMC p values are obtained for testing how extreme each node is with respect to the network structure. The influence measures are applied to two well-known data sets to illustrate the information they provide. From a network perspective, the proposed statistics offer an indication of which actors are most distinctive in the network structure, in terms of not abiding by the structural norms present across other actors.     

A comparison of individuals with unanswered callings to those with no calling at all

The purpose of this research was to compare the life-, job-, and health-related experiences of those who perceive an unanswered occupational calling to those who (1) are living a calling and (2) perceive no calling at all. Surveys containing measures of callings, work engagement, job involvement, career commitment, life and job satisfaction, turnover intentions, physical health and emotional well-being were administered to 378 American academics. As expected, academics with an answered occupational calling tended to report better job attitudes and domain-specific satisfaction and less withdrawal intentions than those who reported an unanswered occupational calling or no calling at all. Furthermore, those who did not have a calling to a particular vocation reported better life-, job-, and health-related outcomes than those experiencing an unanswered calling. Surprisingly, only those academics experiencing an unmet calling reported significantly poorer physical and psychological health as compared to the other two calling groups. These results are consistent with the self-determination theory, which predicts that those who are able to satisfy their basic psychological needs reap benefits in terms of psychological growth, optimal functioning, and wellbeing. The study contributes to the literature on callings by showing that having a calling is a benefit only if it is met, but can be a detriment when it is not as compared to having no calling at all.