Artificial intelligence and UK national security: Policy considerations

RUSI was commissioned by GCHQ to conduct an independent research study into the use of artificial intelligence (AI) for national security purposes. The aim of this project is to establish an independent evidence base to inform future policy development regarding national security uses of AI. The findings are based on in-depth consultation with stakeholders from across the UK national security community, law enforcement agencies, private sector companies, academic and legal experts, and civil society representatives. This was complemented by a targeted review of existing literature on the topic of AI and national security. The research has found that AI offers numerous opportunities for the UK national security community to improve efficiency and effectiveness of existing processes. AI methods can rapidly derive insights from large, disparate datasets and identify connections that would otherwise go unnoticed by human operators. However, in the context of national security and the powers given to UK intelligence agencies, use of AI could give rise to additional privacy and human rights considerations which would need to be assessed within the existing legal and regulatory framework. For this reason, enhanced policy and guidance is needed to ensure the privacy and human rights implications of national security uses of AI are reviewed on an ongoing basis as new analysis methods are applied to data

Evaluating strategies for implementing industry 4.0: a hybrid expert oriented approach of B.W.M. and interval valued intuitionistic fuzzy T.O.D.I.M.

open access articleDeveloping and accepting industry 4.0 influences the industry structure and customer willingness. To a successful transition to industry 4.0, implementation strategies should be selected with a systematic and comprehensive view to responding to the changes flexibly. This research aims to identify and prioritise the strategies for implementing industry 4.0. For this purpose, at first, evaluation attributes of strategies and also strategies to put industry 4.0 in practice are recognised. Then, the attributes are weighted to the experts’ opinion by using the Best Worst Method (BWM). Subsequently, the strategies for implementing industry 4.0 in Fara-Sanat Company, as a case study, have been ranked based on the Interval Valued Intuitionistic Fuzzy (IVIF) of the TODIM method. The results indicated that the attributes of ‘Technology’, ‘Quality’, and ‘Operation’ have respectively the highest importance. Furthermore, the strategies for “new business models development’, ‘Improving information systems’ and ‘Human resource management’ received a higher rank. Eventually, some research and executive recommendations are provided. Having strategies for implementing industry 4.0 is a very important solution. Accordingly, multi-criteria decision-making (MCDM) methods are a useful tool for adopting and selecting appropriate strategies. In this research, a novel and hybrid combination of BWM-TODIM is presented under IVIF information

The relationship between thinking style differences and career choice for high-achieving high school students

The intent of this study was to study high achieving students\u27 career decision-making associated with thinking styles and to examine factors influencing career choices. A causal-comparative research design and correlational research design were used, with a sample of 209 high school students. Data were gathered from two International Baccalaureate (TB) programs and a Governor\u27s School Program. Students responded to two types of questionnaire---the Thinking Style Inventory, and A Questionnaire Related to Career Choices and Students\u27 Sensitivity toward Environmental Forces.;The findings of this study demonstrated that the effect of program on different thinking styles was significant (p \u3c .05), and the effect of gender on different thinking styles was significant ( p \u3c .01). Also, the findings showed that an external thinking style was a good predictor for choosing the social science area for future careers. However, students with a higher external thinking style chose computer and math areas 73% less than students with lower external thinking style. Also, the findings of the study demonstrated that students\u27 passion for a specific subject and family environment were also important factors influencing career choices of high achieving high school students.;The study suggested the importance of taking thinking styles into consideration for the career development of high-achieving adolescents. In addition, the environmental influences of parents, family, and schools are also important considerations for students\u27 career development, along with students\u27 inherent interest in a subject. Therefore, parents, teachers, and guidance counselors should recognize their own critical roles in shaping students\u27 career development

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare

When We Don\u27t See Eye to Eye: Discrepancies Between Supervisors and Subordinates in Absence Disciplinary Decisions

This study provided a within-subjects assessment of the factors associated with absence disciplinary decisions for both supervisors and subordinates. In addition, this study examined discrepancies in disciplinary decisions between a supervisor and his or her subordinates based on differences in psychological and demographic attributes. A sample of non-academic employees from 19 intact triads (one supervisor; two subordinates) at a large Midwest university responded to hypothetical scenarios describing factors that might contribute to absence disciplinary decisions. The results demonstrated that both supervisors and subordinates consider the same set of factors as relevant to disciplinary decisions. Furthermore, with few exceptions, psychological and demographic differences between supervisors and subordinates related positively to discrepancies in disciplinary decisions. The implications of these findings for managing disciplinary programs in organizations are discussed