The impact of artificial intelligence on the current and future practice of clinical cancer genomics.

Artificial intelligence (AI) is one of the most significant fields of development in the current digital age. Rapid advancements have raised speculation as to its potential benefits in a wide range of fields, with healthcare often at the forefront. However, amidst this optimism, apprehension and opposition continue to strongly persist. Oft-cited concerns include the threat of unemployment, harm to the doctor-patient relationship and questions of safety and accuracy. In this article, we review both the current and future medical applications of AI within the sub-speciality of cancer genomics

Implications in productivity and employment

UIDB/04647/2020 UIDP/04647/2020Recent developments in automation and Artificial Intelligence (AI) are leading to a wave of innovation in organizational design and changes in the workplace. Techno-optimists even named it the ‘second machine age’, arguing that it now involves the substitution of the human brain. Other authors see this as just a continuation of previous ICT developments. Potentially, automation and AI can have significant technical, economic, and social implications in firms. The paper will answer the question: what are the implications on industrial productivity and employment in the automotive sector with the recent automation trends, including AI, in Portugal? Our approach used mixed methods to conduct statistical analyses of relevant databases and interviews with experts on R&D projects related to automation and AI implementation. Results suggest that automation can have widespread adoption in the short term in the automotive sector, but AI technologies will take more time to be adopted. Findings show that adoption of automation and AI increases productivity in firms and is dephased in time with employment implications. Investments in automation are not substituting operators but rather changing work organization. Thus, negative effects about technology and unemployment were not substantiated by our results.publishersversionpublishe

Implications on industrial productivity and employment in automotive sector

UIDB/04647/2020 UIDP/04647/2020Recent developments in automation and artificial intelligence (AI) are leading to a wave of innovation in organizational design and changes in the workplace. Techno-optimists even named it the “second machine age,” arguing that it now involves the substitution of the human brain. Other authors see this as just a continuation of previous ICT developments. Potentially, automation and AI can have significant technical, economic, and social implications in firms. This paper will answer the following question: What are the implications on industrial productivity and employment in the automotive sector with the recent automation trends, including AI, in Portugal? Our approach used mixed methods to conduct statistical analyses of relevant databases and interviews with experts on R&D projects related to automation and AI implementation. Results suggest that automation can have widespread adoption in the short term in the automotive sector, but AI technologies will take more time to be adopted. The findings show that adoption of automation and AI increases productivity in firms and is dephased in time with employment implications. Investments in automation are not substituting operators but rather changing work organization. Thus, negative effects of technology and unemployment were not substantiated by our results.publishersversionpublishe

Artificial intelligence and job security challenges

Abstract: As artificial intelligence (AI) continues to advance, its impact on job security becomes a topic of significant concern and debate. While some argue that AI applications will lead to substantial job displacement and unemployment, others believe that it will create new jobs and employment opportunities. This article explores the impact of artificial intelligence on job security, the challenges it poses, and the strategies to maintain job security in the age of AI. We concluded that AI affects job security in diverse ways, acting in certain situations as a complement to human skills, and in other cases as a replacement for them. This complex impact necessitates a balanced approach that embraces AI's potential while taking into account the societal considerations to ensure a sustainable future for job security in the age of AI. Keywords: artificial intelligence, job security, labor market, technology, challenges

Booms, busts and retirement timing

Cyclical fluctuations - which affect both asset and labour markets - can have an ambiguous effect on retirement. We explore this empirically using data from the British Household Panel Survey, exploiting small area geographic identifers to match local house prices, earnings and unemployment to respondents. We match stock prices via the date of interview. Our results show little evidence of any positive wealth effects despite large spatial and temporal variations in asset prices over the period analysed. We find more response to local labour market conditions - increases in unemployment are associated with earlier retirement while increases in wages delay retirement

Social Dimension of Intra-EU Mobility: Impact on Public Services

Freedom of movement of citizens constitutes one of the core values of the European Union and is closely linked to European citizenship. There is, however, a heated debate in many of the destination Member States about the impact of intra-EU mobility on their public services. The debate centres on the ‘welfare magnet hypothesis’, which holds that migrants, including mobile citizens from the central and eastern European Member States, are attracted by the better quality of these services and easier access to them in the host countries. The issue has become highly politicised recently, especially as a consequence of the economic crisis and the increased inflow of these EU mobile citizens. The main objective of this research project is to explore whether there is any evidence to support the welfare magnet hypothesis. It examines the take-up of benefits and social services by mobile citizens from 10 central and eastern European Member States (EU10 mobile citizens) in 9 host countries – Austria, Denmark, Germany, Ireland, Italy, the Netherlands, Spain, Sweden and the UK – compared to the native populations and other citizen groups. It also seeks to identify the obstacles to their integration in the host countries and initiatives to aid their integration

Semiparametric Bayesian Time-Space Analysis of Unemployment Duration

In this paper, we analyze unemployment duration in Germany with official data from the German Federal Employment Office for the years 1980-1995. Conventional hazard rate models for leaving unemployment cannot cope with simultaneous and flexible fitting of duration dependence, nonlinear covariate effects, trend and seasonal calendar time components and a large number of regional effects. We apply a semiparametric hierarchical Bayesian modelling approach that is suitable for time-space analysis of unemployment duration by simultaneously including and estimating effects of several time scales, regional variation and further covariates. Inference is fully Bayesian and uses recent Markov chain Monte Carlo techniques

The impact of labour market dynamics on the return-migration of immigrants

Using administrative panel data on the entire population of new labour immigrants to The Netherlands, we estimate the effects of individual labour market spells on immigration durations using the “timing-of-events” method. The model allows for correlated unobserved heterogeneity across migration, unemployment and employment processes. We find that unemployment spells increase return probabilities for all immigrant groups, while re-employment spells typically delay returns