@inproceedings{7559,
  keywords = {Labour market, tasks, AI benchmarks, AI impact, AI intensity, Simulation},
  author = {Fernando Mart'nez-Plumed and Song'l Tolan and Annarosa Pesole and José Hern'ndez-Orallo and Enrique as and Emilia G'mez},
  title = {Does AI qualify for the job? A bidirectional model mapping labour and AI intensities},
  abstract = {In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.},
  year = {2020},
  journal = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
  pages = {94–100},
  isbn = {9781450371100},
  doi = {10.1145/3375627.3375831},
  language = {eng},
}