This chapter reflects on major issues recounted in the previous chapters, raising three key questions relevant to the Artificial Intelligence and the Future of Skills project. What is the value in identifying ideal models when comparing humans with artificial intelligence (AI) and robotic systems? How might systematic mapping occur between skill taxonomies, tasks, tests and functional AI components? How can major differences be handled in targeted skills, different occupations and changes in the world? Some suggestions are offered on next steps in addressing these questions.

This chapter takes a step back from the project, reviewing practical issues around the assessment of artificial intelligence (AI) that must guide the next phase of research. It provides guidance for setting up a general analytical framework for assessing AI capabilities with regard to human skills. Questions are centred around three main issues. First, the chapter looks at how the various parameters of measurement depend on the objectives of the assessment. Second, it examines selection of tests for comparing AI and human skills. Third, it discusses selection and training of raters. The chapter concludes with a summary of issues considered in planning the study.

This chapter synthesises the expert contributions of the report and offers perspectives for building a comprehensive assessment of artificial intelligence (AI) capabilities. It compares and contrasts the contributions of psychologists and computer scientists along two dimensions: whether they focus on human or AI taxonomies and tests, and whether they test isolated capabilities or more complex tasks. The chapter argues that a more complete assessment of AI must bring together the different approaches. It illustrates this argument with an example in the area of language. Finally, the chapter offers next steps towards a systematic assessment of AI capabilities, which will allow for drawing fine-grained implications for work and education.