Re-Shaping Interpreter Education in the AI EraFrom Training of Interpreting Skills to Devel opment of Interpreter Competence

This chapter discusses two core questions facing the interpreting profession and interpreter education in the AI era: (1) Which aspects of human interpreters’ work may be replaceable or irreplaceable by the machine? (2) What shifts need to be made in interpreter education in line with the new development of AI technologies? On the basis of the multidimensional epistemological model of interpreting, the different components of human interpreting are analysed to assess whether they might be done by the machine. Three major shifts are identified as necessary in re-shaping interpreter education in the AI era. A multicomposite framework of interpreter competence is proposed as the conceptual foundation, of which seven interpreter competence composites are elaborated. A survey is conducted to gauge the relative importance of the 33 components of interpreter competence and coverage of them in current interpreting curricula, which shows that interpreters consider all the seven competence composites important in the profession but AI literacy and application ability have not been covered adequately in interpreter education. Therefore, a focused discussion is provided on critical AI literacy and application ability of interpreters, in order to flesh out the details of this competence composite.