Reshaping the core competitiveness of broadcasters in the context of AI: emotional expression, cultural control and human-machine collaboration

Abstract

Under the impetus of artificial intelligence, the core competencies of traditional broadcasters are severely tested. This study constructs a three-dimensional model of the broadcasters’ core competencies in the context of artificial intelligence, namely emotional competency, cultural competency, and human-AI collaborative competency. On the basis of mixed methods, surveys on 300 broadcasters, 500 audiences, and 50 media organizations were implemented, supplemented by in-depth interviews and case studies. The findings show that under the impact of artificial intelligence, the three aspects of broadcasters’ core competency all indicated significant improvement: emotional competency increased from a mean score to a mean score, improving by 0.45 points; cultural competency increased from a mean score to a mean score, improving by 0.42 points; human-AI collaborative competency increased from a mean score to a mean score, improving by 0.43 points; core competency index increased from a mean score to a mean score, improving by 43%. The weights for the three dimensions are 42%, 35%, and 23% respectively, with emotional competency being most prominent. The research findings can be used to inform broadcaster education and media professional development.