认知
计算机科学
人工智能
知识管理
自动化
经验证据
数据科学
认知科学
心理学
工程类
认识论
机械工程
哲学
神经科学
作者
Yangyang Deng,Liang Chen,Kwanghui Lim
标识
DOI:10.5465/amproc.2023.13359abstract
摘要
Artificial intelligence (AI) as a powerful emerging technology is deemed to impact a wide range of industries. Recent research focuses on AI’s automation and efficiency improvement, but little do we know about AI’s role in cognitively demanding tasks, such as innovation. This study explores this question by examining how AI can augment inventors in dealing with innovation complexity. While the increasing complexity in searching and combining technologies is a major challenge for current innovation, AI might be a possible solution since it is highly efficient in complex contexts. However, AI also reflects and even amplifies biases in historical data and may mislead humans. Therefore, this paper discusses whether and how AI can augment inventors in innovation. The results show that AI alone does not have positive effects on improving inventors’ performance in dealing with innovation complexity, but it can augment inventors with high knowledge breadth and large networks. This study provides empirical evidence on AI's augmenting effects in cognitive tasks and identifies knowledge accumulation and network as two important complementary factors in working with AI. This study also provides insights for future discussions on AI's role in other cognitive tasks at higher levels (e.g., teams or organizations).
科研通智能强力驱动
Strongly Powered by AbleSci AI