Automation, artificial intelligence and robotics: emerging issues and debates in human factors and ergonomics

Figures & data

Figure 1. Scopus citations for the Ironies of Automation (Bainbridge 1983).

Table 1. ChatGPT 3.5 response to the special issue topic.

Prompt

Response

Within the human factors and ergonomics field what are the current knowledge gaps, debates, and controversies relating to automation, artificial intelligence and robotics?

As of my last knowledge update in January 2022, I can provide insights into some general trends and discussions within the human factors and ergonomics field regarding automation, artificial intelligence (AI), and robotics. However, it’s important to note that the field is rapidly evolving, and new developments may have occurred since then. Here are some key points: 1. Trust and reliance on automation: Knowledge Gap: Understanding how users develop trust in automated systems and how this trust influences their reliance on automation is an ongoing area of research. The dynamics of trust are complex and depend on factors such as system reliability, transparency, and user experience. Debate: There is a debate about the appropriate level of automation in various domains. Striking the right balance between human control and automation to optimise performance and safety is a challenging aspect. 2. Human-AI collaboration: Knowledge Gap: Research is exploring how humans can effectively collaborate with AI systems. This involves understanding the optimal division of tasks between humans and AI and designing interfaces that facilitate seamless collaboration. Debate: There are discussions about the potential impact of AI on job roles and whether automation leads to job displacement or the creation of new, complementary roles. 3. User interface design: Knowledge Gap: Designing user interfaces for complex systems involving AI and robotics requires an understanding of how users perceive and interact with the technology. This includes issues related to information presentation, decision-making support, and the integration of AI suggestions. Controversy: Balancing the need for comprehensive information with the risk of information overload is a point of contention. Designing interfaces that provide relevant information without overwhelming the user remains a challenge. 4. Ethical considerations: Knowledge Gap: Ethical issues related to AI and robotics in human factors include issues such as bias in algorithms, privacy concerns, and the ethical implications of decisions made by autonomous systems. Controversy: There are ongoing debates about the ethical responsibilities of designers, engineers, and organisations in ensuring that automated systems are fair, transparent, and unbiased. 5. Training and skill development: Knowledge Gap: Understanding how to train individuals to work effectively with automated systems is a key area of research. This involves assessing the impact of training programs on user performance, situation awareness, and overall system understanding. Debate: There are discussions about the types of skills that will be most valuable in a future where automation and AI are prevalent. This includes debates about the role of education and training in preparing individuals for this changing landscape. 6. Psychological and behavioural aspects: Knowledge Gap: Exploring the psychological and behavioural aspects of human-robot interaction, including user preferences, attitudes, and the emotional impact of interacting with AI and robotic systems. Debate: Discussions focus on how emotional intelligence in machines can enhance human-machine collaboration and the potential implications for user well-being. Research and discussions in these areas continue to evolve as technology advances and the deployment of AI and robotics becomes more widespread. To get the latest information, it’s advisable to check recent publications and conferences in the field of human factors and ergonomics.

Bainbridge, L. 1983. “Ironies of Automation.” Automatica 19 (6): 775–779. doi:10.1016/0005-1098(83)90046-8.

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