A socio-technical system is a type of system in which both social and technical elements are intertwined with each other.
AI Systems are considered social-technical because they are not just technical tools but also have a social impact on the people who use them and are affected by them. AI systems incorporate a range of technical components such as algorithms, data processing, and machine learning but also rely on social elements such as human input, design, and context.
These systems require careful attention to not only the technical components but also the social factors such as ethical considerations, user experience, and the impact on society as a whole.
As per the TTC Joint Roadmap on AI, the "socio-technical characteristics of AI trustworthiness" define a system as trustworthy if it is valid and reliable, safe, fair and has managed bias, secure and resilient, accountable and transparent, explainable and interpretable, and privacy-enhanced.