Abstract
Artificial Intelligence (AI) is interwoven in everyday life with large ramifications for technical communication and UX. AI is divided into robotics, autonomous vehicles, machine learning, and natural language processing.Through AI-driven smart design systems, big data metrics programs, automatic A-B testing, and intelligent writing systems, content strategy systems, technical communicators are interfacing with AI systems in various ways and changing practices for UX (cf. Ealey, 2018; Texeira, 2017). Despite this research, little is known about how we can use practical design dimensions of AI systems to inform social justice purposes. As AI is designed around specific performance criteria, this paper argues that combining social justice perspectives with AI design frameworks such as PEAS (Performance, Environment, Actuators, Sensors) and D-Soaked (Deterministic, Static, Observable, Agency, Knowledge, Episodic, Discreteness) may help technical communicators better intervene in the design of such systems.
| Original language | English |
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| State | Published - Oct 5 2020 |
| Event | ACM Special Interest Group Design of Communication 2020 - New York, NY Duration: Oct 5 2020 → Oct 5 2020 |
Conference
| Conference | ACM Special Interest Group Design of Communication 2020 |
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| Period | 10/5/20 → 10/5/20 |