Machine-centric

Machine-centric describes a system, process, or design that is primarily focused on the needs and capabilities of the machine or technology involved, rather than prioritizing user experience, human interaction, or overall goals. It often implies an emphasis on technical specifications, efficiency of the machine, and internal workings, potentially at the expense of usability, accessibility, and broader societal impacts. This approach can lead to complex interfaces, difficult-to-understand outputs, and solutions that are optimized for the machine's logic rather than the user's needs. It contrasts with approaches that are human-centered or goal-oriented.

Machine-centric meaning with examples

• The software's original design was machine-centric, with a command-line interface that demanded users understand complex coding to complete simple tasks. This design emphasized the server's processing power and ignored the users' need for ease of use. Resulting in a steep learning curve for the software.
• In the early days of AI, the development of machine-centric algorithms prioritized computational efficiency and model accuracy. Little consideration was given to the potential biases embedded in data or the ethical ramifications of AI systems making decisions on the data, leading to unfair and harmful outcomes.
• The industrial automation system, due to being machine-centric, streamlined the manufacturing process for maximum output, regardless of worker comfort or safety. Though the production rate increased, high accident rates decreased worker satisfaction, as these machine-centric systems prioritized production above all else.
• The new online education platform was initially designed in a machine-centric way; focusing on the delivery of digital content rather than engaging the students. The platform's focus on the machines capability limited any interactions with the student; leading to poor course completion rates.