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Expert Insights
Gillian Salerno-Rebic and Maria Burke contend that while AI may speed up the process, its outputs often do not rival a seasoned professional's finesse in visual design. They anchor their argument in experience, highlighting that despite AI's potential, the time needed to train the model may offset its touted efficiency.
Hear Gillian and Maria illustrate:
- Why the human creative flair and expertise, honed over years, still outperforms AI in the domain of visual design.
- How the time investment to train the AI model to produce desirable results could offset the efficiency advantages of the technology.
- The potential friction AI could introduce into workflows due to the effort involved in initial model training.
Quote
I have a decade of experience in this. I'm like, what you're gonna output for me is not as good as what I can do on my own, and right now it's about the like, yeah, maybe it'll be a little bit faster, but I have to spend the time maybe like training the model to get what I want.
Gillian Salerno-Rebic and Maria Burke ,
Founders, North + Form
THE NEW DEFAULT angle
Here's how to navigate the nuances of implementing AI in visual design workflows:
- Validate AI Outcomes: Cross-verify downstream outputs to ensure AI generated designs match the caliber of a seasoned professional's work.
- Invest in Model Training: Accept that training the AI model to produce desirable outcomes may initially demand significant time, but strategic investment may prove beneficial in the long run.
- Balance Human Expertise with AI: Algorithms can fast-track certain tasks, but an experienced human touch may still be needed to achieve the highest quality in visual design.
- Be Open to Iterative Adoption: Gradually integrate AI into design workflows, gauging and adjusting its role based on practical efficiency and quality outcomes.