Entre la estrategia y el existencialismo. Construyo ecosistemas de innovación y escribo para descifrar la identidad, los negocios y el sentido de la vida.
Creators: This employees help build the GenAI models for their orgs and develop tools and interfaces most of us use to interact with these models.
Heavy Users: They use GenAI to help them perform most of their core tasks or to enhance their work functions.
Light Users: Use GenAI to perform less than 50% of their primary tasks.
Non Users: They are either unaffected or unaware of the impact of GenAI on their jobs.
Jobs that feature reliable and supportive people, caring leaders and meaningful work are attractive to creators and heavy users of GenAI.
GenAI and Product Design
AI outputs could be impressive, but producing meaningful ones and turning them into desirable, user centric, manufacturable product that matches user preferences, pain points and expectations doesn’t happen by just pressing a button.
Get Alexander Parrales Arango’s stories in your inbox
Join Medium for free to get updates from this writer.
Some considerations:
Conducting consumer research. Combine GenAI produced insights and primary consumer research to gain a much richer understanding of user preferences than either can provide on their own in the same period.
Developing effective prompts. Highly iterative prompting is required to produce something close to what designers envision, consumers want and companies can manufacture.
Design experts must provide context for overall concept, determine how much detail to include and consider prompt length and how to separate complex prompts.
Refining GenAI outputs. Perform substantial postproduction editing to achieve a meaningful result. Designers and engineers must create their refined version of a concept to ensure the product accounts for manufacturing specifications, requirements and constraints.
Curating the best concepts. Too many choices can overwhelm both, important stakeholders and consumers. Design experts must identify the best ideas from the large number of options produced.
Adding a good dose of human empathy. AI tools are only as good as the data they are trained on. They may reproduce historical biases, oversimplify pros and cons, and gloss over insightful nuances of human behavior. Consider aesthetics, cultural and regional preferences, ergonomics, usability, and accessibility.
Press enter or click to view image in full size
The Human Side of GenAI
From my notebooks of notes taken from books, articles, podcasts, videos, and business events.
Entre la estrategia y el existencialismo. Construyo ecosistemas de innovación y escribo para descifrar la identidad, los negocios y el sentido de la vida.
