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The risks of employing AI in design and product development generally stem from failing to understand its limitations. To reap the benefits of AI and avoid its pitfalls, it’s important to keep in mind what AI is not and what it cannot do. You need to understand both the strengths and weaknesses of this new generation of tools. Here are four limitations of the AI that to keep in mind when working with the technology.
AI has no context awareness. At its basic level, successful design is closely tied to understanding the specific context in which design solutions will be used. However, AI outputs do not appreciate or even recognize important nuances critical to solving user problems. Instead, AI may offer generalized advice or ideas that overlook key aspects of the issue. It’s important to be aware of the risks of solely relying on AI and failing to observe and think critically about the situations outside of AI.
Remember: AI doesn’t recognize nuance, so contributing your critical thinking is essential.
AI is not omniscient or all-knowing. AI companies often portray their tools as having near-magical powers, but the reality is that AI outputs are only as good as the data used to train them. Unawareness of these behind-the-scenes AI production methods can lead users to feel confidence in AI outputs that are unwarranted. AI might also reproduce biases and flawed reasoning found in its training data, which often includes English language information with its associated cultural and demographic biases.
Remember: Maintain a healthy dose of skepticism regarding the accuracy and completeness of AI outputs.
AI is not as user-friendly as it seems. If you have explored the generative AI tools ChatGPT or MidJourney, you have likely discovered that effectively communicating with AI is its own skill set. The fact is, AI cannot generate content independently. Your ability to “talk” with AI determines the degree of control you have over the output — and whether you achieve your desired results or receive an incoherent unrecognizable mess. As with any other skill, improving your ability to communicate with AI requires exploration and practice.
Remember: Honing communication skills with AI, which includes text, voice and visual prompts, reduces the time required to receive desired and usable AI outputs.
AI efficiency cannot deliver results “yesterday.” The buzz is that AI will improve work efficiency and productivity, which may lead some to conclude that AI is the solution to the common demand of “we need it done by yesterday.” The truth is that AI can help designers and product developers speed up parts of the process, but the team will still need to determine which ideas are worth pursuing and then refine and tailor them to meet user needs and project goals. Furthermore, good design involves testing and iteration, which require time to complete.
Remember: AI can improve task efficiency, but product development is a nuanced process that requires critical thinking, careful consideration and time.
This article was originally published on delve.com. Visnu Fraenkel is a Former Senior Industrial Designer and Rahul Kamath is a Senior Design Researcher at Delve.
