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AI in Product Design: Potential, Pitfalls and the Promise of Creativity

Written by Keeghan McGarry (CTO) on 08/08/2023

Artificial Intelligence (AI) has grown to encompass a vast array of functionalities, and its applications are limited only by our imagination. While most people tend to be captivated by the glitz and glamour of shiny new tools like ChatGPT, a Large Language Model (LLM) which falls under the wider AI category of Natural Language Processing (NLP), the true power of AI lies in its myriad forms.

Let's dig a bit deeper.

Expansive Reach of AI

AI is more than just Natural Language Processing. It includes things like machine learning, expert systems, computer vision, and much more. Many applications of machine learning, for instance, have revolutionized data analysis, enabling deeper insights into user data and helping product owners pinpoint and understand issues early on. Data is potent, but deciphering it is complex. Here, AI and machine learning step in, transforming raw data into comprehensible, actionable insights.

Proddr, on the other hand, is an AI-driven platform that uses an LLM to generate feedback and questions around user ideas and stakeholder feedback, helping to preempt potential issues and enhance creative thought processes.

The Real Role of AI

Contrary to popular belief, my opinion is that AI is not designed to create. Instead, it enhances, serving as an extension of human creativity. By providing prompts, probing, and questioning, AI should foster humans' creative thoughts without making assumptions or outright decisions. I touched on the ethical impact this way of looking at AI has in my blog post here.

Imagine a scenario where you have a vast dataset of user interaction metrics and analytics at your disposal. Pair together an AI tool capable of understanding your new ideas and features, and one which understands that vast data set, and you can hone in on those ideas that will actually create an impact. Over time, the AI tool can improve its accuracy by learning from the actual outcomes.

There are also examples of tools which utilise AI to improve time management. One such tool Motion uses AI to manage your calendar, meetings, to-do list etc to increase efficiency. If we applied the same idea to product roadmaps and were able automatically to update deadlines, dependencies etc we could see a huge increase in our workplace efficiency.

AI in Action: Pitfalls, Possibilities, and the Path Ahead

Implementing AI into your workflow is more accessible and advantageous than you might think. Proddr is a prime example of this in action. Leveraged daily by numerous professionals (including myself - shocker!), Proddr brings out the best in teams and is refreshingly easy to use. Just run your brief through Proddr as an initial step to integrating AI into your operations.

Despite its transformative potential, it's crucial to remember that AI is not without its blind spots. While AI can be a powerful assistive tool, it should never be treated as a crutch. Verifying and adjusting AI outputs remains an essential practice, emphasizing the fact that AI, despite its advanced capabilities, is not infallible. It should be seen not as a silver bullet, but as another vital tool in your tool belt, requiring careful application and continuous refinement.

Looking ahead, I think the future of AI seems bright and filled with even wider integration possibilities. Where generative functions similar to Photoshop's AI Fill tool could potentially find their way into design platforms like Figma, to analytical tools which would offer automated suggestions for identified pain points, AI is on track to drive efficiency across industries.

As we continue to embrace AI's capabilities, we must also be mindful of the responsibility that comes with it, ensuring we make the most out of this powerful ally in our data-driven world.

Responsibility and AI

Even with its transformative potential, I see AI as a tool. Just like any tool, its use comes with a certain level of responsibility. I believe this responsibility extends to everyone involved, not just the designers and operators of AI systems, but also us end-users. After all, the direction and behaviour of AI tools are driven by the data we feed into them, and our actions play a critical role in mitigating bias and maintaining privacy.

To use AI responsibly, I find it essential to demand transparency. I need to know how my data is being used, the thought process behind AI's decisions, and any potential risks involved. I've found that transparency cultivates trust, making me feel safe and confident while interacting with AI.

Moreover, I am of the strong opinion that continuous monitoring and auditing of AI systems is necessary to detect and correct any bias, privacy breaches, or other ethical issues that might arise. This involves a commitment to constant learning and improvement, keeping up with the ever-changing landscape of AI.

In conclusion, I see the real promise of AI in its ability to support human creativity and improve decision-making, making it a formidable ally in our data-driven world. But like any tool, it is only as good as the person who uses it. That's why I believe understanding AI and using it effectively is the key to unlocking its full potential.

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