In the ever-evolving landscape of design, innovation means adapting. There are risks of widespread AI, and you can feel it amongst the worldwide design community, but there are also lots of opportunities. There will never be a true understanding of the value of design (and designers) unless we continue to push the boundaries of thinking, seeking new avenues to create (a rare power we possess). One of the most promising frontiers in this quest for innovation is the integration of generative artificial intelligence (AI) tools into our design processes.

Generative AI, a branch of artificial intelligence that enables machines to generate new content, presents a transformative opportunity for designers. By leveraging algorithms and vast datasets, these tools can swiftly generate countless iterations of design concepts, providing fresh perspectives and insights that might otherwise remain undiscovered. I like to think of it like putting 500 sketches on the wall in minutes. It won't replace human touch and human discernment, but it can drastically speed up and narrow us in.

Some Generative AI tools available, that I've used:

1. RunwayML: RunwayML is basic, but user-friendly and includes a style transfer and text-to-image generation.

2. GANpaint Studio: Developed by MIT, GANpaint harnesses the power of Generative Adversarial Networks (GANs) to manipulate and edit images. Designers can use this tool to alter specific features of their designs, explore alternative color schemes, or even generate entirely new concepts based on existing ones.

3. Artbreeder: a unique approach to generative design, allowing users to blend and cross-pollinate different images to create entirely novel compositions. By combining elements from disparate sources, designers can uncover unexpected aesthetic possibilities and refine their design concepts iteratively.

4. DeepDream: Originally developed by Google, DeepDream gets funky with surreal and dreamlike takes, exploring the intersection of technology and imagination in innovative ways.

5. OpenAI's DALL-E: One of the most widely used, this model from OpenAI, generates images from textual prompts.

6. Midjourney: one of hte most popular, this model exists on Discord. One of my favorite aspects of this is being able to look at other peoples' prompts and outputs (helping me learn how to prompt engineer successfully; and sometimes inspiration comes from the wildest places).
   
   Others to check out: Huggingface, Fast.ai.

Generative AI can unlock a multitude of benefits:

1. Suprise! aka "happy accidents" — again, inspiration comes from everywhere.

2. Efficient Iteration: Generative AI can expedite the iteration process, to rapidly produce ideas that can then be identified as the most promising concepts (by humans, hopefully).

3. Data-Driven Insights: By analyzing the output generated by AI models, designers gain valuable insights into emerging trends, consumer preferences, and aesthetic sensibilities, enabling them to make informed design decisions. This testing element I'll be writing about in the future.

4. Collaborative Innovation: Fostering a culture of collaboration, designers can use customer groups own language and references as prompts, creating a shared connection to research insight.

5. Sustainable: the goal is to get to meaningful outcomes faster, with less physical waste, and more thinking. Literally this saves paper, materials, and time.

In conclusion, the integration of generative AI tools represents a paradigm shift in the field of design, offering unparalleled opportunities for innovation and creativity— if we choose to embrace it and leverage it! Embracing technological advances wholeheartedly will help designers survive, common to the common news reel— but we must establish it as a tool for humans, rather than a blanket solution.

The Hadron collider is just metal if people don't know how to use it.

Below are some Gen AI images used to come up with a hockey team's mascot and logo, the Sunday Scaries—final jerseys shown on the team (bottom).