Design processes involve exploration, iteration, and movement across interconnected stages such as persona creation, problem framing, solution ideation, and prototyping. However, time and resource constraints often hinder designers from exploring broadly, collecting feedback, and revisiting earlier assumptions-making it difficult to uphold core design principles in practice. To better understand these challenges, we conducted a formative study with 15 participants-comprised of UX practitioners, students, and instructors. Based on the findings, we developed StoryEnsemble, a tool that integrates AI into a node-link interface and leverages forward and backward propagation to support dynamic exploration and iteration across the design process. A user study with 10 participants showed that StoryEnsemble enables rapid, multi-directional iteration and flexible navigation across design stages. This work advances our understanding of how AI can foster more iterative design practices by introducing novel interactions that make exploration and iteration more fluid, accessible, and engaging.

Generative AI faces many challenges when entering the product design workflow, such as interface usability and interaction patterns. Therefore, based on design thinking and design process, we developed the DesignGPT multi-agent collaboration framework, which uses artificial intelligence agents to simulate the roles of different positions in the design company and allows human designers to collaborate with them in natural language. Experimental results show that compared with separate AI tools, DesignGPT improves the performance of designers, highlighting the potential of applying multi-agent systems that integrate design domain knowledge to product scheme design.

This paper explores the potential for utilizing generative AI models in group-focused co-creative frameworks to enhance problem solving and ideation in business innovation and co-creation contexts, and proposes a novel prompting technique for conversational generative AI agents which employ methods inspired by traditional 'human-to-human' facilitation and instruction to enable active contribution to Design Thinking, a co-creative framework. Through experiments using this prompting technique, we gather evidence that conversational generative transformers (i.e. ChatGPT) have the capability to contribute context-specific, useful, and creative input into Design Thinking activities. We also discuss the potential benefits, limitations, and risks associated with using generative AI models in co-creative ideation and provide recommendations for future research.

AI technologies like ChatGPT are necessitating a fundamental overhaul of our educational systems and institutions. Getting the right answers to predetermined tests is no longer sufficient in an age where AI can access, integrate, and recite knowledge billions if not trillions of times faster than the human mind. So, what are the skills, capabilities, and experiences that our students and citizens will need to prosper in an age where personal and professional success will be based on the application, not the memorization and regurgitation, of knowledge? Let's continue that conversation here in Part II to define the requirements for humans to excel in creating organizational and societal value in a world dominated by AI and Big Data. Many organizations engage in a "wear'em down" decision-making process when dealing with wicked hard challenges with multiple opposing views.

As the world continues to grapple with the impact of both artificial intelligence & the global pandemic, it's essential to consider the future of work. What will the workplace look like, & how will people adapt? Calling all designers, UX researchers, PMs, & architects in NYC! Join us for an exciting evening of discussion & exploration, meet like-minded individuals, & learn from Ate Atema, owner of Atema Architecture, & Suzanne Li, Director of Product Design at Newstand, during an intimate fireside chat! More about speakers: Ate is a visionary architect passionate about creating sustainable spaces. He has designed offices for TED, Endeavor Global, & The Nature Conservancy NY.

The Artificial Intelligence revolution is here. That might sound like hyperbole. After all, the world looks the same. The revolution didn't arrive with Skynet and robots or with Blade Running cyborgs. A small chat at the bottom right hand corner. If you're imagining Siri or Alexa or even Clippy (Rest in Peace, Clippy), it's so much more than that.

For anyone doubting that AI is here, the New York Times recently reported that Carnegie Mellon University plans to create a research center that focuses on the ethics of artificial intelligence. Harvard Business Review started laying the foundation for what it means for management, and CNBC started analyzing promising AI stocks. I made the relatively optimistic case that design in the short term is safe from AI because good design demands creative and social intelligence. But this short-term positive outlook did not alleviate all of my concerns. This year, my daughter started college, pursuing a degree in interaction design.

The future of work is changing our views of jobs for the future. The rapid advancement in AI, ML, automation and algorithmic approach is going to make most of the traditional jobs obsolete. According to a research by the World Economic Forum, approximately 65 percent of today's schoolchildren will end up working in occupations that do not yet exist. The majority of work currently dotting the back-office job landscape will cease to exist in the near future. The emergence of the creator economy and remote working has almost transformed the established paradigms in which people used to work and collaborate.

I am a "hollow vessel waiting to be filled with insights" [5]. I had one simple goal but no objective to achieve: attempt to study BlenderBot 3, Meta's "improved" artificial intelligence (AI) chatbot [7][9], inside its personalized context by interviewing it. I have no intention of learning about its pain points. None of the elements of body language come to play since such an endeavor is impossible. Having worked with many large language models (LLM) in my time, I have personally seen how they could potentially turn into raucous ideological donnybrooks [11].

"Courage is not the absence of fear, but rather the judgment that something else is more important than fear. The brave may not live forever, but the cautious do not live at all" – Philippe Renaldi, The Princess Diaries (2001) Yes, it is always easier to apply advanced technologies such as Big Data, AI / ML, and Edge Analytics to optimize an existing process. But what if that process is out-of-date, or worse yet, wrong. Is your organization applying AI / ML to accelerate your organization's race to irrelevance? Here is a damning example of what can go wrong when an organization focuses on optimizing an existing flawed process.