INFCON 2024 has evolved from a developer-centric conference to a more inclusive IT event. With the addition of designer sessions for the first time this year, the fusion of technology and design garnered new attention. AI-related sessions, in particular, gained unexpected popularity among designers, offering a unique opportunity to explore the intersection of AI and UX design in a technology-focused environment. Contrary to the initial concerns of keynote speakers, designer participants showed high levels of engagement and enthusiasm, eagerly seeking deeper knowledge.
This article examines the insights gained from the key AI-related sessions at INFCON 2024 and explores practical methods that can be applied to real design workflows, focusing on initial concept development, UX research and usability testing, and user experience-centered problem-solving approaches.
Introduction to INFCON
INFCON is a leading IT conference in Korea, hosted annually by Inflearn, the country’s largest IT education platform. The 2024 event, held on August 2nd at COEX in Seoul, marked its third iteration, continuing the tradition of selecting participants through a lottery system. This method aims to provide fair participation opportunities for IT professionals from diverse backgrounds. This year, about 10,000 people pre-registered, but only around 2,000 were given the chance to attend, resulting in a high competition ratio of 8:1.
The conference featured 48 sessions, offering content for a wide range of specialists including developers, product designers, data scientists, and PM/POs. Keynote speakers from major IT companies such as Toss Payments, LINE, Woowa Brothers, Grab, Socar, and Musinsa shared valuable insights into current trends and innovations. INFCON’s accessible ticket pricing (₩44,000, with a discounted rate of ₩22,000 for Inflearn course participants) encouraged participation from a broad spectrum of IT professionals, from newcomers to experts.
Practical Applications from INFCON 2024 Keynotes
Designers at the product design and PM/PO sessions responded enthusiastically to the AI-focused keynotes. Among the standout presentations, Joo Hyung Park and DY Lee from Grab introduced Klever, an AI-powered tool for instant usability testing. Yeonseo Kim from Socar showcased how balancing AI with a user-centered approach can enhance both efficiency and user experience. Finally, Juhye Shin demonstrated the integration of ChatGPT into the design process, boosting efficiency from idea generation to data analysis.
AI-Powered Usability Testing
Revolutionizing UX Research Grab’s product designers Joo Hyung Park and DY Lee presented a fresh approach to UX research using AI technology. In their keynote “Designer’s Experiment in the AI Era,” they introduced Klever, a Figma plugin that utilizes GPT-4’s vision API to perform instant usability testing on designs. This tool simulates user interactions with UI designs using AI agents and quickly generates usability reports. Park and Lee have made this project open-source, encouraging collaboration within the design community.
Key Takeaway : AI can significantly speed up the feedback loop in UX design, allowing for rapid iterations and improvements from the earliest stages of the design process.
AI-Enhanced User-Centric Problem Solving
Balancing Efficiency and Experience Yeonseo Kim, Head of the Data Group at Socar, presented a compelling case study on their AI-based car wash system. Her keynote, “Is Operational Efficiency Achievable with AI and Data?,” showcased how AI can be leveraged within a user-centered framework to enhance both operational efficiency and user experience. The system employs AI for photo analysis to assess ‘contamination’ and considers weather conditions, but the key challenge was objectifying the subjective concept of ‘cleanliness’. This was resolved through a user-centric approach, analyzing expert opinions, customer feedback, and sample photos to train the AI model effectively.
Key Takeaway : Successful AI implementation in UX design requires balancing technological capabilities with user needs and perceptions. By combining AI’s analytical power with user-centered methodologies, designers can create solutions that are both efficient and aligned with user expectations.
AI as a Design Partner
Juhye Shin, Master of SELFISH CLUB, presented “From Data to Hands-On Application: Practical Use of ChatGPT in Real Work,” focusing on the practical integration of AI tools, particularly ChatGPT, into product development and design processes. Shin outlined methods for using AI in initial idea generation, hypothesis development, and creating taxonomies from user flows.
Key Takeaway : AI tools like ChatGPT can be effectively incorporated into various stages of the UX design process, from ideation to data analysis, offering new perspectives and enhancing efficiency.
Next Steps: Integrate AI into Your UX Design Workflow
INFCON 2024 highlighted how AI and UX design are coming together, prompting designers to rethink their traditional workflows. Now, it’s time to turn this shift into actionable steps. These strategies provide a way for UX designers to use AI to create more intuitive and user-focused designs. By following these steps, designers can find new opportunities in the midst of change.
- Experiment with AI-Powered Usability Testing
Integrate Klever or similar AI-powered tools into your design process. Start with small projects to familiarize yourself with the AI’s capabilities in usability testing. Use these tools to quickly generate initial usability reports and iterate on your designs based on AI-generated insights. - Implement User-Centric AI Solutions
When developing AI-enhanced features, prioritize user needs and perceptions. Collect and analyze user feedback, expert opinions, and sample data to train your AI models effectively. Focus on objectifying subjective concepts (like Socar’s ‘cleanliness’ challenge) by combining AI analysis with user-centered methodologies. - Enhance Ideation with AI
Use ChatGPT for initial concept development. Apply the STIC (Situation, Task, Intent, Concern) framework when formulating prompts. Request 15+ responses from ChatGPT, then dive deeper into specific ideas that align with your project goals. This approach can help generate diverse perspectives and uncover unexpected solutions. - Streamline User Research with AI
Leverage AI tools like ChatGPT to develop hypotheses after AI-assisted user interviews. Use AI to create taxonomies from user flows, helping to systematize complex user experiences. Experiment with using AI to generate and evaluate A/B test scenarios before implementation, potentially saving time and resources in the research phase.
