Stanford CS547 HCI Seminar | Autumn 2025 | What Is a (Future) Designer?

Key Concepts

• Generative AI: AI models capable of creating new content, such as images, text, or designs.
• Morphing Matter: Materials and structures that can change shape or form.
• Sustainable Design: Designing products and processes with environmental responsibility in mind.
• X across X: A framework for designers to work across disciplines, scales, and mindsets.
• Co-design with AI: A collaborative approach where designers and AI work together to create solutions.
• Digital Twin: A virtual replica of a physical object or system.
• 4D Printing: 3D printing that incorporates a fourth dimension, time, allowing printed objects to change shape over time.
• Data-Driven Design: Utilizing data to inform and optimize design processes.

The Evolving Role of Designers in the Age of AI

The speaker, with a background in industrial and interaction design, and now practicing engineering design at UC Berkeley, reflects on the profound impact of generative AI on the design field. The advent of AI's capability to design for function, structure, and performative materials has led to an "anxious aha moment" for designers, questioning their relevance and the future of their education. The talk proposes a re-evaluation of the designer's role, emphasizing environmental responsibility, interdisciplinary collaboration, and co-design with AI.

1. The Unhealthy Planet and Environmental Responsibility in Design

A significant challenge for future designers is the "unhealthy planet." The speaker highlights the inherent contradiction in design's role in producing artifacts that often contribute to waste. The traditional nature-centered and human-centered design approaches are not always aligned. The speaker's lab is exploring how to integrate sustainability into their work, particularly with "morphing matter."

• Sustainable Morphing Matter: This involves designing reconfigurable, shape-changing smart materials and structures with sustainable principles or that contribute to sustainable applications.
• Review Paper: A recently published review paper by the lab breaks down sustainability considerations across manufacturing, transportation, use, and end-of-life phases for robots and smart devices.

Case Study: Morphing Food for Sustainable Packaging

A concrete example of this principle is the exploration of "morphing food," specifically pasta, to address plastic waste from food packaging.

• Problem: Food packaging, especially for commodities like pasta, is a major source of plastic waste. Standard pasta packaging uses significant space for air.
• Solution: Developing flat-packable pasta that can be manufactured and packed flat, saving plastic and space. Upon boiling, the pasta transforms into desired 3D shapes.
• Examples: The video showcases flat-packable pasta transforming into saddle, helix, and canoli shapes when cooked.
• Motivation: The shape of pasta is crucial for pairing with different sauces, leading to hundreds of pasta shapes. This project aims to retain the consumer experience of shaped pasta while enabling efficient flat packaging.
• Mechanism: The morphing behavior is achieved by introducing micro-grooves on one side of the pasta sheet. These grooves tune the swelling rate and ratio during cooking, causing the pasta to bend. The chemical reaction of starch swelling and breaking down into sticky amulose also fixes the transformed shape.
• Scientific Fascination: This phenomenon involves complex non-linear soft matter science, requiring collaboration with computational mechanics experts for simulation.
• Fabrication: Customized robotic arms with stamping systems are used to create specific groove patterns.
• User Study: A user study indicated that consumers were not highly sensitive to the sub-millimeter micro-grooves, and ingredient quality remained a primary factor in taste.
• Applications: Beyond saving packaging and storage space, the flat-packable pasta has potential applications for hikers and space travel, where packaging space is critical. A brief conversation with NASA explored its use for astronauts.

2. X Across X: Breaking Boundaries in Design

The second point emphasizes the need for designers to operate "X across X," meaning working across disciplines, scales, and mindsets.

Case Study: Self-Burying Seed Carriers for Reforestation

This project, inspired by the self-burying behavior of the Erodium seed, aims to revolutionize reforestation efforts.

• Inspiration: The Erodium seed's coiled body uncoils in response to rain, driving rotation and burying the seed into the ground for self-propagation.
• Engineering Equivalent: An artificial version was created using chemically processed thin wood veneer that mimics this self-burying phenomenon when exposed to rain.
• Reforestation Application: The larger vision is to use drones to deploy these carriers containing tree seeds. Upon rain, the seeds self-bury, increasing germination rates compared to current methods.
• Problem with Current Methods:
  • Manual Planting: Slow, expensive, and potentially dangerous.
  • Drone Broadcasting: Seeds land on the surface, vulnerable to harsh environments (sun, birds), leading to low germination rates.
• Pilot Tests:
  • Early tests in Pittsburgh with a rudimentary drone and deployment mechanism showed successful seed burial after rain.
  • More advanced field tests in Berkeley forests with tree seeds (e.g., Douglas fir) have yielded promising germination rates (around 60% in earlier tests, with improved results in newer tests).
  • Tests are also being conducted in arid regions of Asia for planting grass species.
• Nature Publication: The project was featured on the cover of Nature, highlighting its inspiration from nature, use of natural materials, and contribution back to nature.
• Peripheral Applications:
  • IoT Devices: The seed carriers could be developed into interconnected IoT devices for environmental monitoring, changing color based on soil pH or acting as biodegradable antennas for wireless communication.
  • Space Exploration: European and Korean space agencies have investigated similar environmentally triggered passive robots for soil monitoring and exploration in outer space, suggesting potential for moisture-driven or thermal fluctuation-powered devices.
• X Across X in Practice:
  • Materials Across Scale: Designing at the centimeter scale of the carrier, understanding material properties at the mesoscale (fiber alignment), and manipulating microfiber angles at the microscale.
  • Approaches Across Disciplines: Engineering design, analytical modeling, plant science (seed interaction with the pod), robotics (drone deployment and path planning), and computer science.
  • Methods Across Fields: Analyzing fiber orientations and hygroscopic phenomena (biological science), chemical processing of wood (chemistry), and finite element analysis for morphing behavior (computational science).
• AI's Role: The speaker posits that "X across X" is challenging for AI because it requires creative knitting of disciplines in ways not yet seen by AI.

3. Co-design with AI: Embracing and Collaborating

Designers must embrace AI and engage in co-design.

Case Study: Volumetric Morphable Matter and AI-Driven Design

This project aims to design fully volumetric morphable matter capable of arbitrary shapes and local motion.

• Hardware Infrastructure: A trust structure where each beam is a pneumatic actuator, allowing for multi-degree-of-freedom control.
• Examples: Cute lobster robots carrying boxes, jumping foxes, and turtles.
• Design Space: The large design space (hundreds of controllable beams, shape, and control policies) is too complex for human designers alone.
• AI Collaboration:
  • Genetic Algorithm: Used to optimize actuator contraction timing and levels, as well as channel grouping.
  • Channel Clustering: AI helps group pneumatic channels, reducing the number of external tubings (e.g., the turtle is controlled by four tubings).
  • Task Specification: Designers can specify tasks (e.g., a robotic furniture that lowers its height, turns, carries a cup, or moves to turn off a light), and AI figures out control policies and channel grouping.
• Future Vision:
  • Morphable Furniture: Beds that can move patients, or furniture that transforms for mixed reality/VR experiences (e.g., a bottle transforming into a banana with adjustable weight and center of gravity).
  • Transformable Backpacks: Backpacks that can turn into wings, requiring shape-changing and weight shifting capabilities.
• Limitations: Manufacturing capabilities are a current limitation, though advanced 3D printing may enable complex meshes.

4. Operating Between the Virtual and the Physical World

Designers must be "dual citizens," operating in both computational and physical realms.

• Smart Material Self-Folding: A smart material that self-folds into a target shape (e.g., a rose flower) when heated.
• Fabrication vs. Computation: This involves physical fabrication experiments and computational understanding to predict transformations.
• Digital Twin: Most projects involve a digital twin behind the physical artifact.
• 4D Printing: Designing flat shapes that self-fold into complex forms (like a rose flower) to save printing time, support materials, packaging, and transportation space.
• Mechanism: Utilizes the shape memory properties of PLA filament printed on a non-shrinkable TPU substrate. Heating causes the PLA to shrink, inducing bending.
• Computational Design: Designing arbitrary origami shapes by calculating bending angles and converting them into G-code for flat printing.
• Applications:
  • Furniture: Flat-packable furniture that self-assembles on-site.
  • Large Constructs: Morphing larger structures like houses or wind turbines, potentially triggered by concentrated solar energy on-site.

5. Breaking Boundaries and Extending to Art

Designers must break boundaries, extending their work to art and other fields.

Case Study: Bacteria-Actuated Smart Garments

This project explores using genetically modified bacteria for smart materials.

• Nano-Actuator: Bacillus subtilis bacteria, with high energy density and moisture sensitivity, were cultivated and placed on fabric.
• Smart Garment: The fabric responds to skin conditions, opening scales when the body is hot and sweaty, and closing when cool.
• Collaborations:
  • New Balance: Developed a morphable shoe that glows in the dark.
  • Centre Pompidou: Created an art installation showcasing the morphable and glowing bacteria.
• Designer's Role: Designers can bridge nanoscience, biological science, and genetic engineering, collaborating with artists and exhibiting in art contexts to broaden vision and create meaningful products.

6. Data as a Material for Designers

Data is becoming a fundamental material for all designers, regardless of their focus.

• Relevance: Data is crucial for computational design, but also for industrial design and physical products.
• Data Sources: User studies, product evaluations, physical characterizations, fabrication machine data, and printing parameters.
• Applications: Optimizing design processes, speeding up simulations, and enabling AI to generate designs.

Conclusion: Redefining Design in the AI Era

The speaker concludes by addressing the anxious question of whether designers will become obsolete. The answer lies in asking "radically different questions," paving "unprecedented paths," and redefining design. While AI learns from existing knowledge, designers can create breakthroughs by generating new knowledge and asking novel questions. The definition of design is expanding to include areas like drug design, exoskeletons, and hybrid artificial/natural constructs. The democratizing nature of technology offers exciting possibilities for creative pursuits.

The discussion also touches upon the challenges and necessary changes in design education, emphasizing the need for interdisciplinary programs, breaking down silos, and fostering a mindset of continuous learning and experimentation, particularly within lab environments. The importance of empowering designers to lead scientific and engineering collaborations is also highlighted. The evolution of design tools, moving from simulation to inverse design and leveraging large language models, is seen as crucial for facilitating these new approaches.