If we want tech, and the products, services, and systems its intertwined with, to represent all of us, to work for all of us, it must be designed by all of us. Our goal is to provide radical access to emerging technologies like artificial intelligence and blockchain. We want people of all ages, races, professions, and genders to be able to use tech as a medium in their work.

• How do we give people an embodied understanding of emerging technologies?

• Is it possible to create analog learning experiences that affect the design of technology?

• What tools will empower anyone to experiment with technologies the same way that they currently experiment with using different materials for mocking up products, different layouts for visual design, or different schematics for systems design?

This ongoing initiative won a Core77 Design Award this year! To date, it consists of two introductory learning experiences: (1) Designing with Machine Learning, and (2) Designing with Blockchain. Several tools are used within these learning experiences, and also stand alone. These include the I Love Algorithms Card Deck, Algorithm ‘Mad Libs’ and Data Sourcing worksheets, the This is Design Work and Map the Problem Space frameworks, and the My First Blockchain workbook.

There exist a number of new technologist-created tools that allow people to use and attempt to ‘see inside’ certain algorithms and models. But most are still highly technical, requiring prior coding knowledge. We approached this project as designers that make things in many analog mediums. Our first experiments were with our community of 90-ish design instructors, and we’ve iterated through a range of audiences: K12 educators, middle and high school students, highly technical and non-technical Stanford students, educators and students from other universities around the world, and the general public. Along the way, we’ve shared our work publicly, and incorporated feedback from computer scientists and others.

PEOPLE WE’RE REACHING

Since launching our first prototype workshops in September, 2018, we’ve run more than 1500 people, ages 11-80+ through learning experiences, both on campus and beyond. We know Stanford is a place of privilege, and made moves to remove barriers to attendance to on-campus events. In an effort to maximize access, we covered the cost of parking and local transport at our free public workshops if needed.

FEEDBACK SURPRISES

When we started this project, our hypothesis was that it would be most impactful for those that were tech novices. This happened, but we’ve been surprised by the reaction from technology experts. Having the tools to prototype the implications of their work seems to resonate. This quote from a recent participant, a CS graduate student, sums it up well: “I used to think machine learning was easy, now I think that applying it effectively is like rocket science.”

MOVING FORWARD

In the year ahead we’ll focus on adapting and diffusing our tools to new audiences, and building new tools in new mediums. Together with our d.school teammates in K12 and beyond, our goal is to build the prototyping cart of the future–full of analog ways to prototype with a new class of mediums for design.