As a consultancy that designs interactive systems for cultural institutions and public education, we have a particular responsibility to thoughtfully navigate this transition. Our position at the intersection of technology and creativity demands that we carefully balance innovation with ethical considerations. We must demonstrate how these powerful tools can be used responsibly while maintaining our commitment to human expertise, fair labor practices, and environmental stewardship.
We recognize that the rapid evolution of AI technology requires us to continually evaluate and adjust our approach. This living document serves as a record of our values, commitment, and progress in doing our part to empower our team members, respect creative rights, and minimize environmental impact. We will review this document annually, evaluating our progress towards these goals, and updating our commitments as both the technology and our understanding of its implications evolve.
Our Values
Human expertise and creativity drive our value. Our clients hire us for human judgment — research-grade methods, design expertise, and years of shipped public work. While AI tools can support our process, they can never replace the human insight and expertise that define our work. We commit to ensuring all creative and strategic work is fundamentally driven by our team’s expertise, using AI only as a supporting tool in our human-led process.
Tools should enhance employment, not threaten it. The value of our company lies in the expertise, creativity, and dedication of our team members. Artificial Intelligence tools represent an opportunity to make their work more meaningful, not to reduce our workforce. We commit to using new technologies to support and enhance existing roles, not to replace team members.
New tools are most valuable when they augment human processes. By automating repetitive tasks and reducing technical barriers, artificial intelligence tools can free our team members to focus on the creative and strategic work that drives real value for our clients. We commit to implementing new tools that empower our team members to work more effectively and creatively.
Quality assurance requires meaningful human oversight. While automated tools can accelerate our work, maintaining our high standards requires human judgment, expertise, and review. We commit to ensuring all automated work undergoes the same rigorous review and quality control processes as traditional work.
Professional skills must be actively maintained. The integration of AI tools should expand our capabilities without eroding our core professional competencies and expertise. We commit to dedicating time for traditional skill practice and development alongside AI tool training.
Ongoing Actions
This is a list of our ongoing actions; this list is reviewed and updated at the end of each calendar year.
New Actions
- (06/2025) We’ve done preliminary research on the environmental impact of using AI tools in our workflows. Surprisingly, the environmental impact is much smaller than we estimated, so it is no longer a primary concern — though we continue to monitor it. Our initial assessment is here.
Research Topics
This is a list of topics that we are actively researching, and hope to incorporate into our ongoing actions in the upcoming year.
- We are actively monitoring the environmental and social impact of large-scale AI deployment and plan to continuously assess how our use of these tools supports our other values. Our goal is to make informed decisions about which AI tools we use based not just on their technical capabilities, but on their alignment with our values regarding fair compensation, environmental stewardship, and ethical business practices.
- We are investigating how to properly measure the environmental impact of the AI tools we choose to use. This applies to both “direct” AI services (e.g. Claude, ChatGPT) as well as AI tools that are integrated into third-party tools.
- We are continuously assessing the business models and monetization strategies of AI tool providers, including how they source and compensate for training data.