For the last 30 years or so, our digital lives have been shaped by an app-centric paradigm, where specialized software applications have acted as the gatekeepers to specific tasks, media types, and workflows. With AI, this app-centric approach is giving way to an artifact-centric model—one that places media and its transformations at the center of the experience.
The dinosaurs amongst us have seen this before, in Unix.
The second Rise of Artifacts
When we talk about “artifacts” in this context, we mean the fundamental building blocks of human experience: media such as text, images, videos, audio. These media types form the core of how humans interact with the world, constrained by the five senses—sight, hearing, touch, taste, and smell. The number of these artifacts are finite. While their combinations and uses may be limitless, the foundational categories themselves are grounded in human perception.
There are a handful of levels of abstractions or let’s say simplified maps that derive from these fundamental media types. Popular amongst them are tables or diagrams. More specific subcategories of sounds such as speech or music. And this can go on forever. However, it is important to recognize that an 80/20 effect plays out here where a handful of artifact types cover most of communication and transformation that is relevant to human needs.
Why AI Makes Artifact-Centric Computing Possible
With AI’s ability to process, and transform media on the fly, the need for rigid, app-centric silos is diminishing. Complex transformations that once required specialized tools and expertise can now be executed with relative ease.
The Unix philosophy: “Do one thing and do it well.” Unix systems were built around tools that operated on text, each designed for a specific purpose but capable of being combined in endless ways. While the Unix model was limited to text as the primary media type, it laid the groundwork for a modular approach to computing, , and the most fluent people were able to seamlessly blend a dozen tools quickly to achieve almost any desired transformation. Watching them work felt like magic. But now, AI can automatically combine the modules. Moreover, we are no longer limited to text or simple player.
The Role of Collaboration and Embedded Computing
Another critical shift in this new paradigm is the elevation of collaboration to a first-class feature. In the app-centric model, collaboration often felt like an afterthought, bolted onto systems designed for individual use. The artifact-centric model, by contrast, assumes that artifacts will be created, transformed, and shared by groups in real-time. This is where AI-powered tools truly shine, enabling seamless collaboration that transcends the limitations of traditional apps.
Moreover, as computing becomes increasingly embedded in our physical environment, We can have overlays of different maps or levels of representation of the most relevant features in our environment, whether the observer be a human or an agent acting on behalf of a human.
The Dual Purpose of Computers: Problem-Solving and Creativity
At its core, computing serves two primary purposes:
- Preserving and solving problems related to human life
- Enabling creative expression that resonates with others
- The first purpose is well-understood and deeply ingrained in fields like science, engineering, and logistics. Computers create maps, traverse networks, and solve abstract problems with unparalleled precision.
The second purpose, however, is harder to quantify but no less vital. It involves using computers to create artifacts that inspire, inform, or connect with other humans. Whether it’s composing music, designing visuals, or crafting narratives, creative expression is fundamentally about artifact creation and transformation. The shift to artifact-centric computing recognizes the universality of this activity across all domains, from the humanities to the sciences.
A New Era of Artifact Transformation
As we transition from app-centric to artifact-centric computing, the implications are profound. This new model frees us from the silos of specialized applications and opens up a world where media and its transformations are fluid, dynamic, and collaborative. It redefines the role of computers, embedding them seamlessly into our environments and making them extensions of our creative and problem-solving capabilities.
In this future, artifacts—text, images, video, audio, and more—will no longer be constrained by the limitations of apps. Instead, they will become the foundation of a new computing paradigm, powered by AI and designed for collaboration, creativity, and the preservation of human life.