Technology and Narrative Lab
Examining Applications and Implications of Emerging Technology
Just as technology advancements continue to increase in size and scope, so do their impact on society. But many policymaking processes and analytic approaches remain rooted in outmoded 20th century models and capabilities.
In Pardee RAND's Tech and Narrative Lab (TNL), policy analysts can apply new and emerging technologies to study policy problems and create novel policy solutions, as well as understand the policy implications of new and emerging technologies.
TNL embodies a philosophy of curiosity and experimentation within the broad context of policy analysis and action.
The lab will focus initially on three categories of technology:
- Artificial Intelligence (AI) and Machine Learning (ML)
- Virtual, Augmented, and Mixed Reality (VAMR), and
- the Internet of Things (IoT)
But the TNL is more than just a place. It embodies a philosophy of curiosity and experimentation within the broad context of policy analysis and action. The TNL will serve as a “home base" for students and researchers interested in technology issues as well as connective tissue between the graduate school, RAND research, and external collaborators, including academia, government, and the private sector. The TNL is all about hands-on work, collaboration, and exploration, and will employ the best practices of technology start-ups — rapid prototyping, developing a "minimum viable product," and iterating.
However, the lab is not only about widgets and algorithms, but also about story—how to convey process and results to non-technical audiences.
What does narrative have to do with technology? Plenty. Over the last few decades, we have seen a migration from hardcopy to digital infrastructure. Data and access to it has become ubiquitous. We have also seen the emergence of three new mediums for communication and collaboration - the internet, mobile devices, and immersive technology (VAMR). These tech capabilities will touch every aspect of life, but they also serve as platforms for interaction, education, and influence.
Photo by Diane Baldwin/RAND Corporation
We live in a complex world. Analysis of its policy challenges is a complicated undertaking. And conveying rigorous, data-driven research results can be quite challenging. The once gold standard of dense, lengthy written reports has eroded over time, so new ways of understanding problems and explaining solutions need to be explored, prototyped, and executed. The TNL embraces the challenge of turning policy analysts into effective storytellers, helping to ensure that research results do not fall on deaf ears.
Why Pardee RAND?
Pardee RAND is uniquely positioned to lead explorations at the intersections of policy and technology. The rich history of RAND research, along with the broad expertise in analytic approaches, provides a foundation of rigor for policy analysis. Strategic partnerships with technologists and storytellers provide new ways to frame questions, test approaches, and share results.
The TNL focuses on all aspects of technology. From creating tools for data capture and analysis to understanding how and why emerging capabilities will impact society, the TNL is a space for asking questions both big and small, and prototyping solutions.
Frequently Asked Questions
- What is the relationship between the coursework and the TNL? How does it fit with the larger Ph.D. requirements?
- What is meant by "development and application" in the TNL?
- What are activities that the TNL does? What are its "products"?
- What are topics it will cover? What resources does it provide?
- Why Tech and Narrative Lab? Why not just a Tech Lab?
- How will this work help train me for my future career? What kinds of jobs would I do?
- What are the requirements for participating in the TNL? What kind of skills are helpful?
What is the relationship between the coursework and the TNL? How does it fit with the larger Ph.D. requirements?
The TNL serves as a place for experimentation and prototyping. For instance, some technology may be highlighted in a class, with the TNL then providing a space to "play" with the capability.
Students can explore applications and/or implications for policy, either within the context of that course or more broadly. In addition, tangible outcomes from the work in the TNL — be they hardware, software, or narrative — provide a portfolio that augments the transcript of coursework and the dissertation. Some of these portfolio artifacts likely will find their way into dissertation research.
What is meant by "development and application" in the TNL?
The TNL is about doing — coding, hacking, prototyping. It also is about sharing the work, both process and results, with others.
In addition to the technology-focused work, concepts around visualization, narrative, and engagement with others will be explored. If a student creates something new, part of the goal is to also experiment with how that tool or methodology is shared, and to explore ways to better tell the story of the work and results.
What are activities that the TNL does? What are its "products?"
Photo by Diane Baldwin/RAND Corporation
The lab is about trying, sharing, failing, and growing. The products are varied — algorithms, applications (software and hardware), visualizations, narrative treatments, and other artifacts.
The goal of the TNL is to provide a safe space for experimentation, allowing students (and researchers) to ask, “what if…” and “why not…” questions outside of traditional coursework or RAND research projects.
What are topics it will cover? What resources does it provide?
As noted above, the three initial areas of focus are Artificial Intelligence (AI) and Machine Learning (ML); Virtual, Augmented, and Mixed Reality (VAMR); and the Internet of Things (IoT). These are broad areas, and workshop topics touch a variety of themes and possible applications, as well as overlaps.
These areas will expand and change as the technology landscape moves. Our goal is always to have at least some of the work focused on future capabilities, not just current tech. Being able to have students explore is a key goal for the TNL.
Why Tech and Narrative Lab? Why not just a Tech Lab?
Photo by Diane Baldwin/RAND Corporation
Communication is a difficult skill to master, particularly when the topics are complex, and the approaches used to understand the material are rigorous and often dense. The ability to frame questions and perform analysis is necessary but not sufficient for being an effective researcher and/or leader.
Being able to "tell the story" of the work, including what, how, and why things were done, is key to engaging target audiences and is required to effect change. The best work in the world is largely useless unless others can understand the relevance and importance.
Since technology is providing new mediums for communication and collaboration, folding narrative approaches into the work of the lab is both appropriate and mission-critical.
How will this work help train me for my future career? What kinds of jobs would I do?
Future careers will likely involve two main factors: the need to learn new things, and the likely role of technology, either as a tool or as an implication. The TNL is all about curiosity and exploration and serves as a place to be constantly learning new things and thinking deeply about how technology affects policy and society.
A graduate could end up in a variety of places after graduation. She could work for an innovative startup, have a technology leadership role in government, be a policy expert within a large technology company, or lead non-profit or NGO efforts. The TNL portfolio provides future employers concrete examples of both rigorous thought and vigorous execution.
The ability to frame questions and rapidly prototype solutions—both to understand the problems better and to scratch at the solutions—will be valuable to a wide variety of organizations.
What are the requirements for participating in the TNL? What kind of skills are helpful?
Above all else, the main requirement is curiosity and a desire to learn, play, experiment, fail, and try again.