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# Combining Game Design and Data Visualization to Inform Plastics Policy:
Fostering Collaboration between Science, Decision-Makers, and Artificial
Intelligence

A Samuel Pottinger  Eric and Wendy Schmidt Center for Data Science and
Environment, University of California Berkeley, Berkeley, CA, 94720, USA
0000-0002-0458-4985 Nivedita Biyani  Benioff Ocean Science Laboratory, Marine
Science Institute, University of California Santa Barbara, Santa Barbara, CA,
93106, USA  Bren School of Environmental Science and Management, University of
California Santa Barbara, Santa Barbara, CA, 93106, USA  Roland Geyer  Bren
School of Environmental Science and Management, University of California Santa
Barbara, Santa Barbara, CA, 93106, USA  0000-0001-7430-1058 Douglas J McCauley
Eric and Wendy Schmidt Center for Data Science and Environment, University of
California Berkeley, Berkeley, CA, 94720, USA  Benioff Ocean Science
Laboratory, Marine Science Institute, University of California Santa Barbara,
Santa Barbara, CA, 93106, USA  Ecology, Evolution, and Marine Biology
Department, University of California Santa Barbara, Santa Barbara, CA, 93106,
USA  Department of Environmental Science, Policy & Management, University of
California Berkeley, Berkeley CA, 94720, USA
https://orcid.org/0000-0002-8100-653X Magali de Bruyn  Eric and Wendy Schmidt
Center for Data Science and Environment, University of California Berkeley,
Berkeley, CA, 94720, USA  0009-0000-1609-6244 Molly R Morse  Benioff Ocean
Science Laboratory, Marine Science Institute, University of California Santa
Barbara, Santa Barbara, CA, 93106, USA  0000-0002-6961-6503 Neil Nathan
Benioff Ocean Science Laboratory, Marine Science Institute, University of
California Santa Barbara, Santa Barbara, CA, 93106, USA  0000-0003-3945-8484
Kevin Koy  Eric and Wendy Schmidt Center for Data Science and Environment,
University of California Berkeley, Berkeley, CA, 94720, USA
0000-0002-8479-4404 Ciera Martinez  Eric and Wendy Schmidt Center for Data
Science and Environment, University of California Berkeley, Berkeley, CA,
94720, USA  0000-0003-4296-998X

(Dec 18, 2023)

Abstract: This multi-disciplinary case study details how a public web
application combines information and game design to visualize effects of user-
defined policies intended to reduce plastic waste. Contextualizing this open
source software within a broader lineage of digital media research, this user
experience exploration outlines potential directions for facilitating
conversation between artificial intelligence, scientists, and decision makers
during an iterative policy building process. Furthermore, this system
dissection reveals how this interactive science effort considers the
practicalities of a treaty’s shifting priorities and proposals in its designs.
Specifically, this historically situated investigation of the tool’s approach
highlights options for centering human decision making where artificial
intelligence helps reason about interventions but does not prescribe them.
Finally, analysis summarizes this application’s specific game design-inspired
mechanics and their efforts to: enable users’ agency to explore solution
possibilities freely, invite deep engagement with scientific findings, and
simultaneously serve multiple audiences with divergent objectives and
expertise.

##  1 Introduction

In his influential “Humane Representation of Thought”, Bret Victor (2014)
explores digital media’s unique ability to “respond” to the user, detailing
how interactivity enables new ways of reasoning to unlock thoughts we
“couldn’t think” before. This paper explores one such visualization
application of these powerful design techniques: the open source global-
plastics-tool.org. Constructed by this article’s cross-disciplinary research
team, this public web application seeks to extend the reach of mathematical
modeling by offering iterative simulation of policy scenario effects,
attempting to improve usability of scientific insights for negotiators and
stakeholders engaging in the development of a “once-in-a-lifetime” global
treaty: the United Nation’s “International Legally Binding Instrument on
Plastic Pollution, Including in the Marine Environment” (Legaspi, 2023; UNEP,
2022, 2023b). However, during this decision support tool’s journey into global
negotiation, its designers encounter three central challenges:

  * •

Providing user agency to explore different policy scenarios freely.

  * •

Inviting diverse stakeholders to holistically consider model outputs through
sophisticated multi-variate displays.

  * •

Serving divergent audiences of varying prior levels of domain knowledge.

Detailing the design of this decision support tool and contextualizing its
place within a broader journey in science communication, this paper distills
how interactive visualization may address those policy engagement hurdles:

  * •

Hidden Hayashida Tutorials: A game design-inspired approach which embeds
narrative in structure and aims to orient users to a sophisticated interface
and complex topic while avoiding the “ludonarrative dissonance” that may arise
from a more traditional “tutorial” feature (Brown, 2015a; Hocking, 2007; JM8,
2023).

  * •

Connected Zelda Valleys: Applying “landmark” visualizations, this design seeks
to orient the user navigationally while also inviting explorations of data or
results across multiple views which limit the moment to moment complexity of
the interface (Brown, 2023a, 2023b; Brown, n.d.; Portnow, 2022).

  * •

Data Rumors: Unobtrusive design gestures towards additional optional content
which try to allow users to “read at multiple levels” of detail, promising to
support those seeking both in-depth knowledge and high level takeaways without
interrupting the regular interaction flow through the broader tool (Brown,
2017; Takahashi and Nelson, 2018; Victor, 2011).

  * •

Environmental Explanations: Using the structure of the visualization to
reflect the underlying AI, an activation of information architecture
attempting to afford model mechanics explanations (Brown, 2020; Carson, 2000;
Victor, 2011).

Furthermore, this cross-disciplinary case study more broadly discusses the
intersection between information and game design that underpins these
patterns.

###  1.1 Background

The recently released global-plastics-tool.org participates in a broader
intellectual conversation on the unique dialectic opportunities of digital
media.

Explorable explanations: Building on interactive communications research
reaching back to 1960’s PLATO (Bitzer et al., 1961), Bret Victor (2011) draws
attention to the possibilities of “explorable explanations” for “active”
reading. This user experience theory observes that static media cannot invite
response and, thus, leave “the reader’s line of thought” both “internal and
invisible” (Victor, 2011). In contrast, Victor (2011) observes that new
interactive technologies allow readers to “as[k] questions, conside[r]
alternatives, questio[n] assumptions, and even questio[n] the trustworthiness
of the author.” Since proposing these profound concepts, these design ideas
see a home in education, engineering, and industry (Bostock, 2023a;
Brusilovsky, 1994; Case et al., 2021; Hayes, 2023).

Scientific communications: However, years after their formulation, growth
opportunities still remain for using these “explorable explanations” in
science communication (Victor, 2011). Discussing interactivity for scientific
publications, Pierre Dragicevic et al. (2019) recently write that there remain
“very few concrete examples” that use these important ideas. Continuing to
speak in unresponsive media of papers and slides, unidirectional artifacts
convey scientific findings but cannot listen to stakeholders’ perspectives or
“respond” to their ideas (Victor, 2014). Digital but trapped in virtual pieces
of paper unable to “react” to users, this way of speaking forces audiences to
“blindly trust” and miss out on “the deep understanding that comes from
dialogue and exploration” (Victor, 2011).

Policy and science: With this historic communication challenge in mind, the
open source global-plastics-tool.org project considers how to interactively
engage with policy makers in finding science-informed solutions to pollution,
building an interface to artificial intelligence (AI) which predicts future
plastics volumes and flows under various scenarios. The media of communication
matters in these policy efforts because, as Jan Nolin (1999) remarks in her
analysis of the European Union’s engagement in the Kyoto Proposal, “scientific
work is usually slow while the pace of policy is erratic.” To understand why
legislation like the global plastics treaty sits within this fluid state,
consider the “processual” and “integrative” approaches in negotiation theory:
learning, information exchange, and collaboration happen across multiple
“phases” (Alfredson and Cungu, 2008). Therefore, the information needs of
stakeholders naturally adjust as perspective and context evolve or, as Nolin
(1999) writes, “scientific input to be effective must thus be timed for
readiness when a new phase of policy shifts in….” With these demands in mind,
communication of scientific findings may need interaction’s ability to “react”
and keep pace with shifting dialogue (Victor, 2012).

###  1.2 Related work

Though Dragicevic et al. (2019) observe that relatively few projects realize
the power of interactivity in scientific communication, some recent tools try
to enable this timely iterative information delivery to support policy design
through simulation. In environment and sustainability, notable examples
include:

  * •

Driving the Future: Simulation of automotive markets under different
incentive, tax, and policy scenarios (Keith et al., 2017).

  * •

En-ROADS: Interactive simulation for policy impact on greenhouse gas emissions
and global warming (Jean et al., 2018; Rooney-Varga et al., 2020).

  * •

Protect High Seas: Tool to identify potential marine protected area candidates
using configurable conservation plans (Visalli et al., 2020).

  * •

MSP Challenge: A multi-user environment for collaborative marine spatial
planning with simulation of policy effects (Abspoel et al., 2021).

Enabling dialectic design of science-informed solutions beyond what a print
out makes possible, all of these digital environments turn static information
into engaging software which allow users to bi-directionally converse with
data, creating “interactive papers” or “explorable explanations” that still
remain the minority in science (Dragicevic et al., 2019).

##  2 Challenges

This study builds on prior work’s foundation by further constructing
vocabulary to identify and address policy tool challenges. Specifically, we
explore hurdles for supporting treaty processes through the open source
global-plastics-tool.org which builds a user interface around machine
learning-based plastic modeling for international negotiation.

###  2.1 User agency

Policy makers need “agency” to explore questions from their own expertise and
in their own timeline, two crucial aspects not well supported by traditional
scientific communication.

Requirement for collaboration: Providing suggestions for engaging with policy
makers, the United Kingdom’s Chris Tyler (2013)111Former Director of the
Parliamentary Office of Science and Techology. warns that scientists “often
consider themselves as the ‘experts’ who engage with policy makers” but they
should not assume “that [they] are the only expert in the room.” Similarly,
Nolin’s (1999) experiences in the European Union echo these benefits of
bidirectional dialogue, highlighting the value of integrating science and
policy in advancing solutions. With this need for mutual collaboration in
mind, the medium of scientific communication may limit reader agency as static
documents “displa[y] the author’s argument, and nothing else” (Victor, 2011).
In this structural challenge, instruction benefits users and orients them to
scientific findings but also risks “lecturing at” decision-makers which
clashes with their need to provide input and inquiry via their perspective and
knowledge.

Requirement for timeliness: Both Nolin (1999) and Tyler (2013) note that
policy “decisions usually need to be made pretty quickly” with strong
constraints on timeline for additional research. Again, this reflects an
inherent limitation of static media on audience agency where readers can “form
questions, but can’t answer them” (Victor, 2011). To this end, Victor (2011)
questions how digital alternatives may respond to inquiry in the moment
itself, addressing concerns otherwise only “answered by a phone call or heavy
research.”

Together, these needs for timely collaboration challenge this scientific tool
to consider how interactivity can not only inform policy makers but work with
them to enable their own agency to answer questions freely in the moment as
new information becomes necessary.

###  2.2 High dimensional outputs

Visualization of highly multi-variate data encounter “visual perception and
cognition … limits on the number of variables that [can be] encode[d] in a
single graph” where even established patterns from information design for
addressing high dimensional complexity can sometimes require reader’s
“extensive study and practice” to use (Few, 2019). Worryingly, the simulation
of policy impacts requires exploring effects across many variables and thus
asks tool design to support comprehensive evaluation without becoming
overwhelming. This challenge of taming complexity asks the project how it may
adapt prior work using interactivity to teach sophisticated interfaces,
maintaining the richness of the data without becoming complicated (Berlow,
2010; Pottinger and Zarpellon, 2023).

###  2.3 Levels of speaking

The policy context of the tool’s usage demands it walk a tightrope in
supporting multiple levels of reading:

  * •

On one hand, recommendations to the scientific community on policy engagement
often emphasize the need for brief summaries in plain language (Hetherington
and Phillips, 2020).

  * •

Meanwhile, information designers warn that traditional media like slides cause
oversimplification and result in poor decision making (Tufte, 2006).

This web application steps into this tension: it must serve audiences of
diverse prior experience to support both the high level overviews recommended
to scientists in policy engagement while simultaneously inviting deeper
understanding of the details needed for effective decision making.

##  3 Design

This plastics policy tool looks to video games for answers to these three
central issues, building up a language of solutions to address this vocabulary
of challenges.

###  3.1 Role of game design

To solve for these three concerns, this policy tool observes that prior work
exploring interactivity looks to the overlap between information and game
design for inspiration:

  * •

Elijah Meeks (2018) provides an early “aspirational guide” which, in
particular, considers the analogies offered by the overall structure of games
to data visualization.

  * •

A Samuel Pottinger (2022) considers the opportunity for incorporating user
expertise in finding solutions in a form of “participatory” design.

  * •

A Samuel Pottinger and Giulia Zarpellon (2023) explore specific tutorial
techniques pioneered by games.

Therefore, we also turn to game design for advice in tackling these
aforementioned challenges, further understanding patterns like Hayashida-style
tutorials, connected levels, open worlds, environmental storytelling, and
side-quest rumors for data visualization.

###  3.2 Design for user agency

Interactive science products often require “sophistication to navigate” and
learning new concepts within a novel interface (Pottinger and Zarpellon,
2023). Of course, video games must also orient new players quickly and,
borrowing from that discipline, prior visualizations feature “Hayashida-style”
tutorials, leveraging a powerful pedagogical technique successfully used in
Nintendo’s work to similarly teach users about a new technical tool (Nutt and
Hayashida, 2012; Pottinger and Zarpellon, 2023). This simple process includes
four steps (Brown, 2015b):

  1. 1.

Introduction: Show the mechanic to the user.

  2. 2.

Development: Give players a simplified task to try the action.

  3. 3.

Twist: Highlight something unexpected about the skill.

  4. 4.

Conclusion: Challenge users to demonstrate mastery of the lesson.

That said, tools like Pyafscgap using this structure often lead through
written tutorials and example analyses where they highlight certain
prototypical observations (Pottinger and Zarpellon, 2023). This explicit
guiding of the user may detract from a sense of freedom or make the tool
appear non-objective, echoing earlier concerns about user agency and asking if
simulations can orient readers without “lecturing at” them.

This “ludonarrative dissonance” problem also appears in games which, as
detailed by Clint Hocking (2007) and refined by JM8 (2023), arises when a
mechanic used by a player feels out of place with the experience’s message or
narrative. In this case, a written introductory tutorial may contrast with the
intended message of providing user agency by:

  * •

Making users feel like novices even though the tool invites them to bring
their expertise to designing a solution.

  * •

Showing example insights, biasing self-directed exploration.

  * •

Forcing attention to specific policy aspects in a way that threatens a feeling
of the tool’s scientific neutrality.

Believing users should discover policy pros and cons instead of having
opinions prescribed, the tool therefore looks to games for possible solutions.
To that end, analysis of Nintendo’s 2017 action-adventure “The Legend of
Zelda: Breath of the Wild” by Cam Shea (2021) offers a possible “open world”
remedy: start journeys in beginning areas with reduced complexity not
identified as a tutorial but which still preamble the broader experience.

Figure 1: Hierarchy pulls the user through a Hayashida sequence.

With Zelda in mind, this interactive tool similarly “gates” details behind
exposure to the concepts required for the larger experience. Visual hierarchy
constructs a simplified “starting region” to introduce mechanics that blossom
in the “full” world in the details tab, reaching towards what designer Mark
Brown (2015a) calls making the tutorial an “invisible” feature.

###  3.3 Design for multi-variate evaluation

The subtle Hayashida sequence considers how to design policies but evaluating
their effects can span up to 90 views in the details tab. To balance rich
functionality with simplicity, the software’s design learns from video games’
separation of play into short term “primary loops” of moment to moment actions
and “secondary loops” of longer term objectives (Brown, n.d.).

Consider the loops of two genres adept at managing large amounts of content:

  * •

Games with connected stage designs like in Rare’s “Banjo-Tooie” allow actions
in one area to impact another even as it still separates content into discrete
levels. This creates a deep world in the secondary loop while building a
primary loop that naturally narrows the moment to moment available subset of
that complexity (Brown, 2023b).

  * •

Designer James Portnow (2022) observes that open world games advertise content
through “landmarks” which orient players without explicit instruction. As
analyzed by Brown (2023a), Zelda BoW achieves this by peeking tall secondary
loop landmarks over the world’s hilly terrain which hide primary loop
landmarks in distant areas.

The tool operates in a way similar to a valley seen in Zelda.

Figure 2: The details tab use “valleys” to structure primary and secondary
loops.

Though users can only take a limited number of actions at any time related to
their current view in the primary loop, the tool keeps secondary loop
landmarks (like other lifecycle stages or regions) visible “in the distance”
through small previews opening into those other spaces. These sight-lines try
to encourage exploration and pull users “over the hill” into a new valley.
Furthermore, like Banjo-Tooie, changes in one area reflect in others, creating
the potential for the user to traverse a vast possibility space without having
to grapple with it all at once. This attempts to construct a “vista” of
secondary loop elements alongside a smaller dynamic set of primary loop
opportunities (Majmudar, 2020).

###  3.4 Design for levels of speaking

Even if hidden tutorials and manipulated sightlines to landmarks introduce the
visualization tool’s mechanics and orient users in a complex multi-dimensional
data space, this sophisticated software still serves various audiences with
different objectives or, as Victor (2011) writes, explorable explanations
should consider how to empower users to “read at multiple levels” of depth.
Those knowledgeable of plastics concepts or only seeking high level takeaways
may engage with the tool superficially. Meanwhile, others may “read closely”
to learn unfamiliar terminology or consider expert details. If design must
support both altitudes of exploration simultaneously, how might video game
design help manage these parallel ways of speaking?

To build these multiple simultaneous levels of engagement, producer Rob Nelson
observes that a unique “ability that games have and other mediums don’t [is]
optional, additional narrative that you can choose to engage with or skip
over” (Takahashi and Nelson, 2018). In games:

  * •

Don Carson’s environmental storytelling unobtrusively layers content into
“setting” like graffiti or signage that the player encounters “along their
journey” if they are paying close attention, allowing the user to naturally
choose their preferred depth of engagement (Brown, 2020; Carson, 2000).

  * •

Rumors which are subtle mentions of “side-quests” afford unobtrusive opt-in:
invitations naturally missed by users who do not want that content or are busy
rushing to another objective (Brown, 2017).

These designs aim to support a deep path for those moving slowly and another
streamlined route for those moving quickly in which optional elements blend
into the background. Indeed, the tool’s interface prepares a similar two track
path by scattering tooltips next to keywords that “experienced” users would
recognize.

Figure 3: A tooltip describes a technical phrase and beacons deeper.

Low within the visual hierarchy, those in a rush can easily skip these
“rumors” even as they still direct close readers (Brown, 2017).

##  4 Implementation

Supporting these nuanced interaction-heavy mechanics from game design requires
careful front-end software engineering, influencing the architecture of the
code sitting around the software’s underlying AI. Therefore, to support
further practical consideration of these potential approaches, this multi-
disciplinary study next examines implementation strategies.

Note that this project targets the web browser for improved portability and
low friction access (AWS, n.d.).

###  4.1 Open source

The tool itself does not use a prebuilt user interface framework in order to
support some specific interaction patterns as discussed in the architecture
section below. That said, major open source technologies may still help
achieve these designs:

  * •

Visualization library D3.js for custom crafting of visual elements required to
build landmarks and exert careful control over visual hierarchy (Bostock,
2023b).

  * •

Popper and Tippy.js to support tooltips and rumors (Atomiks, 2017; Popper,
2021).

  * •

Tabby to structure the tabbed interface required by the Hayashida sequence
(Ferdinandi and Aukia, n.d.).

  * •

Simplebar for additional control over scrollbars to improve affordance of
scrolling necessary for slightline manipulation (Denat, 2023).

In general, this approach collects a series of smaller components in a custom
architecture the enables the design’s bespoke operation.

###  4.2 Architecture

To encourage separation of concerns while still supporting the tool’s specific
interaction patterns inspired by game design, this project generally uses a
model-view-presenter architecture with strong historic precedent (Osmani,
2023). However, the sophisticated web application decomposes the interface
into multiple presenters fitting into a general hierarchy where the bottom
controls individual views while higher level components increasingly focus on
coordination. Note that “facades” manage access to underlying data and
simulation mechanics that make up the analogized model component (Shvets,
n.d.).

Figure 4: Overview of presenter structure.

This structure reinterprets events as they move up and down the hierarchy to
ensure proper handling across different sections of the coordinated interface.
Achieving the connected level design of Banjo-Tooie, this architectural
approach specifically allows visualization code to span across multiple tabs
within the broader interface, keeping different sections of the software in
sync while still achieving separation of concerns and centering the same user-
designed policy scenario (Brown, 2023b).

###  4.3 Offline access

This design and architectural approach supporting these game-inspired
mechanics involves propagation of many events that could cause significant
network traffic. That in mind, practical advice from research team members
experienced in negotiation process emphasize that use of the tool in actual
treaty settings (including “side meetings”) cannot expect constant internet
connectivity. Therefore, this negotiation-focused project employs locally
installable progressive web applications which offer three options for offline
usage (MDN, 2023b).

  * •

Cache first: Always prioritizing cached content, this strategy only executes
network requests in the case of a cache miss.

  * •

Cache first with refresh: Always prioritizing cached content, this approach
still requests updated copies of resources after returning cached material to
the client.

  * •

Network first: This tactic always goes to the network but uses the cache as a
fall back if requests fail.

To prioritize positive experience during weak connectivity where requests may
still succeed slowly while still affording for somewhat frequent updates, this
software package elects for the cache first with refresh approach.

###  4.4 Domain-specific language

The sophisticated visualizations called for by these game-inspired designs
involves updating many coordinated complex components as users refine their
policy scenarios. A tool frequently used by games, this software turns to a
domain specific language or “DSL” to enable the project to “reduce the
communication costs” between collaborators in constructing this complex logic
(Strumenta, 2022; West, 2008). Also cutting down on development time, this
approach adds a custom runtime environment deployed in the browser and tied to
visualizations (Strumenta, 2022). Furthermore, this language includes specific
integration of certain keywords and operators for common plastic simulation
actions like calculating product lifecycle distributions and proportionally
distributing effects as part of simulation propagation. To that end, this tool
runs the open source ANTLR 4 technology in the browser to offer a custom
interpreter using a bespoke grammar as further discussed in the project
repository (Parr, 2023). Various open source ANTLR language implementations
provide precedent for this design (Everett, 2013; Kiers, 2020; Pottinger,
2023; Sturluson, 2019).

###  4.5 Other technologies

A number of libraries also enable the underlying advanced functionality
required for this tool’s interactivity within the browser:

  * •

Browser compatibility software es-module-shims and Polyfill.io (Bedford, 2021;
Champion, 2020).

  * •

Handlebars for client-side rendering of complex UI elements (Katz, 2019).

  * •

Papa Parse to request and process model outputs (Holt, 2015).

  * •

Version 1 of ua-parser to check browser compatibility (Salman, n.d.).

This software further uses additional open source technologies like Grunt and
QUnit (OpenJS, 2023a, 2023b). The project README provides full details on open
source technologies included, detailing other components beyond the scope of
this paper.

##  5 Usage

With design and implementation in place, discussion next turns to actual
practical usage of the tool. Due to the important constraints of the treaty
process itself, this section focuses on a specific set of quality assurance
and improvement observations.

###  5.1 Overview

So far, this public software primarily serves policy makers and other
organizations related to negotation for the United Nation’s “International
Legally Binding Instrument on Plastic Pollution, Including in the Marine
Environment” (UNEP, 2023b). Sharing directly with well over a dozen
delegations as well as other researchers and industry, tool engagements have
taken place during:

  * •

Second inter-sessional period: Outside official events in the time between the
negotiations in Paris and Nairobi, various meetings with officials from
different nations as well as a public webinar and news media coverage (Geyer
et al., 2023; Schlossberg, 2023).

  * •

Third negotiation committee: Though not officially part of proceedings, “side-
event” scientific sharing opportunities hosted jointly with other similar
organizations as well as various bilateral meetings, all taking place in
Nairobi itself during November 2023’s INC-3222United Nations Intergovernmental
Negotiating Committee in Nairobi (UNEP, 2023a)..

  * •

Third inter-sessional period: The current period (at time of writing) between
official negotiation committee meetings in which conversations continue with
individual delegations and other stakeholders.

Having peaked at just over 13,000 daily page views333These numbers do not
attempt to remove automated access by robots / crawlers and only includes
traffic to global-plastics-tool.org, excluding the general public site at
https://plasticstreaty.berkeley.edu. during November 2023 largely coinciding
with news coverage and attention on social media, application traffic
continues to see up to around 5,000 daily page loads (Benioff, 2023; Geyer et
al., 2023; Schlossberg, 2023). Indeed, the software remains accessible as the
treaty process is expected to continue into 2025 (UN, 2023). Finally, in
addition to this detailed tool focused on policy makers, the team also offers
a general audience version at https://plasticstreaty.berkeley.edu.

###  5.2 Evaluative constraints

To understand this case study’s decision to limit usage insights to this
single piece of software itself, consider that this policy tool operates in an
ongoing international process.

Negotiation and evaluation: Various approaches in negotiation theory focus on
the importance of exchanges and communication, a framing where intentional
information flow matters (Alfredson and Cungu, 2008). This complicates common
evaluative approaches as they may obtain data about an individual and their
insights within the context of the treaty, making them potentially “private
information” (NIH, n.d.). For example, visualization evaluations like Multi-
dimensional In-depth Long-term Case-studies (MILC) would involve the
disclosure of not just experiences of the tool but also example findings from
the data, perspective which may become crucial to negotiation where unintended
exposure of that information could cause harm (Shneiderman and Plaisant,
2006).

Prioritization of participation: Even if taking steps to ensure data safety,
consideration of the geopolitical context and desire to serve policy makers as
partners444This framing of partner is in contrast to considering policy makers
as research subjects. in this “once-in-a-lifetime” treaty process leads this
tool building effort to forgo collection of information about individuals and
to avoid research on their treaty insights (Legaspi, 2023). Respecting these
practical needs for elevated privacy both enables this interactive science
project to participate in this multi-national process and offers a public
scientific resource to the community addressing a “worsening global crisis”
(WWF, n.d.). Indeed, doing so answers a growing call to go beyond the paper
and “blend research and engagement” to “respond rapidly to real-world events
and public demand” (Swain, 2023). However, this pragmatic stance also prevents
this case study from providing findings from controlled experiments or diary
studies, asking it to instead focus on “quality assurance” and “quality
improvement” tasks where information is only collected on the software itself
(CPHS, n.d.).

Limitations: As this research team turns to careful reflection on the tool
itself instead of conducting research about users and their insights, this
paper offers caution regarding important limitations on its usage
observations. Notably, these narrower results do not seek to provide
“generalizable knowledge” about user populations such as negotiators, a larger
and separate task potentially possible through later human subjects research
(CPHS, n.d.).

###  5.3 Observations

Despite these constraints on formal evaluation, reflection on tool engagement
during this time still offers some perspective on its practical use and
mechanics.

Policy selection: Though specific policy designs remain subject to change
throughout the aforementioned multiple rounds of “exchanges” during the fluid
nature of negotiation, the political process itself often offers guidance as
to the general families of policies under consideration (Alfredson and Cungu,
2008). For example, the so called “zero draft” put out by the United Nations
itself may offer perspective where “the text is guided, as per the mandate
received from the committee, by the views expressed at the committee’s first
and second sessions” (UNEP, 2023b). In addition to direct user feedback, these
articulations of collective perspective may offer guidance to interactive
science projects like global-plastics-tool.org with regards to which high
level “policy levers” to emphasize in the user interface.

Role of facilitator: Though user-guided exploration remains the goal, the
tool’s sessions quickly adopted the En-ROADS approach where workshops or
presentations using the software feature a “facilitator” who first introduces
the motivations and science behind the tool, offering an invitation on behalf
of the tool for policy makers to engage with the results through their own
inquiry (Jones et al., 2022). As discussed below, continued use of this
precedent from the prior literature in the future may offer an “ice-breaking”
for the interactive science product to enter into productive collaborative
discussion.

Non-linearity: While this interactive tool appears to successfully execute the
design’s intended primary loop where the simulation software sparks
conversations about incremental edits that drive forward the larger secondary
loop of comparing different policy scenarios, this hidden tutorial may also
unexpectedly repeat (Brown, n.d.). Though designers imagine a progression from
overview to details tab as users become more experienced, the tool’s current
structure instead may appear to encourage a cycle:

  * •

Start on the overview tab to discuss a policy at high level.

  * •

Go to the details tab when hitting a deeper question.

  * •

Return to the overview tab to chart out next topics.

This may suggest that the visualization platform in its current form uses its
sequence both to tutorialize mechanics as well as policies themselves.

Multiple play styles: While the tool sparks multiple rounds of inquiry which
feature expected policy refinement loops, sometimes the software also sees its
sessions stay within the overview tab. In consideration of the existing tool’s
current design, this may indicate additional affordance to the details tab
could help spur users to deeper understanding. However, a games lens offers an
alternative explanation. Prior work suggests that different segments of
audiences often naturally form divergent but successful “play styles” and, for
this tool, this theory could suggest that one such mode of engagement may only
require the high level overview to provide insight (Stewart, 2011). Indeed,
the tool often only navigates to the details tab in response to a deeper
question. Therefore, this “play styles” hypothesis may further suggest that
the overview tab serves higher level thinking through surveying major ideas
and that the conclusion of the Hayashida sequence only becomes necessary for
users encountering deeper inquiry. Furthermore, this may provide another form
of multiple levels of reading suggested by Victor (2011).

Scientist usage: The tool also unexpectedly benefits the science itself:
helping its own authors evolve the AI models by showing data in more holistic
views that highlight unexpected implications or behaviors. Though not
required, the tool frequently explores different model outputs in service of
the research team itself, revealing new insights or searching for
implementation issues which would cause unexpected policy effects.

Model transparency: Using interactivity to answer questions which seek to
understand something unexpected or interesting hinted at in its landmarks, the
tool appears to spur discussion using its small contextual charts, potentially
suggesting those design features’ anticipated use in facilitating navigation
and provoking follow up inquiry that pulls to adjacent views. That being said,
the same mechanics also appear to unexpectedly offer the software a method of
model explainability. In response to modeling questions, the details tab
itself outlines the variables included and incidentally addresses if
simulation incorporates certain dynamics. In fulfillment of Victor’s (2011)
expectations for explorable explanations, the system and financial parameter
panels in particular document underlying assumptions of the simulation and
invite users to understand the impact of changing those variables. Put another
way, the tool may sometimes respond to questions using its “rumor” tooltips
but other times use a form of environmental storytelling: the concepts simply
listed on the details tab itself convey model architecture (Brown, 2017,
2020).

Progressive web application: With research team members having gone physically
to INC-3, the tool sees frequent offline use, possibly providing the
anticipated valuable flexibility where, due to the practicalities of that
complex event, ongoing connectivity proves difficult as activities move
between various venues.

##  6 Discussion

With these reflections in mind, this study contextualizes this open source
tool, understanding opportunities for further study and potential additional
connections to other concepts.

###  6.1 Overview of design patterns

To improve utility of discussion, this case study summarizes and names the
designs that it considers:

  * •

Hidden Hayashida Tutorials: Building on prior work in both data visualization
and game design, the use of visual hierarchy to embed the four step Hayashida
sequence into the architecture of a data visualization to construct an
“invisible” tutorial (Brown, 2015a; Nutt and Hayashida, 2012; Pottinger and
Zarpellon, 2023). This structural narrative approach promises to orient users
while avoiding the ludonarrative dissonance that an explicit guide may
generate (Hocking, 2007; JM8, 2023). This tool’s two tab connected layout
attempts to embody this possible instructional pattern.

  * •

Connected Zelda Valleys: Bringing the concept of “primary” and “secondary
loop” gameplay to data visualization, the combination of open world and
connected level designs deploys small “landmark” visualizations which both
attempt to orient the player navigationally and invite deeper exploration of
alternative perspectives into data or results (Brown, 2023a, 2023b; Brown,
n.d.). Building this “geography” into visualizations aims for sophisticated
tools to tame their complexity by subsetting the actions available to the user
at any single moment, hoping to maintain interface simplicity (Portnow, 2022).
This tool’s summary charts surrounding the timeseries display seeks to
demonstrate this potential navigational method.

  * •

Data Rumors: Creating small “side-quests” within a visualization, the use of
subtle hints towards additional optional content seeks to allow users to “read
at multiple levels” without interrupting the regular interaction flow through
the broader tool (Brown, 2017; Takahashi and Nelson, 2018; Victor, 2011). This
project’s tooltips attempt to address this exploration opportunity.

  * •

Environmental Explanations: Mirroring the structure of the model into the
structure of the visualization affords model mechanics explanations and tries
to enable readers to “play with the premise and assumptions of various claims”
(Victor, 2011). The details tab and, in particular, the assumptions drawers
try to embody this context setting approach.

Given this vocabulary, this study encourages future researchers to consider
these design concepts for further exploration.

###  6.2 Permission to play

The potential usefulness for a facilitator to open meetings may reflect what
Andrew Walsh (2019) calls a need for “permission to play” in tool sessions.
This may suggest that traditional context of communication sets expectations
regarding unidirectional sharing that the tool may break. That said, future
work could better understand these potential underlying sociological barriers
and how design itself may serve to similarly offer this permission without a
team member present.

###  6.3 Backtracking

Cycling between the overview and details tab may indicate the unexpected
emergence of “backtracking behavior” often seen in open world and
“Metroidvania” games (Brown, 2018). This pattern has players take new skills
or knowledge to revisit prior content and, while this can recontextualize
earlier experiences with new understanding and deeper meaning, poor design can
also cause backtracking to become tedious repetition (Brown, 2023b). Later
work may further expand this study’s design language to understand how
intentional management of this behavior can reinforce insight and engagement.

###  6.4 Inquiry-based design

With the tool seeing questions naturally pull users to the deeper parts of the
interface, this open world design visualization approach may spark the
“inquiry-based” learning suggested by Nicolette Hayes (2023). This may
indicate the educational visualizations outside policy can benefit from
similar analogies to video game design.

###  6.5 Model explanation algorithms

Though not the central focus of this tool, the potential utility of this
software to explain model structure may suggest that visualizations trying to
offer “model explainability” might consider including similar game design
techniques to those explored here alongside algorithms like Local
Interpretable Model Explanations (Ribeiro et al., 2016).

###  6.6 Role of AI

This tool could try to use multi-variate optimization to propose solutions to
users, offering its own “policy answer” alongside user-generated suggestions
(Blank and Deb, 2020). However, using the video games lens, doing so could
create ludonarrative dissonance. As an extension of the projects’s existing
modeling, this hypothetical feature would see the software claiming to invite
outside expertise and exploration (with AI as a “helper” not a “driver”) while
simultaneously offering a mechanic providing “optimized” solutions.

In this case of interacting with actual policy negotiation, this project
intentionally excludes this AI-driven auto-optimization option despite access
to the machinery required. Again, policy makers offer expertise necessary for
finding good solutions (Tyler, 2013). In this framing, visualization and game
design allow that knowledge to participate in co-creation of solutions,
potentially reaching beyond the limits of blind mathematical optimization.

Nevertheless, future work may consider if different design contexts could
benefit from this kind of AI-generated solution or may offer studies on
evolving policy maker perceptions of these algorithmic designs.

###  6.7 Future human subjects research

This case study considers quality assurance and improvement activity for a
single tool, providing information about only this software and only one case
of these potential design patterns. That said, while this simulation currently
remains constrained by the nature of ongoing treaty processes and a desire to
avoid collecting information about individuals within this sensitive context,
later research could seek generalizable knowledge through human subjects
research approaches like MILC which may be more appropriate outside active
negotiation (Shneiderman and Plaisant, 2006).

Still, in imagining future research, this effort cautions that this
interactive science tool does not serve the general public and instead focuses
on active and often knowledgeable treaty participants (Tyler, 2013).
Therefore, it remains possible that this unique target audience may engage
with this tool with specific “play styles” different than other users
(Stewart, 2011). Indeed, the formulation of MILC responds to this situated
nature of data visualization where evaluation cannot consider just any user
but a specific population where professional objectives and background mediate
their experience of a technology (Shneiderman and Plaisant, 2006).

In short, later research hoping to build generalizable knowledge should ensure
study takes place in-situ. To that end, this study also recognizes a potential
opportunity for additional methods formulation for this kind of active policy
negotiation context.

###  6.8 Technical measures for privacy

To further this effort’s ethical stance regarding the avoidance of collecting
information about policy makers and their insights within the sensitive
context of treaty negotiation, the decision support web application itself
takes a number of privacy-preserving technical steps:

  * •

Providing a single page application where computation runs client-side so that
navigation between elements does not generate network requests that may reveal
intentions or activity, a privacy-preserving practice paired with also
avoiding use of technologies like “beacons” which would reveal the questions
being explored or results being considered by a user (MDN, 2023a).

  * •

Though not intentionally requesting information about users, adopting HTTPS to
avoid malicious manipulation or traffic interception (Basques, 2015).

  * •

Disabling or curtailing certain web provider defaults for logging analysis, in
particular strictly limiting use of IP addresses to only what is required for
basic operation including traffic routing, security, abuse prevention, and
reliability (Bruno, 2022).

  * •

Providing an offline version also allows users to leverage the application
with intentionally disabled network connectivity which may further help avoid
generating web traffic.

Future work in the policy space should also consider the privacy aspects of
not just research methods but implementation.

###  6.9 Use of a DSL

The domain specific language displaces earlier prototypes written either in
the R or Python programming languages. Teammates observe that migration both:

  * •

Improves readability of code through integration of domain specific keywords
(JetBrains, n.d.).

  * •

Reduces the length of scripts by removing “boilerplate” code (O’Sullivan,
2018).

Indeed, code for interventions in the DSL achieves sufficient brevity that the
visualization tool displays this logic within the interface and even allows
users to modify that code in their local copy of the live application.

This in-situ programming capability deserves additional discussion in that it
creates what Maggie Appleton (2022) calls a “Programming Portal” feature. This
further realizes conception of explorable explanations by Victor (2011) in
that it allows “the reader to play with the author’s assumptions and analyses,
and see the consquences.” Furthermore, this paper observes that the game
design and development communities also find similar benefits both from
incorporation of DSLs and this “hot reload” ability to change the programming
behind the experience in-situ (West, 2008; Zylinski, 2023).

This live development capability serves not just users but the developers of
the tool as well. In practice, most of the tool’s current policy options were
created from within the tool itself by using the web application as the first
development environment with the ability to see how new logic interacts with
the model outputs in real time without the delay of a “compile” step, a
pattern embodied in the “prototype” drawer in the details tab. Returning to
requirements identified by Nolin (1999) for timeliness, this approach may
offer agility in keeping pace with policy conversation.

###  6.10 Mediation

By allowing changing of systems and financial assumptions, this tool answers
the call made by Victor (2011) for explorable explanations to allow the
questioning of modeling. That in mind, this software focuses on media for
“active reading” and iterative policy design in service of providing
actionable scientific information to decision-makers, considering how policy
makers may question the tool and bring forward scientific perspective during
negotiation (Victor, 2011). Note, however, that this dialectic experience
executes within existing treaty process and does not consider how interactive
software may mediate or alter that process itself. Even though tools to help
in discussion and resolution of disagreements between stakeholders represents
a different goal than this projects’ intention potentially beyond what it
could practically consider in the context of this specific treaty opportunity,
this possibility of mediated disagreement resolution remains a possible area
for future research.

##  7 Conclusion

When Bret Victor (2012) implores audiences to “stop drawing dead fish” he
challenges them to consider the fundamentally responsive nature of interactive
tools: digital fish should react to users. Where the rigidity of static media
limit their mutual embrace, this project suggests that interactivity
facilitates the union of science and policy. Adding to the early discourse
between video game and information design, this tool’s analogies offer not
just an open source exemplar but also help to identify a language for building
these dialectic experiences in policy contexts.

In facilitating this human-machine conversation, consider a concept from Jesse
Schell (2019) central to the game design at the heart of the tool: experiences
are co-created by game and player. In that spirit, these cross-disciplinary
methods aim to create a balanced conversation in the space between AI,
scientist, and decision-maker. For that, these approaches may reach beyond
policy to other collaborative design contexts, reasserting the importance of
human input even in a world further saturated with AI. This gestures to an
exciting promise, a future in which computation does not displace experience
but instead where both add to each other.

The global plastics policy simulation tool is open source at global-plastics-
tool.org and is public for further use in the plastics treaty negotiations
currently underway. To that end, this project notably limits scope to
permissively licensed technologies to leave its own flexible Berkeley Standard
Distribution open source license unencumbered by proprietary closed-source
components (OSI, n.d.). Finally, a scrolling storytelling experience for the
general public to complement the detailed interface is also publicly available
at https://plasticstreaty.berkeley.edu.

##  8 Acknowledgements

Funding from:

  * •

Eric and Wendy Schmidt Center for Data Science and Environment at the
University of California Berkeley.

  * •

Benioff Ocean Science Laboratory at the University of California Santa
Barbara.

Project code is released under the permissive Berkeley Standard Distribution
open source license and invites community contributions which are also
provided under the same BSD terms (OSI, n.d.).

Reflecting the tool’s full credits page at https://global-plastics-
tool.org/#about-people at time of writing, the tool’s team also acknowledges
and thanks Elijah Baker for policy research, Carl Boettiger for early project
advice, Kelly Wang for communications, Linda Nakasone for reporting some bugs
(open source community process), and Thought Lab for development of the
general public page at https://plasticstreaty.berkeley.edu/ which complements
the tool. Furthermore, this paper acknowledges and thanks:

  * •

Color Brewer for color schemes (Brewer et al., 2013).

  * •

draw.io tools for diagramming (Diagrams.net, 2023).

  * •

All open source libraries in the project README at
https://github.com/SchmidtDSE/plastics-prototype.

  * •

Pandoc for markdown to latex conversion (MacFarlane, 2022).

  * •

The “Sage Harvard” CSL file (CSL, 2022).

Note that, for transparency, the tool also maintains a formal version-
controlled and standards-compliant “humans.txt” (https://global-plastics-
tool.org/humans.txt) with comprehensive and detailed individual credits for
the entire project which is current at time of this paper’s submission
(Bernabeu et al., 2012). Finally, thank you to policy makers who have used and
considered the tool.

##  9 Conflicts of interest

We do not have any conflicts to disclose.

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