Enshittification

Artist’s Statement:

Through this digital game, we are representing the enshittification ecosystem. Enshittification is the gradual degradation of an online platform, driven primarily by profit-maximization motives at the expense of user experience. It is characterized by a predictable cycle where a platform initially optimizes for users, then shifts to benefit third parties (advertisers, sellers), and finally prioritizes profits for itself, leading to an overall decline in utility and reputation.

Our goal is to help players understand how enshittification operates by placing them in the role of a CEO managing a social media platform. Players must make critical decisions about algorithm design, ad personalization, and ad frequency to maximize revenue. These choices impact key factors such as user numbers, engagement, reputation, and costs, demonstrating the delicate balance of growth, profit, and user satisfaction.

To enrich the experience, the game incorporates real-world-inspired events like acquisitions, legal challenges, and competition, reflecting the complexities faced by platform leaders. By navigating these scenarios, players will gain insight into the trade-offs inherent in the enshittification cycle and the broader implications of prioritizing profit over users. This interactive approach makes the abstract concept more tangible and engaging.

Final concept map:
Here is the final concept map of the system. It is a simplified version of the entire enshittification system designed to help translate the abstract concept into something tangible for players to understand. 

Playtests and History Versions of the game

Version 1: 8th November 2024

Initially, we had a paper version of the game which relied on die rolls to determine how ad frequency and personalization would change and its effects on revenue. At this point, we did not have a full system built out and we were comparing this with the system of college admissions to decide on which system to focus on. We ran paper versions of both games with playtesters in class and came to realize that enshittification was an interesting system to represent through a game. 

Here is a picture of the paper versions of the games and an initial mind map for the enshittification game:

After deciding upon the system we wanted to teach via a game, we built out the initial formulas on excel before translating it into a digital game. 

Here is a screenshot of the work we did on excel and then translating it into code:

This work led to the second version of the game.

Version 2: 11 November 2024

Here is a screenshot of the game when Christina was testing it

As you can see from the screenshot, the things the player has control over are Ad Frequency, Ad Personalization, and Algorithm upgrades. 

We tested this game in class with Christina who is the professor of the class in addition to being an author and speaker. Here is a screenshot of while Christina was playing the game:

The following is the feedback we received:

1. Controls

• Observation: Christina was unclear on how to start playing the game and the controls available for the player and their purpose. This led to the player feeling unsure on how they can use the controls effectively. After a couple of minutes of discovering, when Christina understood the tools, she made the comment that “Now that I understand the tools, I am interested”
• Feedback:
  • Suggestion that was shared by Christina: Add a tutorial or on-screen guidance to clarify controls and their impact. In addition, make it clear what the goal of the game is. 

2. Game Mechanics

• Observation: The player felt “doomed” when money turned negative, leading to a less enjoyable experience. The player felt like they could not make it back to being profitable and they didn’t have any choice on how to recover.
• Feedback:
  • The consequences of negative money create frustration rather than challenge.
  • Suggestion: Introduce mechanics to recover from negative money (e.g., loans, events to earn quick cash (investments/raising money)) or soften penalties.

3. Event Design

• Observation: The game feels like it could benefit from more dynamic events.
• Feedback:
  • The player suggested adding events to increase engagement and variety.
  • Suggestion: Implement random or player-driven events to introduce new opportunities and challenges. Christina in particular mentioned several times that having a button that helped to raise funds/ increase revenue would have been helpful. 

4. Decision-Making Clarity

• Observation: The player was confused about the meaning of certain terms e.g Yield, Gross etc and lacked the necessary information to make decisions.
• Feedback:
  • Terms and their implications are unclear (e.g., outcomes of choices, meaning of words).
  • Suggestion: Provide clearer explanations for game terminology and offer decision-making hints or previews of potential outcomes.

5. Fun Factor

• Observation: The player was unsure how to make the game more enjoyable.
• Feedback:
  • The lack of clarity and frustration with mechanics reduce fun.
  • Suggestion: Focus on balancing challenge and reward, introducing surprise elements, and ensuring the player has enough agency to feel in control (This was primarily because after revenue went negative the player was not able to do much).

Using this feedback, we came up with the following changes to be made to the game:

 

• Revisit the formulas to ensure that revenue doesn’t drop as quickly as it did so that the player doesn’t lose agency
• Introduce a tutorial or just a guide on what the controls of the game are
• Introduce external scenarios/events to bring in more of the fun element to the game

Version 3: 13 November 2024

For this version of the game, we added a little description of how to use the tools of the game. 

We tested this with a female Stanford student who is an undergraduate student and also in the class. The following is a picture of her playing the game:

Here is the main observation and feedback for this particular playtest:

 

1. Fun Factor

• Observation: Playtester largely ignored the reputation scores, suggesting that the mechanic felt disconnected or lacked visible impact on gameplay.
• Feedback:
  • Terms and their implications are unclear (e.g., outcomes of choices, meaning of words).
  • Suggestion: Add a dynamic social media feed to reflect the consequences of player actions in real-time.
    • Example: Show posts, comments, or headlines reacting to player decisions and reputation changes.
  • Highlight how reputation scores influence gameplay, such as unlocking new options, triggering events, or affecting other game elements.

Given that the player didn’t pay attention to the reputation score, we gave it more thought on whether it was really needed in the game and be visible to the player. After some thought, it was clear that reputation is perceived and not necessarily a thing the player will keep a constant eye on. Therefore, it is still used in calculation of other factors but we decided to not have it be visible to the players. 

Version 4: 20 November 2024

With this version of the game, we tested it with 3 different players. They are all Stanford students. The following are the changes that were made before testing it with these players:

 

• Added some external scenarios that players had to make decisions on to make it more interesting
• Fixed all the math to ensure that the system replicates the real world situation of enshittification. 
• Got rid of the reputation score that was initially visible to players

All three playtesters are Stanford graduate students. The following are pictures from the playtests:

Here is a summary of the observations and feedback we got from these players:

1. Event and Scenario Visibility

• Observation: Events and scenarios were often missed due to poor visibility or placement.
• Feedback: Scenarios and events were not prominent, leading to reduced interaction and impact.
• Suggestions:
  • Pause the game and display events/scenarios prominently in the center of the screen.
  • Use visual effects (e.g., flashing borders, animations) or audio cues to draw attention.
  • Move scenarios to a fixed, prominent location and avoid requiring scrolling.
  • Increase font size and improve contrast to enhance readability.

2. Onboarding and Rules Clarity

• Observation: Players struggled with understanding gameplay mechanics, variables, and objectives.
• Feedback: Lack of upfront guidance and clear onboarding reduced engagement and created confusion.
• Suggestions:
  • Add an introductory screen or tutorial explaining:
    • Gameplay mechanics.
    • Controllable variables and their significance.
    • Winning conditions or endgame criteria.
    • Scenario frequency and impact.
  • Provide tooltips or hover-over explanations for variables and actions.
  • Replace the title “Enshittification” with a contextualized name to provide immediate context.

3. Gameplay Experience and Pacing

• Observation: Early gameplay was perceived as slow and disengaging, with scenarios appearing too frequently later on.
• Feedback: Players wanted a quicker hook and a better balance in scenario pacing.
• Suggestions:
  • Introduce engaging events or choices earlier in the game to captivate players.
  • Adjust scenario timing to allow more breathing room between events.
  • Use a countdown or visual indicator to signal when the next scenario will appear.

4. Variable Comprehension and Revenue Mechanics

• Observation: Players had difficulty understanding variables, their relationships, and why certain outcomes (e.g., halted revenue growth) occurred.
• Feedback: Lack of feedback and explanations for variable interactions reduced clarity.
• Suggestions:
  • Add tooltips or notifications explaining the relationships between variables (e.g., revenue, user numbers, overhead costs).
  • Provide feedback when key mechanics (e.g., revenue growth) are impacted, explaining the reasons.

5. Technical Issues: “NaN” Bug

• Observation: The balance value displayed “NaN” due to calculation errors, disrupting gameplay.
• Feedback: The bug undermined gameplay and caused confusion.
• Suggestions:
  • Investigate and resolve the “NaN” bug, ensuring edge cases are handled.
  • Implement error-checking logic with fallback values or clear error messages.

6. Endgame and Purpose

• Observation: Players felt the lack of an endpoint made the game less purposeful.
• Feedback: The absence of a clear goal reduced the sense of accomplishment or closure.
• Suggestions:
  • Define a clear ending point or goal (e.g., achieving a target revenue or navigating the platform to a specific milestone).
  • Add a summary screen reflecting performance and outcomes.

7. Design and Positive Impressions

• Observation: Despite challenges, players found aspects of the game enjoyable, such as watching numbers fluctuate and the overall design.
• Feedback: Positive impressions highlight potential if issues are addressed.
• Suggestions:
  • Focus on improving usability and addressing technical bugs to enhance player experience.

Version 5: 21 Nov 2024

 

The main changes made were to bring the scenario pop ups to the center of the screen (as shown below) and fixing the NaN bug. We understand that having an end goal (e.g how much money/getting acquired) may be exciting to players, however, we chose not to implement that as we are still able to effectively communicate the system to the players with the game as of now. In future iterations, that would potentially be a goal. 

 

We tested this game with another female Stanford graduate student. Picture below:

 

 

Here is the final feedback we received:

1. Initial Understanding of the Game

• Observation: The playtester initially found the game difficult to understand and was unsure how to make money.
• Feedback: Lack of a clear introduction left the player confused about roles, scene descriptions, and parameter relationships.
• Suggestion:
  • Add a digital introduction or onboarding tutorial at the start of the game that covers:
    • The game’s premise and goals.
    • Player roles and objectives.
    • Relationships between key parameters (e.g., balance, reputation).

2. Failure Definition

• Observation: The playtester asked whether the game had a clear definition of failure.
• Feedback: Lack of clarity about failure conditions left the player unsure about goals and progress.
• Suggestion:
  • Clearly define failure conditions (e.g., reaching a specific negative balance or reputation threshold).
  • Communicate these conditions at the start or through in-game notifications.

3. Satisfying Moments

• Observation: The player found the moment of turning a loss into a profit very satisfying.
• Feedback: Positive moments of success provided rewarding and engaging gameplay.
• Suggestion:
  • Emphasize these satisfying moments with celebratory animations or sound effects.
  • Design mechanics that allow players to experience these moments more frequently to maintain engagement.

Given this feedback and limited time, the biggest change that we incorporated into the final version of the game is adding a mini tutorial in the beginning explaining each parameter and what it affects before the player gets started. The other features are nice to have – animations, lose condition etc for future versions of the game. 

Here is a screenshot of the tutorial in the beginning:

Here is the final version of the game – https://6742c533f357ef51b584400b–spontaneous-snickerdoodle-471154.netlify.app/