Video Art Tokenization in 2023


24 Aug 2023
Video Art Tokenization in 2023

The vast domain of the artistic sphere features video art as a relatively recent addition, yet one that has established its unique place. As 2023 began, video art gained greater attention and proved to be more than a mere fad. Foundational exhibitions and focused critiques merely touched upon the growth of this art form. However, an interesting metamorphosis was unfolding amidst the praise and curiosity, fueled by the digital era's defining feature: blockchain technology. This led to the emergence of 'video art tokenization', an innovative blend of artistry and tech that could transform the principles and value perception of video art, possibly addressing long-standing issues related to its collectability.

Video Art's Development and Importance

Starting as an avant-garde genre, video art was often regarded as the defiant counterpart to traditional artistic forms. It challenged established norms by providing artists with a vibrant platform where motion replaced stillness, and audio-visual stories held sway. By early 2023, organizations like MoMA underscored its international importance through groundbreaking exhibitions such as "Signals: How Video Transformed the World."

Nevertheless, its inherent qualities presented singular problems. Unlike the physical limitations of paintings or sculptures, video art's digital nature enabled infinite replication. Every copy maintained the original's legitimacy, democratizing the art form while simultaneously detracting from its perceived value based on conventional market standards. In a realm where an artwork's rarity frequently dictated its market worth, video art presented a dilemma. Collectors struggled to comprehend notions of originality and valuation. Why acquire an original if indistinguishable duplicates possessed equal artistic merit?

Video art's incompatibility with traditional art market principles – where scarcity is highly valued – poses not only economic but also philosophical challenges. It urges us to reconsider our understanding of worth, authenticity, and the core essence of art in today's digital age. The importance of video art thus goes beyond its visual allure, placing it at the crossroads of artistic expression, technological innovation, and market dynamics.

The Emergence of NFTs and Video Art Tokenization in the Artistic Sphere

Blockchain technology's inception, followed by the art world's introduction to Non-Fungible Tokens (NFTs), has sparked a transformative revolution. Essentially, an NFT is a distinct digital certificate of authenticity, securely stored on a decentralized digital ledger that confirms the originality of a digital asset. As the digital domain increasingly intertwines with our physical existence, NFTs have made their mark, particularly in supporting the value of digital artwork.

NFTs started as quiet murmurs within specialized digital art circles but quickly gained traction, drawing the interest of artists, galleries, and investors. They provided an answer to the longstanding problem of digital reproduction without devaluation, tackling a central issue for the art community – how to authenticate and appraise digital art when duplication is effortless.

Traditionally, artists did not directly profit from secondary sales of their works; however, NFTs offered newfound empowerment. Artists could now secure royalties from resales through "smart contracts" embedded in NFTs, establishing a viable financial framework that had been previously unattainable.

Moreover, video art tokenization through NFTs revitalized the dynamics of the art market. Auction houses initially expressed skepticism but later adopted this trending wave as record-breaking sales of digital artworks converted to NFTs made headlines. Motivated by the integration of technology and artistry, collectors started to view NFTs as more than mere curiosities – they became genuine investment prospects, signifying a shift in how art is evaluated and exchanged.

Nevertheless, NFTs' true brilliance in the artistic world extends beyond economics; it broadens artistic expression's horizons. Digital artists who were once marginalized within the broader artistic journey moved to center stage as leaders in an era where art transcends visual or auditory limitations and becomes a dynamic, interactive experience.

Examining Tokenized Video Art Collections

The fusion of video art and blockchain technology gives rise to an intriguing world of tokenized video art collections, challenging conventional standards and presenting groundbreaking opportunities for both artists and collectors.

Origins and Development

Tokenized video art collections stem from the unique characteristics of video art, which is dynamic, replicable, and inherently digital, as well as the revolutionary potential of NFTs. When artists started tokenizing their video works, a specific genre of collections emerged that pushed the limits of both video art and the NFT domain.

Prominent Collections and Innovators

The Akeroyd Collection, Shane Akeroyd's online media library, serves as a powerful example of what can be accomplished by blending traditional video art with tokenization's avant-garde features. Housing creations from influential artists like Cory Arcangel, Apichatpong Weerasethakul, and Theaster Gates, this collection demonstrates an exceptional fusion of classical video art and cutting-edge tokenization.

Artwrld is another noteworthy platform that showcases tokenized video collections from celebrated artists such as Shirin Neshat and Paul Pfeiffer. This platform has become a guiding light for digital video artists who want to capitalize on blockchain benefits and engage with a broader and more appreciative audience.

Distinctive Characteristics and Advantages

Enhanced transparency and traceability stand out among the most transformative aspects of tokenized video art collections. Unique digital records of provenance accompany each tokenized piece, adding layers of trust and authenticity while empowering potential buyers to examine the artwork's background, ownership changes, and previous valuations. This shift marks a significant departure from traditional art sales plagued with ambiguous provenance.

Furthermore, tokenizing video art addresses its inherent reproducibility by attaching value to once-easily replicated works. Tokenizing a piece includes a unique digital certificate signifying its originality and market worth.

Potential and Obstacles Ahead

Although tokenized video art collections have undoubtedly had a significant impact, they still face challenges, including concerns about copyrights, exhibition rights, and the broader legal framework governing digital ownership. However, as artists and platforms persist in experimenting, innovating, and stretching boundaries, the possibility for video art tokenization to revolutionize the essence of art collecting is tangible.

In conclusion, the melding of video art with NFTs takes us to the verge of a new epoch. A time when the intangible gains value, duplication transforms into uniqueness, and video art earns its place among highly coveted collectibles.

Tackling Obstacles and Envisioning the Future

The combination of video art and NFT ecosystem has created many opportunities for artists, collectors, and platforms; however, it also involves several complexities. This marriage of art and technology is innovative but comes with a series of issues that must be addressed for enduring success.

Legal Uncertainties and Intellectual Property

A major concern with video art tokenization is the unclear legal rights. How do exhibition rights adapt in a decentralized digital realm? What specific rights are granted to collectors when they obtain a tokenized video artwork, particularly regarding public displays or reproductions?

Traditional Market Ideals and Comprehension

The conventional art market, with its roots in physical art appreciation dating back centuries, may require time to grasp and welcome the intricacies of video art tokenization. The notion that a digitally reproducible piece can hold substantial value might defy long-established market perceptions. It becomes essential to educate traditional galleries and collectors about the inherent worth and possibilities offered by tokenized video art.

Looking Forward: A Hopeful Tomorrow

In spite of these challenges, a bright future awaits. Advancements in blockchain technology will likely reduce technical obstacles by becoming more accessible and user-friendly. As legal structures adapt to the rapid advancements of digital innovations, transparent guidelines pertaining to ownership and rights will develop.

Efforts such as educational initiatives, workshops, and partnerships between art institutions and tech professionals can help bridge the gap, expanding the understanding of video art tokenization's potential to broader audiences.


The joining of video art and NFTs represents more than just a momentary craze; it marks an evolutionary leap in the world of art, unifying innovation with tradition. As artists experience newfound liberation and collectors delve into uncharted territories, the challenges that surface are simply growing pains of a sector on the cusp of transformation. Reflecting on the impact of technology and creativity, it's clear that we stand at a critical turning point. A vast landscape of potential lays ahead, ready to be adorned with the vivid hues of innovation, collaboration, and forward-thinking vision.

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Applying Game Theory in Token Design

Kajetan Olas

16 Apr 2024
Applying Game Theory in Token Design

Blockchain technology allows for aligning incentives among network participants by rewarding desired behaviors with tokens.
But there is more to it than simply fostering cooperation. Game theory allows for designing incentive-machines that can't be turned-off and resemble artificial life.

Emergent Optimization

Game theory provides a robust framework for analyzing strategic interactions with mathematical models, which is particularly useful in blockchain environments where multiple stakeholders interact within a set of predefined rules. By applying this framework to token systems, developers can design systems that influence the emergent behaviors of network participants. This ensures the stability and effectiveness of the ecosystem.

Bonding Curves

Bonding curves are tool used in token design to manage the relationship between price and token supply predictably. Essentially, a bonding curve is a mathematical curve that defines the price of a token based on its supply. The more tokens that are bought, the higher the price climbs, and vice versa. This model incentivizes early adoption and can help stabilize a token’s economy over time.

For example, a bonding curve could be designed to slow down price increases after certain milestones are reached, thus preventing speculative bubbles and encouraging steadier, more organic growth.

The Case of Bitcoin

Bitcoin’s design incorporates game theory, most notably through its consensus mechanism of proof-of-work (PoW). Its reward function optimizes for security (hashrate) by optimizing for maximum electricity usage. Therefore, optimizing for its legitimate goal of being secure also inadvertently optimizes for corrupting natural environment. Another emergent outcome of PoW is the creation of mining pools, that increase centralization.

The Paperclip Maximizer and the dangers of blockchain economy

What’s the connection between AI from the story and decentralized economies? Blockchain-based incentive systems also can’t be turned off. This means that if we design an incentive system that optimizes towards a wrong objective, we might be unable to change it. Bitcoin critics argue that the PoW consensus mechanism optimizes toward destroying planet Earth.

Layer 2 Solutions

Layer 2 solutions are built on the understanding that the security provided by this core kernel of certainty can be used as an anchor. This anchor then supports additional economic mechanisms that operate off the blockchain, extending the utility of public blockchains like Ethereum. These mechanisms include state channels, sidechains, or plasma, each offering a way to conduct transactions off-chain while still being able to refer back to the anchored security of the main chain if necessary.

Conceptual Example of State Channels

State channels allow participants to perform numerous transactions off-chain, with the blockchain serving as a backstop in case of disputes or malfeasance.

Consider two players, Alice and Bob, who want to play a game of tic-tac-toe with stakes in Ethereum. The naive approach would be to interact directly with a smart contract for every move, which would be slow and costly. Instead, they can use a state channel for their game.

  1. Opening the Channel: They start by deploying a "Judge" smart contract on Ethereum, which holds the 1 ETH wager. The contract knows the rules of the game and the identities of the players.
  2. Playing the Game: Alice and Bob play the game off-chain by signing each move as transactions, which are exchanged directly between them but not broadcast to the blockchain. Each transaction includes a nonce to ensure moves are kept in order.
  3. Closing the Channel: When the game ends, the final state (i.e., the sequence of moves) is sent to the Judge contract, which pays out the wager to the winner after confirming both parties agree on the outcome.

A threat stronger than the execution

If Bob tries to cheat by submitting an old state where he was winning, Alice can challenge this during a dispute period by submitting a newer signed state. The Judge contract can verify the authenticity and order of these states due to the nonces, ensuring the integrity of the game. Thus, the mere threat of execution (submitting the state to the blockchain and having the fraud exposed) secures the off-chain interactions.

Game Theory in Practice

Understanding the application of game theory within blockchain and token ecosystems requires a structured approach to analyzing how stakeholders interact, defining possible actions they can take, and understanding the causal relationships within the system. This structured analysis helps in creating effective strategies that ensure the system operates as intended.

Stakeholder Analysis

Identifying Stakeholders

The first step in applying game theory effectively is identifying all relevant stakeholders within the ecosystem. This includes direct participants such as users, miners, and developers but also external entities like regulators, potential attackers, and partner organizations. Understanding who the stakeholders are and what their interests and capabilities are is crucial for predicting how they might interact within the system.

Stakeholders in blockchain development for systems engineering

Assessing Incentives and Capabilities

Each stakeholder has different motivations and resources at their disposal. For instance, miners are motivated by block rewards and transaction fees, while users seek fast, secure, and cheap transactions. Clearly defining these incentives helps in predicting how changes to the system’s rules and parameters might influence their behaviors.

Defining Action Space

Possible Actions

The action space encompasses all possible decisions or strategies stakeholders can employ in response to the ecosystem's dynamics. For example, a miner might choose to increase computational power, a user might decide to hold or sell tokens, and a developer might propose changes to the protocol.

Artonomus, Github

Constraints and Opportunities

Understanding the constraints (such as economic costs, technological limitations, and regulatory frameworks) and opportunities (such as new technological advancements or changes in market demand) within which these actions take place is vital. This helps in modeling potential strategies stakeholders might adopt.

Artonomus, Github

Causal Relationships Diagram

Mapping Interactions

Creating a diagram that represents the causal relationships between different actions and outcomes within the ecosystem can illuminate how complex interactions unfold. This diagram helps in identifying which variables influence others and how they do so, making it easier to predict the outcomes of certain actions.

Artonomus, Github

Analyzing Impact

By examining the causal relationships, developers and system designers can identify critical leverage points where small changes could have significant impacts. This analysis is crucial for enhancing system stability and ensuring its efficiency.

Feedback Loops

Understanding feedback loops within a blockchain ecosystem is critical as they can significantly amplify or mitigate the effects of changes within the system. These loops can reinforce or counteract trends, leading to rapid growth or decline.

Reinforcing Loops

Reinforcing loops are feedback mechanisms that amplify the effects of a trend or action. For example, increased adoption of a blockchain platform can lead to more developers creating applications on it, which in turn leads to further adoption. This positive feedback loop can drive rapid growth and success.

Death Spiral

Conversely, a death spiral is a type of reinforcing loop that leads to negative outcomes. An example might be the increasing cost of transaction fees leading to decreased usage of the blockchain, which reduces the incentive for miners to secure the network, further decreasing system performance and user adoption. Identifying potential death spirals early is crucial for maintaining the ecosystem's health.

The Death Spiral: How Terra's Algorithmic Stablecoin Came Crashing Down
the-death-spiral-how-terras-algorithmic-stablecoin-came-crashing-down/, Forbes


The fundamental advantage of token-based systems is being able to reward desired behavior. To capitalize on that possibility, token engineers put careful attention into optimization and designing incentives for long-term growth.


  1. What does game theory contribute to blockchain token design?
    • Game theory optimizes blockchain ecosystems by structuring incentives that reward desired behavior.
  2. How do bonding curves apply game theory to improve token economics?
    • Bonding curves set token pricing that adjusts with supply changes, strategically incentivizing early purchases and penalizing speculation.
  3. What benefits do Layer 2 solutions provide in the context of game theory?
    • Layer 2 solutions leverage game theory, by creating systems where the threat of reporting fraudulent behavior ensures honest participation.

Token Engineering Process

Kajetan Olas

13 Apr 2024
Token Engineering Process

Token Engineering is an emerging field that addresses the systematic design and engineering of blockchain-based tokens. It applies rigorous mathematical methods from the Complex Systems Engineering discipline to tokenomics design.

In this article, we will walk through the Token Engineering Process and break it down into three key stages. Discovery Phase, Design Phase, and Deployment Phase.

Discovery Phase of Token Engineering Process

The first stage of the token engineering process is the Discovery Phase. It focuses on constructing high-level business plans, defining objectives, and identifying problems to be solved. That phase is also the time when token engineers first define key stakeholders in the project.

Defining the Problem

This may seem counterintuitive. Why would we start with the problem when designing tokenomics? Shouldn’t we start with more down-to-earth matters like token supply? The answer is No. Tokens are a medium for creating and exchanging value within a project’s ecosystem. Since crypto projects draw their value from solving problems that can’t be solved through TradFi mechanisms, their tokenomics should reflect that. 

The industry standard, developed by McKinsey & Co. and adapted to token engineering purposes by Outlier Ventures, is structuring the problem through a logic tree, following MECE.
MECE stands for Mutually Exclusive, Collectively Exhaustive. Mutually Exclusive means that problems in the tree should not overlap. Collectively Exhaustive means that the tree should cover all issues.

In practice, the “Problem” should be replaced by a whole problem statement worksheet. The same will hold for some of the boxes.
A commonly used tool for designing these kinds of diagrams is the Miro whiteboard.

Identifying Stakeholders and Value Flows in Token Engineering

This part is about identifying all relevant actors in the ecosystem and how value flows between them. To illustrate what we mean let’s consider an example of NFT marketplace. In its case, relevant actors might be sellers, buyers, NFT creators, and a marketplace owner. Possible value flow when conducting a transaction might be: buyer gets rid of his tokens, seller gets some of them, marketplace owner gets some of them as fees, and NFT creators get some of them as royalties.

Incentive Mechanisms Canvas

The last part of what we consider to be in the Discovery Phase is filling the Incentive Mechanisms Canvas. After successfully identifying value flows in the previous stage, token engineers search for frictions to desired behaviors and point out the undesired behaviors. For example, friction to activity on an NFT marketplace might be respecting royalty fees by marketplace owners since it reduces value flowing to the seller.


Design Phase of Token Engineering Process

The second stage of the Token Engineering Process is the Design Phase in which you make use of high-level descriptions from the previous step to come up with a specific design of the project. This will include everything that can be usually found in crypto whitepapers (e.g. governance mechanisms, incentive mechanisms, token supply, etc). After finishing the design, token engineers should represent the whole value flow and transactional logic on detailed visual diagrams. These diagrams will be a basis for creating mathematical models in the Deployment Phase. 

Token Engineering Artonomous Design Diagram
Artonomous design diagram, source: Artonomous GitHub

Objective Function

Every crypto project has some objective. The objective can consist of many goals, such as decentralization or token price. The objective function is a mathematical function assigning weights to different factors that influence the main objective in the order of their importance. This function will be a reference for machine learning algorithms in the next steps. They will try to find quantitative parameters (e.g. network fees) that maximize the output of this function.
Modified Metcalfe’s Law can serve as an inspiration during that step. It’s a framework for valuing crypto projects, but we believe that after adjustments it can also be used in this context.

Deployment Phase of Token Engineering Process

The Deployment Phase is final, but also the most demanding step in the process. It involves the implementation of machine learning algorithms that test our assumptions and optimize quantitative parameters. Token Engineering draws from Nassim Taleb’s concept of Antifragility and extensively uses feedback loops to make a system that gains from arising shocks.

Agent-based Modelling 

In agent-based modeling, we describe a set of behaviors and goals displayed by each agent participating in the system (this is why previous steps focused so much on describing stakeholders). Each agent is controlled by an autonomous AI and continuously optimizes his strategy. He learns from his experience and can mimic the behavior of other agents if he finds it effective (Reinforced Learning). This approach allows for mimicking real users, who adapt their strategies with time. An example adaptive agent would be a cryptocurrency trader, who changes his trading strategy in response to experiencing a loss of money.

Monte Carlo Simulations

Token Engineers use the Monte Carlo method to simulate the consequences of various possible interactions while taking into account the probability of their occurrence. By running a large number of simulations it’s possible to stress-test the project in multiple scenarios and identify emergent risks.

Testnet Deployment

If possible, it's highly beneficial for projects to extend the testing phase even further by letting real users use the network. Idea is the same as in agent-based testing - continuous optimization based on provided metrics. Furthermore, in case the project considers airdropping its tokens, giving them to early users is a great strategy. Even though part of the activity will be disingenuine and airdrop-oriented, such strategy still works better than most.

Time Duration

Token engineering process may take from as little as 2 weeks to as much as 5 months. It depends on the project category (Layer 1 protocol will require more time, than a simple DApp), and security requirements. For example, a bank issuing its digital token will have a very low risk tolerance.

Required Skills for Token Engineering

Token engineering is a multidisciplinary field and requires a great amount of specialized knowledge. Key knowledge areas are:

  • Systems Engineering
  • Machine Learning
  • Market Research
  • Capital Markets
  • Current trends in Web3
  • Blockchain Engineering
  • Statistics


The token engineering process consists of 3 steps: Discovery Phase, Design Phase, and Deployment Phase. It’s utilized mostly by established blockchain projects, and financial institutions like the International Monetary Fund. Even though it’s a very resource-consuming process, we believe it’s worth it. Projects that went through scrupulous design and testing before launch are much more likely to receive VC funding and be in the 10% of crypto projects that survive the bear market. Going through that process also has a symbolic meaning - it shows that the project is long-term oriented.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.


What does token engineering process look like?

  • Token engineering process is conducted in a 3-step methodical fashion. This includes Discovery Phase, Design Phase, and Deployment Phase. Each of these stages should be tailored to the specific needs of a project.

Is token engineering meant only for big projects?

  • We recommend that even small projects go through a simplified design and optimization process. This increases community's trust and makes sure that the tokenomics doesn't have any obvious flaws.

How long does the token engineering process take?

  • It depends on the project and may range from 2 weeks to 5 months.