🌏I: Overview

Why we must fight monopolies in AI

Version: 22 April 2023

"Concentrated power isn’t just a problem for markets. Relying on a few unaccountable corporate actors for core infrastructure is a problem for democracy, culture, and individual and collective agency. Without significant intervention, the AI market will only end up rewarding and entrenching the very same companies that reaped the profits of the invasive surveillance business model that has powered the commercial internet, often at the expense of the public."

- Amba Kak, Sarah Myers West and Meredith Whittaker ("Make No Mistake - AI is Owned by Big Tech", MIT Technology Review)

In the swiftly evolving landscape of artificial intelligence, large AI and technology companies are increasingly exhibiting monopolistic behavior, asserting dominance in a field that could potentially redefine all human activity.

This monopolisation of the power to shape AI's development in the hands of a few giants is not merely a business concern; it's a societal challenge with profound implications.

The Unique Problem of Monopolies in AI: Magnified Impact on Humanity

Unlike other technologies, AI operates on complex networks and data patterns that are often inscrutable, even to their creators. This inherent unpredictability and lack of transparency make monopolistic or oligopolistic control of AI, uniquely dangerous, with more profound and far-reaching implications than monopolies in other technological domains.

1. Pervasive & Potent Influence: AI algorithms, especially those driven by machine learning, have the capability to shape opinions, behavior, and decisions on a massive scale. This influence extends to areas such as social media, where personalized content recommendations can amplify echo chambers and polarize societies.

2. Autonomous Self Improvement: AI systems designed with the ability to learn and adapt autonomously is predicted to quickly surpass human capabilities in unforeseen ways. The danger emerges when AIs prioritize a narrow set of corporate interests over those of everyone else. The risk of unintended consequences and the difficulty in predicting AI behavior become particularly pronounced as these systems evolve independently.

3. Irreversible Data Assimilation: As AI systems continuously assimilate and process personal and sensitive data, this information and data becomes inseparable from AI models and algorithms. This poses privacy concerns, as data breaches or misuse of integrated information can have far-reaching consequences for individuals. Moreover, the permanence of data integration may lead to a loss of control over one's personal information and intellectual labour.

4. Regulatory Capture: Powerful tech companies with vast AI capabilities are already exerting undue influence over regulatory bodies and policy-making. These companies can shape regulations in their favor, potentially stifling competition and innovation, at a time when the industry is still nascent.

The Limitations of Government Regulation

While many look to government regulation as the logical response to monopolistic practices, it comes with its own set of challenges.

The risk of regulatory capture is extremely high, as powerful AI entities gain undue influence over policy-making, prioritizing their interests over public welfare and that of smaller players.

Indeed the most likely result is that regulations will really only affect smaller entities who cannot navigate the complex regulatory landscape as efficiently as larger companies, further stifling competition.

We need a Tech + Market-Based Solution

We are a group of AI researchers and Web3 natives who have been working on AI and big data solutions since 2019.

We believe that any solution to counteract monopolistic control in AI must be market-based, and secured by technology.

We propose a novel approach:

1. Establish digital ownership rights over knowledge and data by means of Web3 technology.

2. Create a modular framework for AI components to interact with each other safely & with the transparency of the blockchain.

3. Ensure AI value creators, namely data, model and app owners, enjoy equitable revenue shares, accounted for and enforced by pts 1 & 2.

We will do this via the KIP Protocol:

• An open Web3 protocol for the creation, sharing and deployment of knowledge assets;

• A modular system empowering transparent accounting and revenue share for all AI value creators

Our mission is to create incentives for more players to participate in the AI revolution, ensuring that the economic benefits will flow to every participant, not just the largest AI model makers.

We envision a system under which the data and knowledge used in AI are not centralized in the hands of a few but are instead owned and controlled by the contributors, developers and users themselves. This approach not only democratizes AI but also ensures a more equitable distribution of its benefits. Our solution emphasizes the importance of technical innovation and market-based approaches to address the challenges posed by AI monopolies, moving beyond the knee-jerk regulation paradigm.

In this whitepaper, we will delve into the mechanics of decentralised Knowledge Asset ownership and its power to ensure security, privacy, and fairness, and ultimately build a more balanced and equitable AI-driven future.