Opinion Elon Musks push for opensource AGI overlooks user needs and ethical AI education

Disclaimer: The writer’s opinions and perspectives shared in this article are their own and do not reflect the views of crypto.news’ editorial team.
In a recent legal battle, Elon Musk has filed a lawsuit against OpenAI for allegedly deviating from their mission of developing AGI for the betterment of humanity. Carlos E. Perez believes that this lawsuit could potentially transform the current market leader in Generative AI into a situation similar to WeWork.
The focus of this legal dispute is OpenAI’s transition towards becoming a for-profit entity. This shift towards profit-driven motives raises concerns about vested corporate interests and takes attention away from important issues such as ethical AI training and data management.
Elon’s creation, Grok, a competitor to ChatGPT, has the capability to extract ‘real-time information’ from tweets. OpenAI has been known for scraping copyrighted data without limitations. Recently, Google has secured a $60 million deal to access data from Reddit users for the training of Gemini and Cloud AI.
Merely advocating for open-source practices is not enough to protect the interests of users in this environment. Users require mechanisms to ensure that they provide meaningful consent and receive compensation for assisting in the training of LLMs. Platforms emerging to crowdsource AI training data play a crucial role in addressing these concerns.
The majority of internet users globally rely on centralized social media platforms, and the data they generate comprises a significant portion of the online data produced. Despite this, users often lack control and ownership over their data, with consent processes being deceptive or coercive at best.
Data has been likened to the new oil, and big tech companies have little incentive to grant users more control over their data due to the potential increase in training costs. However, the emergence of blockchain technology offers a new era for users to gain control over their data and engage in more transparent, cost-effective practices.
Web2’s model of trust among entities is being replaced by Web3’s ownership model, leveraging blockchain and cryptography to prevent malicious actors from exploiting data. This community-centric approach empowers users to reclaim control over their data and enables secure data sharing and transaction settlement.
The evolution of privacy and security technologies like zero-knowledge proofs and multi-party computation has revolutionized data validation and sharing, particularly in AI training. Decentralized platforms in Web3 facilitate direct connections between data producers and AI model trainers, eliminating the need for intermediaries and reducing costs.
Transitioning from top-down to bottom-up approaches in AI training frameworks is essential to ensure ethical practices. This shift towards a meritocratic system that values ownership, autonomy, and collaboration prioritizes equitable distribution over profit maximization.
It is imperative for the industry to embrace these new-age models that align incentives and benefit both large corporations and individual users. Holding onto outdated practices will not serve the long-term interests of the industry, as the future demands a more collaborative and ethical approach to AI training.