The Age of Artificial Media, and Provable AI's role in it
The future of media is artificial, and it's causing quite a stir.
Enterprises and consumers alike are feeling the heat, as multi-billion-dollar lawsuits relating to copyright and data-privacy infringements are filed day after day. The emergence of deepfakes and the spread of disinformation are setting off alarm bells. Concerns about bias, surveillance, hacking, and privacy are on the rise. And let's not forget the age-old fear of robots taking over - that's making a comeback as AI-powered machines become an everyday sight on our streets.
Contrary to the prevailing sense of apprehension, we firmly believe that AI development & can thrive ethically, sidestepping legal quagmires and combating the 'evil tech' stereotype, given the right set of tools. Rather than succumbing to fear or hoping no one ever finds out how the sausage is made, we champion the potential of AI to do great things, with the right tools to verify legal & ethical training.
How did we get here?
We're living in a time brimming with anticipation, as we're on the brink of witnessing an explosion in the quantity and diversity of generated content. We can trace the evolution of media through three distinct epochs, each one building upon the last, shaping our past, present, and future:
Expert media describes an era when production and distribution of content was exclusively controlled by professionals who were trained or devoted to specific fields such as journalism, art, music and audio production, film, and video production. As a result, the amount of content produced was comparatively small, and the experts whose content was amplified by institutional channels of distribution, were the main voices who were heard at scale.
Social media democratized content creation, allowing anyone to contribute to a vast pool of text, audio, image, and video content. This led to the rise of citizen journalism, self-published music and audio books, and individual artists monetizing their work. Despite concerns about disinformation and legal issues, this has also sparked global movements for change, with much individual-generated content being amplified by expert media channels.
Artificial media means generative AI models have started and are anticipated to continue to produce a massive amount of media content across different formats such as text, audio, images, and video. This promises an exponential rise in the amount of content generated, surpassing the combined output of social and expert media.
With each transition from era to era, we've seen both an exponential increase in content production as well s an escalating risk of disinformation and potential legal violations. We're going to look at three main issues we see with the rise of artificial media and how provable AI helps combat against their worst implications: 1) Copyright & Data Privacy Infractions; 2) Compliance with Existing & Impending Regulation; 3) Fears about Unethical AI.
1) Copyright & Data Privacy Infractions
The challenges associated with copyright and data privacy infractions are becoming increasingly complex. Many of these complications arise from AI models being trained on a vast array of materials, including those protected by copyright laws and data privacy regulations such as the General Data Protection Regulation (GDPR). This indiscriminate use of data is already leading to a surge in lawsuits, and the situation is likely to escalate unless AI systems, especially generative ones, can be brought in line with existing legal frameworks.
However, AI companies are not without tools to navigate these tricky waters. By training AI systems with provable, verified data anchored to the blockchain, trainers can provide concrete evidence of the sources used in the training process. This means they can ensure their models are trained only on legal, licensed sources for which they have obtained the necessary permissions. This approach effectively eliminates the risk of lawsuits related to copyright and data privacy infractions, allowing companies to spin up defenses in minutes rather than months of searching to provide all of the data requested in an investigation like the FTC's.
Weavechain's solution for AI training, Verifiable, provides a robust framework for this process, incorporating notarized authentic content signed at the source, a complete value chain, and verifiable computation options. This pioneering approach could be the key to ensuring AI development can defend itself from costly litigation, damages, and retraining fees if they are found to be in violation.
2) Compliance with Existing & Impending Regulation
As AI continues to evolve and integrate deeper into our society and economy, companies that develop and deploy these technologies will face a host of new and complex regulatory challenges. The call for regulation is growing, and it goes beyond the data privacy and copyright issues mentioend above. The prevention of bias in AI systems and the need for safeguards against fraud and terrorism are paramount. These concerns are not only being voiced by the public and lawmakers, but also by tech giants like Microsoft. In fact, the regulatory landscape is becoming so complex that some US lawmakers are advocating for the creation of an entire regulatory body dedicated to overseeing AI, while the EU has already passed its inaugural AI regulation bill.
In light of these developments, the ability to train AI systems on verifiable data is becoming increasingly important. This approach allows AI companies to demonstrate that they have complied with regulations in a zero-trust environment, when we are entering a world of disinformation where it is becoming more and more difficult to distinguish fact from fiction.
Again, notarized authentic content signed at the source, a complete value chain, and verifiable computation power demonstrate verifiable compliance with regulations. The icing on the cake is that Verifiable integrates directly into the training process with minimal friction, eliminating the need for expensive audits to "figure out what happened before the black box," instead providing regulators with a provable chain of compliant behavior.
3) Fears about Unethical AI
There is an undeniable undercurrent of fear and mistrust surrounding AI. This skepticism stems from a myriad of concerns, ranging from the fear of AI-driven discrimination to the dystopian idea of robots taking over the world. This mistrust is further exacerbated by the “black-box” nature of AI training and illegal data scraping, which often occurs without the knowledge or consent of the individuals whose data is being used. With such apprehensions, garnering moral support or buy-in for AI products can be a challenging task.
This is where Weavechain's newest offering, Verifiable, comes into play. It offers a comprehensive solution to these concerns by allowing companies to provide concrete proof that the data used to train their AI models was collected ethically. In a zero-trust environment, companies can demonstrate that their data comes from reputable sources, thus dispelling fears of unethical data practices.
And it gets better – Verifiable actually enables companies to license data directly with automated payments, fostering a gig economy of crowdsourced content where creators are fairly compensated for their contributions. This not only ensures ethical data practices but also promotes transparency and trust, which are crucial in overcoming the public's apprehension towards AI. By licensing data legally and ethically, companies can bridge the trust gap, providing reassurance that AI technology is not only innovative but also responsible and fair.
Provable AI in Action
Take a moment to check out this short demo created for the Augment Decentralized AI Hackathon. It'll give you a firsthand look at how Verifiable works:
In an era where businesses are under costly legal scrutiny and public trust is hard to earn, AI companies can safeguard their reputation and win over consumers by incorporating verifiable defenses into their AI Stacks. Verifiable was designed with these challenges in mind, acknowledging the growing number of lawsuits, regulatory activity, public concern over generative AI disinformation, and creators' frustration over uncompensated use of their work.
Verifiable provides the simplest solution, integrating seamlessly into the training data stack, enabling companies to comply with regulations and prepare defenses swiftly. It also allows them to proudly demonstrate their commitment to ethical AI training and fair compensation for creators.
Whether the goal is to ward off lawsuits, prepare for regulatory changes, build consumer trust, or ensure fair and verifiable licensing of content, we are here to help. We are excited about the potential of fostering a future of defensible, ethical AI and look forward to discussing how we can support you. Please get in touch to learn more. You’re warmly invited to:
Watch the Future of Data podcast for conversations on security, privacy, economies, lineage, confidential computing, interoperability, blockchain/Web3, artificial intelligence/AI, ethics, and regulation
Subscribe to our newsletter