Big Data Expert: Current AI Regulations Hinder Progress, David Sacks Appointment a Positive Step

David Sacks’ Appointment Boosts AI, Crypto

Chi Zhang, CEO at Kite AI, believes the EU’s law on AI, while enacted with good intentions, could “impose burdensome compliance on smaller innovators.” Conversely, the United States “more open-ended” approach to AI lacks cohesive federal legislation, potentially hindering innovation.

In written responses shared with Bitcoin.com News, Zhang, a mentor for early-stage founders, emphasized the importance of striking a balance between fostering innovation and ensuring public safety. However, she acknowledged that achieving this equilibrium has its challenges.

Regarding the appointment of David Sacks as the incoming administration’s AI and crypto czar, Zhang sees it as evidence of the Trump administration’s “strong focus on driving innovation.” She believes Sacks’ experience scaling digital platforms and managing complex ecosystems could also bring much-needed structure and coordination to the AI and blockchain industries.

Echoing some of her peers who have praised the selection, Zhang suggests Sacks’ appointment points to a U.S. government policy framework that supports fair value capture, incentivizes innovation, and addresses ethical concerns. Such a framework could lay the groundwork for sustainable growth and position the United States as a future global hub for both crypto and AI, the CEO said.

Meanwhile, in her responses, Zhang also discussed two recent advances in generative AI (GenAI) and their benefits to the ecosystem. Below are Zhang’s answers to all the questions sent.

Bitcoin.com News (BCN): The U.S. President-elect Donald Trump has picked former Paypal Chief Operating Officer David Sacks as the new White House AI and crypto Czar. As an expert working at the intersection of AI and crypto, could you tell our readers what Sacks’ appointment means for the future of both the AI and crypto industries?

Chi Zhang (CZ): David Sacks’ appointment signals a strong focus on driving innovation at the intersection of AI and blockchain technologies. His experience in scaling digital platforms and managing complex ecosystems at PayPal could bring much-needed structure and coordination to these rapidly evolving industries. For AI and crypto, this could mean policy frameworks that support fair value capture, incentivize innovation, and address ethical concerns—paving the way for sustainable growth and making the US a global hub for both crypto and AI, just like it has been for the software industry.

BCN: The internet has been abuzz with generative AI (GenAI) solutions, enabling users to explore unlimited virtual concepts that promote a new era of online culture. Despite the exciting aspects of this trend, there are associated risks and inherent dangers, including deepfakes, which can be very harmful to businesses. Considering GenAI has been in existence for a long period, what do you think are the elements behind the recent boom?

CZ: The recent boom in GenAI can be attributed to advancements in large language models (LLMs), improved training algorithms, and the availability of high-performance computing resources such as GPUs. Additionally, decentralized technologies have enabled collaborative data-sharing frameworks, accelerating innovation. The accessibility of tools and APIs has empowered more developers and businesses to integrate GenAI into real-world applications, fueling its widespread adoption.

BCN: Internet users can now create AI models in high-quality text, graphics, and videos. Can you provide examples of how the ability to create AI models in high-quality text, graphics, and videos can be harnessed for positive impact in various industries and aspects of life?

CZ: Generative AI has a range of applications across industries. For individuals, it powers creative tools for content generation, from writing assistance to image creation. For businesses, it’s transforming marketing by automating ad designs, enabling hyper-personalized customer experiences, and generating synthetic data for training models. In healthcare, it’s being used to create diagnostic tools and simulate medical scenarios. Its ability to accelerate prototyping and problem-solving makes it invaluable across fields.

BCN: Besides being beneficial in many ways, GenAI has its some of which have been highlighted above. Could you highlight any other risks associated with the rapidly expanding GenAI technology?

CZ: Beyond deepfakes and impersonation risks, GenAI can propagate bias if trained on flawed datasets, leading to unintended discrimination in applications like hiring or lending. Another concern is the lack of transparency in model outputs, which can erode trust. Additionally, intellectual property disputes arise when GenAI models generate content derived from copyrighted data. These risks emphasize the need for robust governance and fair attribution mechanisms.

BCN: Regulation has become a crucial aspect of recent technological developments. Most governments are scrambling to protect citizens and their nations from the potential dangers of emerging technologies. However, the decentralized nature and rapid evolution of these technologies pose significant challenges for many governments worldwide. As governments worldwide strive to balance citizen protection with innovation, in your opinion, how effective are current global regulatory policies in addressing the challenges posed by emerging technologies like AI?

CZ: Global AI regulation is still in its infancy, with varying levels of progress. While the EU’s AI Act is a comprehensive attempt at addressing risks, it could impose burdensome compliance on smaller innovators. In contrast, the U.S. has adopted a more open-ended approach but lacks cohesive federal legislation. Striking a balance between fostering innovation and ensuring public safety is challenging, and decentralized systems like Kite AI can help by embedding transparency and accountability at the infrastructure level.

BCN: What alternative methods would you recommend for governments to regulate the emerging technology ecosystem, particularly artificial intelligence?

CZ: Governments should focus on outcome-based regulation rather than rigid compliance measures. Collaborative frameworks involving public and private sectors can ensure that policies keep pace with technological advancements. Regulatory sandboxes, for example, allow innovation within controlled environments. Decentralized governance models can also play a role by ensuring fair access and robust attribution without the need for heavy-handed interventions.

BCN: Your project, Kite AI, aims to ensure fair access to AI resources—data, models, and agents. Could you briefly talk about this and how you plan to achieve this goal?

CZ: At Kite AI, we’re building the foundation layer for a global AI-driven digital economy. Imagine a system where anyone, from small developers to large organizations, can access high-quality AI data and tools transparently and fairly. Through our blockchain-powered coordination layer, we ensure that contributors retain ownership of their assets and are fairly rewarded whenever their data, models, or AI agents are used. This makes AI innovation accessible to everyone, not just big tech.

BCN: Transformers and large language models (LLMs) are two additional recent advances in Generative AI. Could you explain to our readers what they are, how these function, and the benefits they bring to the Gen AI ecosystem?

CZ: Transformers are a type of machine learning model architecture that excels at understanding and generating sequential data, such as text or code. LLMs (Large Language Models) are built on transformers and trained on massive datasets to perform tasks like language translation, summarization, and content generation. Their versatility has unlocked new capabilities in GenAI, making it easier to build applications that require understanding and producing human-like text.

BCN: Despite existing for several years, generative AI has experienced a surge in popularity over the past few years, likely due to advancements in supporting decentralized technologies. What are your expectations for the industry’s development over the next five years?

CZ: In the next five years, we expect GenAI to integrate seamlessly with decentralized frameworks, enabling collaborative ecosystems where contributors are fairly rewarded for their data and expertise. AI-powered digital economies will emerge, driven by decentralized governance and transparent attribution. Kite AI is at the forefront of this transformation, providing the foundational infrastructure to unlock global collaboration and innovation in AI.