Integrating AI with blockchain can enhance AI’s trustworthiness and revolutionize various sectors.
AI Developers Should Prioritize User Control
Stacey Engle, co-founder and CEO of Twin Protocol, argues that integrating artificial intelligence (AI) with blockchain technology can prevent misuse of AI and make AI operations more trustworthy. This combination, she asserts, has the potential to revolutionize various sectors, from healthcare to decentralized finance, by making services more reliable and user-friendly.
Engle highlights the promising future of AI by referencing accounting giant PwC’s prediction that AI could contribute $15.7 trillion to the global economy by 2030. This “unparalleled capacity” to reshape industries and economies, as Engle describes it, underscores the technology’s potential impact.
However, Engle acknowledges concerns about privacy as a potential hurdle to wider AI adoption. To address these concerns, she urges AI developers to prioritize user control, data privacy, and robust security measures. Additionally, AI companies should strive to educate the public about these safeguards.
On the topic of AI regulation, Engle emphasizes the need for a balanced approach that promotes transparency, user control, and data privacy while avoiding stifling innovation through overregulation. She believes this balance can be achieved through collaboration between AI developers, users, and regulators.
Engle’s written responses to Bitcoin.com News also addressed challenges in obtaining reliable personal data at scale and her vision for the AI industry’s future by 2030. Below are Engle’s answers to all the questions sent.
Bitcoin.com News (BCN): Despite criticism and growing scrutiny, the AI sector continues to expand, raising questions about the limits of AI’s potential. Can you briefly explain the basic concepts behind the growing awareness that the AI sector is experiencing?
Stacey Engle (SE): The explosive growth in AI awareness and adoption is fueled by its transformative potential. According to PwC, AI could contribute up to $15 trillion to the global economy by 2030, highlighting its unparalleled capacity to reshape industries and economies. At the same time, the World Economic Forum estimates that 800 million people may need to be reskilled by 2030 as AI and automation redefine work. These figures underscore both the vast opportunities and the urgent responsibilities that accompany AI’s rise.
Several key factors drive this momentum. AI’s ability to automate complex tasks, analyze massive datasets and self-improve through learning is revolutionizing industries like finance, healthcare, and education. Additionally, innovations such as blockchain and AI twins are expanding AI’s use cases, from enhancing transparency to personalizing experiences at scale.
The awareness really does highlight the positive trajectory of AI’s impact. With a balanced approach—prioritizing innovation while addressing societal needs and ethical considerations—we are poised for transformative growth that can empower individuals, industries, and communities alike.
BCN: How do you see AI and blockchain as complementary technologies, and in what specific ways can they enhance each other?
SE: AI and blockchain are complementary as they both aim to enhance security, transparency, and scalability. AI, with its ability to learn and adapt, can optimize blockchain operations, making them more efficient. On the other hand, blockchain can provide a secure and transparent platform for AI operations, ensuring data integrity and trust. For instance, in decentralized finance (DeFi), AI can enhance decision-making processes, while blockchain ensures secure and transparent transactions.
In healthcare, AI can analyze patient data for personalized care, and blockchain can ensure this sensitive data remains secure and unaltered. Together, they can revolutionize various sectors, making services more reliable and user-friendly. AI refines the output and blockchain ensures it remains secure and trustworthy.
BCN: While AI boasts several advantages, concerns about its risks are growing. Data privacy and personal security top the list of worries, with some experts fearing that the technology could eventually give rise to machines that operate beyond human control. This concern has reportedly been echoed by prominent figures like Geoffrey Hinton, known as the “Godfather of AI,” and Elon Musk. In your view, are these fears justified and if so, what can players in this space do to assuage skeptics?
SE: Yes, these fears are justified as AI’s potential misuse can lead to serious consequences. However, integrating AI with blockchain can mitigate these risks. Blockchain’s decentralized nature enhances security and transparency, making AI operations more trustworthy. For instance, Twin Protocol uses blockchain technology to secure user data, ensuring every interaction is verifiable. It also allows users to control their AI Twins and the information shared, enhancing privacy and security. To assuage skeptics, players in this space should prioritize user control, data privacy, and robust security measures, while also educating the public about these safeguards.
BCN: Many believe it is these fears that are fueling the regulation of the AI industry, a development most experts think is unnecessary and counterproductive. What are your thoughts on the current regulatory environment for AI? How can it be improved? What regulations should be retained, and which should be discarded?
SE: The current regulatory environment for AI is necessary but needs refinement. It should focus on promoting transparency, user control, and data privacy. Regulations that encourage these principles should be retained. However, over-regulation can stifle innovation. Improvement can be achieved by fostering a collaborative environment between AI developers, users, and regulators.
This collaboration can help create regulations that protect users without impeding progress. Furthermore, integrating AI with blockchain can enhance security and transparency, addressing many concerns about AI. Education about AI and its implications is also crucial to dispel fears and misconceptions. I think a key point is to have inclusive stakeholders involved and to be talking about real-life application, not hypotheticals.
BCN: How do you navigate the complex regulatory landscape surrounding AI and blockchain, particularly in terms of data privacy and security?
SE: Navigating the complex regulatory landscape surrounding AI and blockchain involves a multi-faceted approach. At Twin Protocol, we prioritize user control and data privacy. Our platform is designed to give individuals sovereignty over their data, with the ability to grant or revoke access as they see fit. We use blockchain technology to ensure secure storage and sharing of user data, with all interactions and data entries securely recorded on an immutable ledger. This not only enhances security but also fosters transparency and trust. Furthermore, we utilize smart contracts to specify sharing terms and conditions, ensuring data is shared only under specified terms.
BCN: What are some potential use cases for AI Twins, and how do you see them being utilized in various industries, such as education, healthcare, or entertainment?
SE: AI Twins can revolutionize industries. In education, they can facilitate personalized learning and reskilling. In healthcare, they can simulate patient responses to treatments. In entertainment, they can create realistic digital personas and truly immersive experiences. For businesses, they ensure knowledge transfer and reduce employee turnover impact. The use cases truly are endless, and we have partners around the world that are utilizing AI to better the world.
BCN: How does the Twin Protocol ensure the security and privacy of user data, particularly in the context of AI Twins, and what measures are in place to prevent data breaches or unauthorized access?
SE: Twin Protocol ensures security and privacy through a decentralized, tamper-proof system where all transactions are securely recorded. Robust encryption standards are used, allowing only authorized users to access or modify AI Twins. Users have control over data sharing and interaction, with the ability to manage permissions and revoke access at any time. Strict privacy policies and ethical guidelines are implemented to prevent data breaches and unauthorized access.
BCN: Any AI model or project needs a large scale of user behavioral datasets and analytical insights. In your opinion, what are the biggest challenges to obtaining reliable personal data at scale?
SE: One of the biggest challenges is trust. People are increasingly wary about how their data is collected, used, and shared. Rightfully so—data breaches, misuse of information, and a lack of transparency have created a trust deficit. To overcome this, organizations need to prioritize ethical data practices by being clear about why they’re collecting data, how it benefits the user, and what safeguards are in place to protect it.
Another challenge is bias. The data we collect is often a reflection of the systems and societal structures we operate within. If not managed carefully, AI models can perpetuate or even amplify these biases. To address this, it’s critical to design inclusive data collection strategies and rigorously audit datasets for fairness.
Finally, accessibility to high-quality, diverse datasets is a major hurdle. Some communities or demographics may not be as represented in the data collection process, leading to gaps in understanding and results. This calls for innovative solutions, such as synthetic data or partnerships with diverse organizations, to fill in these gaps while maintaining privacy.
Ultimately, obtaining reliable data at scale is less about the technology and more about building an ecosystem rooted in transparency, inclusion, and user empowerment.
When people feel respected and secure, they’re more willing to engage—and that’s when innovation truly thrives. Also, we always add a layer of fun. We want training your AI Twin to be fun and simple – and when that happens, more data is stored.
BCN: What do you envision for the future of AI and blockchain, and how will they shape the world around us?
SE: The future of AI and blockchain is about convergence—these technologies complement each other in ways that can fundamentally reshape industries and societies. AI brings intelligence, adaptability, and personalization, while blockchain offers security, transparency, and decentralization. Together, they form a foundation for trust and innovation in a digital-first world.
In the future, I see them enabling more equitable access to opportunities. For example, AI could provide personalized education tailored to each individual’s learning style, while blockchain ensures the credentials earned are secure and universally recognized. These technologies will also redefine how we interact economically and socially. Decentralized finance (DeFi), powered by blockchain and enhanced with AI-driven decision-making, could make financial systems more inclusive and efficient. In governance, transparent and automated systems could rebuild trust between people and institutions, creating accountability at scale.
However, their true potential lies in addressing systemic global challenges. Imagine using AI and blockchain to improve food supply chains, reduce waste, and ensure fair trade, or leveraging them to distribute resources in disaster relief more effectively.
For this vision to become reality, we must focus on ethical development. That means building systems that prioritize people, foster collaboration, and create value for all—not just the few. If we get this right, AI and blockchain won’t just shape the future; they’ll help us create one that’s more inclusive, equitable, and resilient.
