AI and Web3 Could Make Entertainment More Interactive, but Privacy Remains a Constraint

AI and Web3 could change how entertainment is made, watched and paid for. But the ideas discussed at the “Reimagine Media & Content Ecosystem with Web3 & AI” panel come with a practical tension: more personalized experiences depend on data, while users want greater control over how that data is handled.

The discussion brought together Feida Zhu, associate dean at SMU; James Liu, director at Alibaba Cloud; Raymond Chung, CTO at ZEASN; and Anndy Lian, advisor at Bybit. Their proposals span interactive television, AI assisted production, blockchain based verification and new ways for creators to earn. They describe possible uses, rather than measured results from deployed systems.

Television becomes interactive

As viewing shifts toward smartphones and portable devices, television providers face pressure to make the living room experience more responsive. AI could help by tailoring recommendations, responding to voice commands and adjusting what a service offers to a viewer’s preferences. The panel also pointed to educational features for children and real time interaction as possible extensions.

Lian sees a TV evolving beyond a screen that simply plays a selected program. An AI assistant could ask what a viewer wants to watch, recommend a film, or help with gaming and educational tasks. That vision turns the interface into an active part of the experience, although the discussion didn’t specify how such a system would handle mistakes, unwanted suggestions or shared household profiles.

AI could also affect what appears on screen. Chung described systems that might generate dynamic or customized material, including lessons adapted to a student’s learning style and games adjusted to a player’s skills and preferences. For producers, those tools could support a wider range of formats and make variations for different audiences easier to create. The panel offered no production cost comparisons or evidence about how generated material would perform with viewers.

That distinction matters. Personalized output may give audiences more relevant choices, but it also changes the production process: creators and distributors would need to decide where automated generation fits, how much human review content requires, and how to maintain a recognizable creative voice.

Web3 proposes new forms of control

The Web3 case rests on blockchain and decentralized networks. Liu argued that these systems could give users more control over personal information by storing data across decentralized infrastructure, addressing concerns about the volume of information traditional platforms collect. The panel did not detail a particular storage design or explain how it would balance privacy with the data access AI services may need.

Blockchain could also help record who owns a piece of content and track its distribution. In principle, verifiable records could make unauthorized copying easier to identify. The panel presented this as a possible response to piracy, though a record of ownership does not by itself prevent someone from copying or sharing a file. Its usefulness would depend on how content is registered and how rights holders and platforms act on those records.

Another proposed use is verifying authenticity. AI can generate or alter media, creating a need for ways to check where a piece of content came from and whether it has changed. Blockchain records could provide a trail for that information. The panel framed this as one way to address manipulated media and misinformation, while leaving open how verification would work across different services and how users would judge the records they see.

Creator earnings and participation

Web3 could give creators additional ways to earn from their work. Zhu discussed tokens that represent a creator’s influence or popularity and could be traded or used within an online ecosystem. Creators might also sell non-fungible tokens (NFTs) tied to their content, creating another route to reach audiences and generate income.

These models could connect audience participation more directly to creator earnings. The panel also suggested that AI and blockchain might reward users for making content that attracts an audience, across formats such as anime and soap operas. The value of that approach would depend on whether audiences choose to participate and whether creators can build durable relationships with them. No figures or specific platform examples were presented to show how much these models might earn.

Privacy remains a design problem

AI systems often rely on large amounts of data, and using that information can create risks if it is mishandled or exposed. Lian placed responsibility on both service providers and users: providers should protect sensitive information and limit access, while users should consider what they share and understand the implications across both Web2 and Web3 services.

That advice points to a central implementation question. Personalized recommendations and adaptive content need information about users, but an entertainment service should make clear what it collects and how that information shapes the experience. Privacy focused AI models and encryption methods could help protect data, though the panel did not name specific techniques or describe how well they work in these settings.

The panel’s picture of entertainment is therefore a set of connected possibilities: AI could make viewing and content creation more responsive, while blockchain could support ownership records, authenticity checks and new creator payment models. The practical test will be whether services can deliver those features with clear data practices and useful safeguards. The event was supported by Singapore Management University and Moledao.