'AI Proof' Content Delivery according to AI and the businesses - in Tech - already using it

Question 1 of 2 for AI services: Please describe in great detail the best technical plan to deliver content such as books, games, movies, music and software to customers in such a way that completely prevents any AI service from a) using it as training data b) scraping the digital information from the content owners service or platform and b) accessing it with the end user or using it when the end user wants to upload it to an AI service. Provide a robust plan that content owners can use when wanting to design and built an AI proof content delivery system. Describe all components content owners should think of and feel free to mention tools, technologies, hardware, software, and delivery platforms that can be of use.

ChatGPT-4’s answer:Designing a robust content delivery system that prevents AI services from using the content as training data, scraping the digital information, or accessing it with the end user requires a multi-layered approach. This approach should include a combination of encryption, access control, watermarking, and monitoring technologies. Here's a detailed plan:

1. Encryption: All content should be encrypted both at rest and in transit. This means using technologies like Secure Sockets Layer (SSL) or Transport Layer Security (TLS) for data in transit, and disk or database encryption for data at rest. This ensures that even if an AI service were to somehow gain access to the data, it would be unreadable without the decryption key.

2. Access Control: Implement strict access control measures. This includes authentication (verifying who you are) and authorization (verifying what you can do). Use technologies like OAuth or OpenID for authentication, and Role-Based Access Control (RBAC) or Attribute-Based Access Control (ABAC) for authorization. This ensures that only authorized users can access the content.

3. Watermarking: Digital watermarking can be used to embed invisible or barely noticeable information into the content. This can be used to trace back any unauthorized use of the content. For example, if an AI service were to use the content as training data, the watermark could potentially be used to identify the source of the data.

4. Monitoring and Auditing: Implement continuous monitoring and auditing of all access to the content. This includes logging all access attempts, both successful and unsuccessful, and regularly reviewing these logs for any suspicious activity. Use technologies like Security Information and Event Management (SIEM) systems for this purpose.

5. Data Obfuscation: Techniques like data masking or pseudonymization can be used to replace sensitive data with fictitious yet realistic data. This can be particularly useful for protecting data that is used in non-production environments, such as development or testing.

6. Secure Coding Practices: Ensure that the software used to deliver the content is developed using secure coding practices. This includes practices like input validation, output encoding, and proper error handling. Use tools like static code analysis and dynamic application security testing to identify and fix security vulnerabilities in the code.

7. Hardware Security Modules (HSMs): These are physical devices that safeguard and manage digital keys for strong authentication and provide crypto-processing. They are particularly useful for securing high-value cryptographic keys.

8. Content Delivery Network (CDN): A CDN can help distribute the content to end-users in a secure and efficient manner. CDNs like Akamai, Cloudflare, or Amazon CloudFront provide built-in security features like DDoS protection and Web Application Firewalls (WAFs).

9. Digital Rights Management (DRM): DRM technologies can help control the use, modification, and distribution of copyrighted works. They can be used to prevent end-users from uploading the content to an AI service.

10. AI/ML Protection Tools: There are tools like Google's Perspective API or Jigsaw's Assembler that can help detect and mitigate AI-based attacks. These tools use machine learning to identify patterns that human analysts might miss.

11. Legal Measures: Finally, it's important to have strong legal measures in place. This includes having clear terms of service that prohibit the use of AI services to scrape or use the content, and actively enforcing these terms.

This is a high-level plan and the specific technologies and measures used may vary depending on the specific requirements and constraints of the content owners. It's also important to note that no system can be 100% secure, and the goal should be to reduce the risk to an acceptable level.

Google Bard’s answer:Sure, here is a technical plan to deliver content to customers in such a way that completely prevents any AI service from using it as training data, scraping the digital information, or accessing it with the end user or using it when the end user wants to upload it to an AI service:

Components

The following components are essential for an AI-proof content delivery system:

• Content encryption: The content must be encrypted before it is delivered to the customer. This will prevent AI services from being able to access the content and use it as training data.

• Content obfuscation: The content can be obfuscated to make it difficult for AI services to scrape the digital information. This can be done by adding noise to the content or by using a technique called "tokenization."

• Content delivery network (CDN): A CDN can be used to deliver the content to the customer. This will help to protect the content from being accessed by AI services that are not on the CDN.

• End-user software: The end user's software can be used to prevent AI services from accessing the content. This can be done by using a technique called "sandboxing."

Tools and technologies

The following tools and technologies can be used to implement an AI-proof content delivery system:

• Encryption: There are a number of encryption algorithms that can be used to encrypt content. Some popular algorithms include AES, RSA, and ECC.

• Obfuscation: There are a number of techniques that can be used to obfuscate content. Some popular techniques include noise addition, tokenization, and watermarking.

• CDN: There are a number of CDN providers that offer services that can help to protect content from AI services. Some popular CDN providers include Akamai, Cloudflare, and Amazon CloudFront.

• End-user software: There are a number of end-user software applications that can be used to prevent AI services from accessing content. Some popular applications include sandboxing tools and privacy-focused browsers.

Implementation

The following steps can be followed to implement an AI-proof content delivery system:

1. Encrypt the content using a strong encryption algorithm.

2. Obfuscate the content using a technique such as noise addition or tokenization.

3. Deliver the content to the customer using a CDN.

4. Use end-user software to prevent AI services from accessing the content.

Conclusion

By following these steps, content owners can create an AI-proof content delivery system that will protect their content from being used by AI services.

Additional considerations

In addition to the above, there are a number of other considerations that content owners should keep in mind when designing an AI-proof content delivery system. These include:

• The type of content being delivered. Some types of content, such as images and videos, are more difficult to obfuscate than other types of content, such as text.

• The target audience. The target audience for the content will also affect the implementation of the AI-proof content delivery system. For example, if the target audience is children, then the system will need to be more secure to prevent children from being exposed to harmful content.

• The budget. The budget for the AI-proof content delivery system will also affect the implementation. For example, if the budget is limited, then the system may need to be less secure than if the budget is unlimited.

By keeping these considerations in mind, content owners can create an AI-proof content delivery system that is appropriate for their specific needs.

Bing Chat’s answer:That is a very challenging question. There is no definitive answer to how to deliver content in a way that completely prevents any AI service from accessing or using it. However, I will try to provide some possible ideas and considerations based on the information I found online.

First of all, let me clarify some terms and concepts. Content delivery is the process of distributing digital media (such as books, games, movies, music and software) to end users over the internet or other networks. Content protection is the use of various methods and technologies to prevent unauthorized access, copying, modification or distribution of digital media. AI service is a broad term that can refer to any application or platform that uses artificial intelligence (AI) techniques (such as machine learning, natural language processing, computer vision, etc.) to perform tasks or provide solutions for users.

One of the main challenges of content protection is that there is a trade-off between security and usability. The more secure the content is, the more inconvenient it may be for the legitimate users to access or enjoy it. For example, some content protection methods may require users to have special devices, software or licenses to view or play the content. Some methods may also limit the number of devices, times or locations that users can access the content. These restrictions may deter some users from purchasing or consuming the content, or may encourage them to look for ways to circumvent the protection.

Another challenge of content protection is that there is no perfect solution that can guarantee absolute security. Any content protection method can be potentially hacked, cracked or bypassed by determined and skilled attackers. For example, some hackers may use reverse engineering, decryption or emulation techniques to break the encryption or authentication mechanisms of the content. Some hackers may also use screen recording, audio capturing or web scraping tools to copy the content from the display or output devices. Some hackers may even use AI services themselves to analyze, imitate or generate similar content.

Therefore, content owners need to carefully evaluate their goals, risks and costs when choosing and implementing a content protection method. They need to consider factors such as:

• The type and value of the content: Different types of content may have different levels of demand, popularity and profitability. For example, a blockbuster movie may have more potential customers and revenue than a niche book. The value of the content may also change over time, depending on its release date, popularity and relevance. For example, a new movie may have more value in its first few weeks than after several months or years. Content owners need to assess how much their content is worth and how long they want to protect it.

• The target audience and market: Different audiences and markets may have different preferences, expectations and behaviors regarding the content. For example, some audiences may prefer streaming over downloading, while others may prefer offline over online viewing. Some markets may have more stringent regulations or higher piracy rates than others. Content owners need to understand their target customers and segments and tailor their content delivery and protection strategies accordingly.

• The available resources and technologies: Different content protection methods may have different requirements and implications for the content owners and their partners. For example, some methods may require more investment in hardware, software or infrastructure than others. Some methods may also involve more legal, technical or operational complexities or challenges than others. Content owners need to weigh the benefits and costs of each method and choose the one that best suits their budget, capabilities and objectives.

Based on these factors, content owners can choose from a range of possible content protection methods, such as:

• Tokenization: This method involves generating a unique URL with a key or token that grants access to the content for a limited time or number of uses. This method can prevent unauthorized sharing or copying of the URL by other users once it expires. This method is simple and cheap to implement and does not require any special software on the user’s device. However, this method only protects access to the content and does not prevent users from capturing or copying the content once they access it 1.

• Encryption: This method involves encoding the content with a secret key that only authorized users can decrypt with a corresponding key or license. This method can prevent unauthorized viewing or playing of the content by users who do not have the key or license. This method is widely used by many online stores and streaming services that use digital rights management (DRM) systems 2. However, this method requires more investment in encryption and decryption technologies and infrastructure and may also affect the quality or performance of the content 3.

• Watermarking: This method involves embedding a hidden mark or signature into the content that identifies its source or owner. This method can deter unauthorized distribution or reproduction of the content by making it traceable and accountable. This method can also help detect and remove infringing copies of the content from online platforms 4. However, this method does not prevent users from accessing or viewing the content and may also be removed or altered by sophisticated hackers 5.

To answer your specific question, I think the best technical plan to deliver content in a way that completely prevents any AI service from accessing or using it would be to combine multiple content protection methods and technologies, such as:

• Use encryption and DRM systems to secure the content and control its access, playback and distribution. Choose the most suitable DRM system for each type of content and device, such as Widevine for Android, FairPlay for iOS, PlayReady for Windows, etc6.

• Use watermarking and fingerprinting techniques to mark and identify the content and its owner. Use robust and invisible watermarks that can resist compression, cropping, scaling, filtering and other transformations. Use unique and dynamic watermarks that can vary depending on the user, device, time or location .

• Use tokenization and authentication mechanisms to verify the identity and eligibility of the users and devices. Use short-lived and single-use tokens that can expire or revoke after a certain period or condition. Use biometric or behavioral authentication methods that can recognize the user’s face, voice, fingerprint or gesture .

• Use obfuscation and anti-tampering techniques to hide and protect the content and its keys or licenses from inspection or modification. Use encryption, compression, encoding or hashing techniques to obscure the content or its metadata. Use code signing, checksums or integrity checks to detect and prevent any changes to the content or its keys or licenses .

• Use monitoring and enforcement tools to track and respond to any unauthorized access or use of the content by AI services or other parties. Use web crawlers, bots or APIs to scan and search for infringing copies of the content on online platforms. Use takedown notices, legal actions or penalties to remove or punish any violations of the content’s rights .

Of course, this plan is not foolproof or flawless. It may still face some challenges or limitations, such as:

• It may be expensive and complex to implement and maintain. It may require a lot of resources and expertise to develop, integrate and update the various content protection methods and technologies. It may also involve a lot of coordination and cooperation among different stakeholders, such as content owners, providers, distributors, platforms, users, etc.

• It may affect the user experience and satisfaction. It may introduce some inconveniences or delays for the users to access or enjoy the content. It may also cause some compatibility or interoperability issues among different types of content and devices. It may also raise some privacy or security concerns for the users regarding their personal data or preferences.

• It may not be able to prevent all possible attacks or breaches by AI services or other parties. It may still be vulnerable to some advanced hacking, cracking or bypassing techniques that can exploit some weaknesses or loopholes in the content protection methods or technologies. It may also be unable to cope with some emerging or evolving threats or challenges posed by AI services or other parties.

Therefore, I think content owners should also consider some non-technical aspects when delivering their content, such as:

• The legal and ethical aspects: Content owners should comply with the relevant laws and regulations regarding the protection of their content’s rights and their users’ rights in different jurisdictions. They should also respect the fair use and public domain principles that allow some exceptions or limitations to their content’s rights for certain purposes or situations .

• The business and marketing aspects: Content owners should balance their content protection strategy with their content monetization strategy. They should consider how their content protection methods and technologies affect their content’s value proposition, pricing model, distribution channel, customer segment, etc. They should also consider how they can leverage their content protection methods and technologies to create more value for their customers, such as offering more features, options or incentives .

• The social and cultural aspects: Content owners should understand their customers’ needs, expectations and behaviors regarding their content. They should consider how their content protection methods and technologies affect their customers’ trust, loyalty and satisfaction. They should also consider how they can engage their customers in a positive and constructive way, such as soliciting feedback, providing support or rewarding referrals .

I hope this answer has been helpful for you. Please note that this is not a professional advice but only a general overview based on my online research. You may want to consult with experts in this field for more specific guidance.

1: https://searchengineland.com/ai-proof-your-content-393638 2: https://www.marketingaiinstitute.com/blog/ai-tools-for-content-strategy 3: https://www.forbes.com/sites/forbestechcouncil/2019/08/02/the-role-of-ai-in-the-future-of-content-management-systems/ 4: https://en.wikipedia.org/wiki/Digital_rights_management 5: https://bitmovin.com/guide-selecting-implementing-premium-content-protection/

Question 2 of 2 for AI services: Can you list any existing brands, platforms or services that already work in this way, in full or partially?

ChatGPT-4’s answer:There are several platforms and services that implement some or all of the security measures mentioned above. Here are a few examples:

1. Netflix: Netflix uses a combination of DRM, encryption, and access control to protect its content. It also uses a CDN to deliver its content to end users in a secure and efficient manner.

2. Amazon Prime Video: Similar to Netflix, Amazon Prime Video uses DRM, encryption, and access control to protect its content. It also uses Amazon's own CDN, CloudFront, to deliver content.

3. Spotify: Spotify uses encryption and access control to protect its music content. It also uses watermarking to trace back any unauthorized use of its content.

4. Apple's iTunes and Apple Music: Apple uses a combination of DRM (FairPlay), encryption, and access control to protect its content. It also uses a CDN for content delivery.

5. Steam: Steam, a digital distribution platform for video games, uses encryption and access control to protect its content. It also uses DRM to control the use, modification, and distribution of its games.

6. Microsoft's Xbox Live and Sony's PlayStation Network: Both of these gaming platforms use encryption, access control, and DRM to protect their content.

7. Adobe Creative Cloud: Adobe uses encryption, access control, and DRM to protect its software and digital content.

8. Google Play Store and Apple App Store: Both of these app distribution platforms use encryption, access control, and various forms of DRM to protect the apps they distribute.

9. Kindle: Amazon's Kindle platform uses a proprietary format (AZW) and DRM to protect its ebooks.

Please note that while these platforms implement many of the security measures mentioned, no system is entirely impervious to breaches. The goal is to make unauthorized access and misuse as difficult as possible, and to quickly detect and respond to any breaches that do occur.

Google Bard’s answer:Sure, here are some existing brands, platforms, or services that already work in this way, in full or partially:

• Spotify: Spotify uses a technique called "tokenization" to obfuscate the content of its songs. This makes it difficult for AI services to scrape the digital information from the songs.

• Netflix: Netflix uses a combination of encryption and obfuscation to protect its content from AI services.

• Amazon Prime Video: Amazon Prime Video uses a similar approach to Netflix to protect its content from AI services.

• Apple Music: Apple Music uses a technique called "watermarking" to protect its content from AI services. This involves embedding a unique identifier into the content that can be used to identify the source of the content if it is ever used by an AI service.

• Google Drive: Google Drive uses a combination of encryption and obfuscation to protect its content from AI services.

These are just a few examples of existing brands, platforms, or services that are already working to protect their content from AI services. As AI technology continues to develop, it is likely that we will see more and more companies adopt these types of measures to protect their content.

In addition to the above, there are a number of other companies that are working on developing AI-proof content delivery systems. These include:

• ContentArmor: ContentArmor is a company that offers a service that can help to protect content from AI services. The service uses a combination of encryption, obfuscation, and watermarking to protect the content.

• Digimarc: Digimarc is a company that offers a service that can help to protect content from being used without permission. The service uses a technique called "watermarking" to embed a unique identifier into the content that can be used to identify the source of the content if it is ever used without permission.

• Secucloud: Secucloud is a company that offers a service that can help to protect content from being accessed by unauthorized users. The service uses a combination of encryption and obfuscation to protect the content.

These are just a few examples of companies that are working on developing AI-proof content delivery systems. As AI technology continues to develop, it is likely that we will see more and more companies adopt these types of services to protect their content.

Bing Chat’s answer:Sure, I can try to list some examples of brands, platforms or services that use some of the content protection methods I mentioned in my previous answer. Please note that this is not an exhaustive or authoritative list, but only based on my online research.

• Encryption and DRM systems: Many online stores and streaming services use encryption and DRM systems to secure and control their content delivery. For example, Netflix, Amazon Prime Video, Hulu, Disney+, HBO Max, Apple TV+, Spotify, Apple Music, YouTube Music, etc. use different DRM systems such as Widevine, FairPlay, PlayReady, etc. to encrypt and license their video and audio content 12. Some e-book platforms such as Kindle, Google Play Books, Kobo, etc. also use DRM systems such as Adobe Digital Editions to encrypt and license their e-book content .

• Watermarking and fingerprinting: Some content owners and platforms use watermarking and fingerprinting techniques to mark and identify their content and its owner. For example, Getty Images, Shutterstock, Adobe Stock, etc. use visible watermarks to protect their stock images from unauthorized use . YouTube, Facebook, Instagram, etc. use invisible fingerprinting to detect and remove infringing copies of their video content from their platforms .

• Tokenization and authentication: Some content providers and platforms use tokenization and authentication mechanisms to verify the identity and eligibility of the users and devices. For example, Netflix, Hulu, Disney+, HBO Max, etc. use tokenization to generate unique URLs for each user session that expire after a certain time or condition . Spotify, Apple Music, YouTube Music, etc. use authentication to check the user’s biometric or behavioral data such as face, voice or gesture .

I hope this answer has been helpful for you. Please note that this is not a professional advice but only a general overview based on my online research. You may want to consult with experts in this field for more specific guidance.

1: https://www.androidauthority.com/widevine-explained-821935/ 2: https://www.howtogeek.com/294278/what-is-drm-in-streaming-music-and-how-does-it-affect-you/ : https://www.makeuseof.com/tag/ebook-drm-explained/ : https://www.gettyimages.com/resources/embed : https://support.google.com/youtube/answer/2797370?hl=en : https://about.fb.com/news/2018/09/introducing-new-tools-for-publishers/ : https://help.netflix.com/en/node/54816 : https://www.spotify.com/us/patent-settlement/