Artificial intelligence (AI) is transforming industries from healthcare and finance to retail and creating entirely new sectors that didn’t exist just a few years ago. And we’ve only hit the tip of the iceberg of what’s possible. Yet, as demand for data to power these systems continues to grow, it’s critical that we consider how to source it accurately and ethically.
The Web Fuels Modern AI
Most today’s AI systems are being designed to interact with users to autonomously complete tasks or make decisions. These intelligent agents are founded on large language models (LLMs) that read, write, and reason using human language. LLMs, like GPT-4, are created by training massive neural networks on huge amounts of text and image data containing billions (or even trillions) of parameters to make predictions.
Publicly available web data has fueled this AI revolution. To make these models useful for practical applications, they need to be supplied with up-to-date data constantly being pulled from websites. All major generative AI models have been trained using web scraping from existing articles, forums, niche community sites, etc.
These “AI crawlers” which focus specifically on collecting data to train task-specific LLMs are precisely why startups are turning to a new breed of proxy-based products to source high-quality datasets.
The Case for Proxies
AI-optimized proxies have a wide range of uses that offer several positive benefits to consumers and businesses alike. They offer significant advantages for internet users by enhancing privacy, security, and online freedom. However, aggressive AI crawlers are increasingly overloading website publishers and open-source communities, frustrating operators.
While there are many upsides for a brand to open its site content to crawlers, there is also a risk when bad actors gain access. Misuse by aggressive AI crawlers can cause service instability and downtime, higher bandwidth costs, and even (unintentional) DDoS attacks.
To protect their infrastructure and ensure a fair experience for their users, most sites now use a combination of rate limiting, bot detection, and CAPTCHAs to block automated crawlers and bots. This has become the biggest challenge of web data extraction, hence the need for tools such as proxy servers.
The easiest way to prevent IP blocks is to use high-quality residential proxies. Proxies allow agents to route their traffic through different IP addresses, appearing as human visitors rather than bots. This helps avoid blocks and ensures the agent gets access to the content.
It’s not just about avoiding detection, however, it’s also about context. Websites often display different content depending on a visitor’s location. Prices, search results, and even availability can change between countries or cities. Premium residential proxies support various online business activities that go beyond web scraping, including market intelligence, ad verification, brand protection, and social media management.
Taking the Ethical Approach
Ethical and legal considerations are crucial when scraping data for AI agents. While scraping publicly accessible web data is generally permitted, content behind authentication or paywalls and personal information should be excluded.
Data ethics extends beyond compliance and legal requirements such as GDPR (General Data Protection Regulation). Ethical data collection is a moral responsibility that ensures data privacy protection, prevents mishandling of sensitive information, and upholds fairness and transparency standards.
Unethical data gathering methods such as collecting or using information without consent violate the principles of fairness and transparency. Some companies are even more deceptive by misleading users who think they are simply using a benign app like a fitness tracker or taking a survey as a promotional offer when, in reality, they collect location data, personal information, and other data through various means like GPS, cookies, analytics services, and app permissions.
While there are plenty of unethical data gathering methods, these bad actors don’t represent the entire industry. Many crawler agents promote fair, transparent, and sustainable practices.
Yet, some industry watchdogs are seeking solutions to shield content from AI bot scraping. IETF’s AI Preferences Working Group (AIPREF) is laying the groundwork for a universal standard that will signal to AI systems what is and isn’t off limits.
Ultimately, the responsibility for curbing the negative impacts of AI crawlers lies with two key players: the crawlers themselves and the proxy service providers. While AI crawlers can voluntarily limit their activity, proxy providers can impose rate limits on their services, directly controlling how frequently and extensively websites are crawled.
Scraping Best Practices for AI agents
We’re still in the early stages of AI agent development, and the demand for web data is only going to increase. The challenge is to meet this growing need while minimizing disruption to the web.
Ethical web scraping aims for a sustainable approach that respects website operations. When executed correctly, it can be a mutually beneficial practice for both website owners and those who utilize the data collected.
Here are a few best practices to follow:
- Don’t overload websites with too many requests
- Respect the robots.txt file and reasonable rate limits
- Avoid collecting personal or sensitive information
- Honor clear “no scraping” signals when they exist
Web data is essential for AI agents
Web data is the foundation for AI agents. Without it, they’re limited to outdated training data and rendered useless. With it, they can solve problems in real time, respond to new developments, and deliver meaningful value.
When bots can read web pages, it opens a ton of possibilities – think about asking Siri or Alexa for directions, getting tailored suggestions on Netflix or Amazon, or even your robot vacuum finding its way around the house, just on the scale of the entire internet.
However, quality data doesn’t just appear. It takes infrastructure like proxies, intelligent scrapers, and reliable data pipelines to ensure it’s gathered responsibly and sustainably.
If you’re building AI agents, don’t underestimate the importance of their information sources. The web offers the most current, high-quality data available. But accessing it effectively requires the right tools and an ethical mindset.
