Hello, curious minds! I’ve got exciting news: I just left my job, which means I can finally pour more time into brewing fresh AI goodness on the blog. If you’d like a quick sip of my favorite AI “flavors” before today’s feature, just click here to sample the menu—and don’t forget to subscribe so you never miss a cup!
🌿 Brewing Thought Before the First Sip
Artificial intelligence is evolving faster than ever — shaping how we create, connect, and even think. But behind this technological aroma lies a strong, bitter note: data. Every algorithmic flavor of AI is steeped in it — collected, filtered, and brewed from the web itself. What happens, though, when this endless brewing of information starts to boil over into our privacy?
☕ First Sip into the Great Scrape
This piece, adapted from Daniel J. Solove and Woodrow Hartzog’s article “The Great Scrape: The Clash Between Scraping and Privacy,” explores the fundamental tension between large-scale data collection (known as scraping) and privacy law. The authors argue that the rapid expansion of artificial intelligence has ushered in what they call “the great scrape,” a moment that demands a “great reconciliation” with privacy regulation.
The article illustrates how scraping is inherently incompatible with universal privacy principles such as the Fair Information Practice Principles (FIPPs), and how existing legal battles—centered around the Computer Fraud and Abuse Act (CFAA) and property-based torts—focus largely on corporate interests rather than the privacy rights of individuals. Rejecting the notion that publicly available data eliminates privacy expectations, Solove and Hartzog propose reframing scraping as a form of routinized surveillance and regulating it as a privilege that should only be exercised in the public interest, rather than banning it outright.
☕ As the Brew Deepens: Inside the Scraping Wars
Before diving into the privacy debate, Solove and Hartzog take us through how scraping actually works — from the early days of polite web crawlers to the rise of AI-driven bots that can vacuum up personal data at lightning speed. They show how scraping has evolved from a useful research tool into a massive, automated industry, sparking what they call the Scraping Wars — a two-front battle fought in courts and in code.
On the legal front, landmark cases like hiQ v. LinkedIn and Van Buren v. United States reveal how U.S. courts still struggle to define “unauthorized access,” often prioritizing corporate disputes over individual privacy. On the technological front, websites are fighting back with digital shields — CAPTCHAs, IP bans, and rate limits — while scrapers invent new tricks to sneak past them.
Even the emergence of a scraping marketplace, where companies like OpenAI now pay for licensed data, hasn’t solved the underlying problem: the people whose data fuels these deals are still left out of the conversation.
☕ When Privacy Meets the Great Scrape
After mapping the legal and technical battlefield, Solove and Hartzog turn to the heart of the conflict — the collision between scraping and the universal principles of privacy law. They argue that large-scale data extraction simply can’t coexist with the Fair Information Practice Principles (FIPPs), which form the backbone of data protection worldwide.
Scraping breaks nearly every privacy rule in the book: it’s rarely fair or transparent, ignores consent, collects data without clear purpose, and makes security meaningless when anyone can harvest information with a bot. Even more troubling, scraping undermines individuals’ ability to control their own data — once extracted, it’s out of context, out of reach, and out of their hands.
The authors also challenge the comfortable myth that “public information” equals free-for-all data. Just because something is online doesn’t mean it’s fair game. People may share details publicly, but they don’t expect them to be endlessly mined, repurposed, and reassembled by machines. Citing court cases like Carpenter v. United States, they emphasize that public visibility doesn’t erase privacy. In a world overflowing with personal data, privacy laws must evolve to protect not just secrecy — but dignity, context, and control.
☕ The Last Drop: Brewing a Balance Between Innovation and Privacy
As the cup nears its end, Solove and Hartzog leave us with a sobering aftertaste — we are living through what they call a scraping epidemic. Data is being scooped, mined, and monetized on an unprecedented scale, often without consent, transparency, or accountability. The internet, once imagined as a space for open knowledge, is now being ruthlessly harvested to feed the insatiable appetite of artificial intelligence.
Courts have yet to brew a clear legal recipe: decisions swing between tolerance and restriction, leaving companies, users, and regulators in a fog of uncertainty. Laws that should protect individuals often end up defending corporate interests instead, assuming that “publicly available” means “free for the taking.” The authors push back against this myth, reminding us that just because data is visible doesn’t mean it’s voluntary fuel for AI.
Solove and Hartzog argue that personal data online isn’t free—it’s simply unprotected. They call for a new, more thoughtful legal blend: one that acknowledges AI’s potential but refuses to let innovation justify exploitation. Banning scraping entirely would stifle progress, but letting it run wild corrodes trust and privacy.
☕ Perhaps the real question isn’t how we brew data — but who we brew it for.
resource: "The Great Scrape: The Clash Between Scraping and Privacy" by Daniel J. Solove and Woodrow Hartzog