Protecting IP: Women and theft of their work

Several notable women have produced works that grew booming cultural phenomenons. Such success invites attempts at Ip theft, and several notable female creators have used the law to protect their property.

Gayle Lynds utilized standard US copyright registration via her publishers (St. Martin's Press/Berkley Books). Because she heavily researched the real CIA tradecraft detailed in her work, she relied on strict nondisclosure agreements (NDAs) with her intelligence sources to keep her plots from leaking before publication. While no public plagiarism lawsuits followed, but early in her career, advance reading copies (ARCs) of her manuscripts were frequently targeted by gray-market book pirates who tried to scan and distribute digital copies online before the official release dates.

Stella Rimington’s biggest threat was the British Government and state apparatus itself, rather than a traditional copycat author. As the former head of MI5, her intellectual property was legally bound by the UK Official Secrets Act. When she tried to publish her memoirs, MI5 and the government aggressively tried to block and heavily redact it, fearing she would compromise state secrets. To protect her fictional Liz Carlyle thrillers, she had to submit her manuscripts to a strict government clearance filter to prove her spy craft was purely fabricated and not leaked classified data.

Lauren Wilkinson & Phoebe Waller-Bridge, both relied on heavy-duty intellectual property management teams to license their books/characters for television, and both had to face prolonged corporate friction over IP control for their texts. Luke Jennings (creator of the Villanelle novellas that Phoebe Waller-Bridge adapted into Killing Eve) publicly complained that the television producers completely disregarded his creative control over the characters by killing off the lead in the finale, prompting him to use his legal ownership of the print IP to continue her story independently on Substack.

Today, women protecting their IP use a combination of legal tech, anti-scraping code, and modern watermarking to stop AI models and digital pirates from ripping them off.

1. Hardening the Code (Anti-AI Defense) [1]

• AI Bot Blocks: Deploying lines of code in their website registries (like robots.txt directives specifically blocking GPTBot or CCBot) to legally and technically turn away AI scrapers.
  

• Data Poisoning (Nightshade/Glaze): Digital artists use invisible pixel-altering software before posting online. If an AI scrapes the image, the hidden code "poisons" the AI's training data, wrecking its ability to copy the style.
  

2. Digital Provenance (C2PA Standards) [2]

For visual and multimedia creators, the frontier is Content Credentials (backed by the C2PA standard). Devices and editing software inject an unalterable, cryptographically signed metadata footprint into the file at the moment of creation. If an automated scraper or deepfaker modifies the file, the cryptographic chain breaks instantly, flagging the work as altered or unauthorized.

3. Automated Legal Dragnets [3]

Authors use automated SaaS brand-protection platforms (like Red Points or Corsearch). These systems deploy 24/7 AI web-crawlers across digital marketplaces, pirate sites, and social media. The second they spot a stolen manuscript, a copycat cover design, or an unauthorized audiobook voice-clone, the system instantly fires off automated DMCA takedown notices without needing a human lawyer.

4. Direct Licensing Deals [4]

For high-profile authors, protection means bypassing the open web entirely. They restrict their new IP to walled-garden platforms (like Kindle Enterprise or sub-networks with strict digital rights management) and sign direct licensing or collective licensing agreements that explicitly force AI companies to pay for data use upfront.

References: [1] Luo, H., Li, L. & Li, J. (2025). Digital Watermarking Technology for AI-Generated Images: A Survey. Mathematics 13(4). https://doi.org/10.3390/math13040651 [2] (2026). Meta Seal: State-of-the-Art Open Source Invisible Watermarking. Meta AI Research. https://facebookresearch.github.io/meta-seal/

[3] Seng, D. (2021). COPYRIGHTING COPYWRONGS: AN EMPIRICAL ANALYSIS OF ERRORS WITH AUTOMATED DMCA TAKEDOWN NOTICES. Santa Clara High Technology Law Journal 37(2), pp. 119-150. https://doi.org/10.2139/ssrn.3570192

[4] (December 10, 2025). Exclusive: New platform aims to stop AI from using creators' work without permission. Axios. https://www.axios.com/2025/12/10/ai-creators-rights-axm