Description
"Data scraping" or "web scraping" is the automated finding and extraction of data from websites and other online sources. Data scraping is used for marketing, research, sales insights, academia, and archivists. Scraping is now supercharged by algorithms designed to derive "intelligence" from massive datasets of scraped data and 'learn as they go' to improve the algorithms' overall performance.
Numerous lawsuits and regulatory actions challenge the legality of web scraping, particularly the 'training' of generative AI systems using scraped data. Many times, the source of data sets used for AI system development have unknown provenance, complicating risk management efforts. Increasing attention to risks of minors and other sensitive data use and the implications of automated processing compound risk decision making.
Whether engaged in scraping or developing AI using scraped data, assessing the legality of web scraping involves untangling overlapping privacy, AI, consumer protection, contracting, tort, and other laws, as well as active monitoring of case law and regulatory activities.
Listen as our authoritative panel explores the current web scraping legal landscape and provides practical risk management tips.
Presented By
Mr. Friel is a thought leader in digital media, intellectual property, data privacy and protection, and consumer protection law, with over three decades of relevant experience to address the intersection of law and technology.
Having served as a general counsel for several years in the late 1990s before returning to private practice, he has the necessary expertise to advise clients on making practical and informed business decisions and help companies and entrepreneurs navigate the complex opportunities created by disruptive technology. With his in-house and private practice experience, Mr. Friel assists clients with creating data inventories, and information governance and data privacy and security programs. He has been helping shape law and public policy regarding digital media since he was the Sherwood Shafer Fellow at the American Civil Liberties Union from 1992-1994, addressing the potential benefits and risks of the then emerging Internet, and has made the evolution of data technologies, and corresponding regulation, the focus of his legal practice.
Ms. Jacobson is a partner in the Data Privacy, Cybersecurity & Digital Assets Practice. She offers practical and tactical counsel on privacy and cybersecurity compliance strategies, data breach response, technology transactions and marketing initiatives for national and multinational organizations. Ms. Jacobson assists clients with the design and development of privacy-sensitive policies for the collection and use of personal data. She regularly advises businesses on the privacy and cybersecurity aspects of environmental, social and governance (ESG) programs, ethical data use, machine learning and artificial intelligence, vendor contracting and management and business sales, combinations and acquisitions.
Ms. Ricci is responsible for providing advice on AI, privacy operations, technology contracts and secondary market transactions. BECU is currently the country’s fifth-largest credit union, with nearly 1.4 million members and $29 billion in assets. Ms. Ricci was formerly the chief legal officer at two prior tech companies and one financial services company and has held legal, risk and business roles at large financial institutions. The opinions expressed in this CLE presentation are the presenter’s own and do not reflect the view of BECU.
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This 90-minute webinar is eligible in most states for 1.5 CLE credits.
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Date + Time
- event
Wednesday, October 8, 2025
- schedule
1:00 p.m. ET./10:00 a.m. PT
I. Introduction to data scraping
II. Data scraping and AI development
III. Data scraping and privacy and data protection laws
IV. Data scraping and AI laws
V. Contracting for risk management
VI. Actionable takeaways
The panel will discuss these and other key issues:
- What are the privacy and data protection implications of web scraping?
- How do AI laws impact scraping?
- How can organizations minimize liability under privacy laws when using scraped data with AI systems?
- What steps can companies take to protect against unauthorized scraping?
- How can organizations mitigate their exposure to web scraping risks by strengthening contractual terms with third parties?
