Data Mining Symposium
Who's Mining Your Business: Privacy Infringement and Profits
On Thursday, September 22, 2011, the Thomas M. Cooley Law School hosted its Symposium. The following is a summary of the event. Our speakers discussed Data Mining and the misconceptions inside and outside of the legal field about privacy rights.
Our invited speakers and presentation topics included:
Dr. Andreas Weigend
Andreas Weigend, Ph.D., a Behavior Marketing Expert, former Chief Scientist for Amazon.com, and the author of over 100 scientific papers on the application of machine learning techniques for finance and business problems. He lectures at Stanford University on social data and directs the Social Data lab. His expertise is in social and mobile technologies, and in consumer behavior. An excerpt from the Symposium can be watched here:
Dr. Weigend discussed how in today's increasingly digitized world, consumers are sharing data in unprecedented ways. He pointed out that Social Data has two meanings: (1) the social graph or who is related to whom; and (2) the data sharing of photos, locations, and phone numbers. Dr. Weigend spoke about the "Identity War." He said, "The bridging of the physical and the digital, being in the same photo at the same time, or having physical faces recognized in the digital world is where these wars will be happening. What's private and public is not black and white."
Richard D. De Veaux
Richard D. De Veaux is a Professor of Statistics at Williams College in Massachusetts. He is an applied statistician interested in data-mining methodology and its application to problems in science and industry. He is also a statistics educator interested in understanding how statistical concepts are best communicated.
Professor De Veaux discussed his extensive work in data mining, dating back to a time before it was even labeled as data mining. His focus was to gather the data collected by his clients and make valid predictions in the marketing field. He questioned whether data mining is made up of human intelligence or experimental design. His answer was that it’s all of those things, putting the domain knowledge about your subject together, and that’s data mining.
Dr. Chris Clifton
Dr. Chris Clifton, faculty of computer science at Purdue, works on data privacy, particularly with respect to the analysis of private data. This includes privacy-preserving data mining, data de-identification and anonymization, and limits on identifying individuals from data mining models. He also works more broadly in data mining, including data mining of text and data mining techniques applied to interpretation of heterogeneous information sources.
Dr. Clifton discussed how sharing data increases the risk of unintended disclosure and misuse of that data. There is no regulatory, contractual, or liability framework. He explained the technology that exists in data mining, how it fits within our legal framework, and how we demand of this legal technology to be further developed and used. He suspects that in the commercial market place, people are willing to give all of their information to Google and Facebook for fairly limited services, even though the market place is not going to demand privacy.
Jason Shin is a Michigan lawyer with nearly ten years of experience as a legal counselor and trial attorney for local and national privately held companies, publicly traded companies, as well as start-up companies in numerous industries, including manufacturing, Internet and e-commerce, finance, health, technology, and telecommunications. Mr. Shinn has collaborated with businesses on all aspects of e-commerce and Internet law, including securing and protecting website content and complying with specific Internet laws and regulations (e.g., CAN-SPAM, DMCA, COPPA, FTC regulations, and privacy regulation compliance).
Mr. Shinn spoke about his involvement in the balance of technology and the legal response, and how it is lagging behind the technological capabilities in terms of data mining and data-privacy issues. Mr. Shinn emphasized the importance of data mining in three following points: (1) Self-interests of users creates a digital fingerprint, and it’s later converted into a digital self-portrait; (2) Custodians, the people who create these digital profiles, must understand the rights and obligations they have with the information; and (3) Attorney–Client relationships must be properly handled to address their issues and mitigate the risks.