Social Impacts of Data Mining
2004/12/30
Outline
•Is data mining a hype or a persistentgrowing business?
•Is data mining merely managers’ businessor everyone’s business?
•Is data mining a threat to privacy and datasecurity?
•Trends in data mining
Is data mining a hype or apersistent growing business?
•Life cycle of technology adoption
Is data mining a hype or apersistent growing business?
•At what stage is data mining?
•Integration of data mining into existingbusiness technology
–Database system
–OLAP system
–User security
–Inventory and order management system
–Product management
Is data mining merely managers’business or everyone’s business?
•Data mining will surely help company executivesa great deal in understanding the market andtheir business.
•Data mining will become increasingly availableto everyone.
–What could I do at home with data mining?
–Do I have to understand the inside of a data miningsystem or the tricks of data mining algorithms in orderto do data mining?
Is data mining a threat to privacyand data security?
•Like any other technology, data mining can beused for good or bad.
–When I provide a company with information aboutmyself, are these data going to be used in ways Idon’t expect?
–Will the data be sold to other companies?
–Can I find out what is recorded about me?
–How can I find out which companies have informationabout me?
–Do I have the right or the means to refuse companiesto use the profiling information they have about me?
Is data mining a threat to privacyand data security?
•Are there any means set up by which I cancorrect any errors in the profile data recordedabout me? What if I want to erase, complete,amend, or update the data?
•Will the information about me be “anonymized,”or will it be traceable to me?
•How secure are the data?
•How accountable is the company who collects orstores my data, if these data are stolen ormisused?
Trends in data mining
•Application exploration
•Scalable data mining methods
•Integration of data mining with database system,data warehouse systems, and web databasesystems
•Standardization of data mining language
•Visual data mining
•New methods for mining comlex types of data
•Web mining
•Privacy protection and information security indata mining