Data Mining is the business of finding useful information in large data sets. It is also a way of spying on people, a tool for attacking privacy & ultimately Free Speech. Political power is the raison d'être.
The Wiki's article tells us that it is about looking for patterns. It is far more. Bruce Schneier, the well known security specialist let the cat out of that particular bag in his Crypto-gram of 15 August 2019 by telling us about Palantir's Surveillance Service for Law Enforcement. It means that your privacy has been destroyed. Given that Palantir achieved a $41 billion valuation you might think that there are people out there with money and power who are very nosey.
Doctor Schneier's next piece tells us that the FBI Wants More. Recall that the FBI is the bunch of comedians who brought us the Ruby Ridge Massacre and the Waco Massacre. They then investigated themselves and found themselves not guilty. The FBI is like the CIA, part of the Deep State, the criminal conspirators who attempted to subvert Democracy by impeaching the President using a fraudulent investigation.
Palantir's Surveillance Service for Law Enforcement
[2019.07.15] Motherboard got its hands on Palantir's Gotham user's manual, which is used by the police to get information on people:The Palantir user guide shows that police can start with almost no information about a person of interest and instantly know extremely intimate details about their lives. The capabilities are staggering, according to the guide:
- If police have a name that's associated with a license plate, they can use automatic license plate reader data to find out where they've been, and when they've been there. This can give a complete account of where someone has driven over any time period.
- With a name, police can also find a person's email address, phone numbers, current and previous addresses, bank accounts, social security number(s), business relationships, family relationships, and license information like height, weight, and eye color, as long as it's in the agency's database.
- The software can map out a person's family members and business associates of a suspect, and theoretically, find the above information about them, too.
All of this information is aggregated and synthesized in a way that gives law enforcement nearly omniscient knowledge over any suspect they decide to surveil.
Read the whole article -- it has a lot of details. This seems like a commercial version of the NSA's XKEYSCORE. It is at Leaked Palantir 'Gotham' user manual shows how fast police and government can grab your info from Boing Boing.
FBI Wants More:-
The FBI wants to gather more information from social media. Today, it issued a call for contracts for a new social media monitoring tool. According to a request-for-proposals (RFP), it's looking for an "early alerting tool" that would help it monitor terrorist groups, domestic threats, criminal activity and the like.The tool would provide the FBI with access to the full social media profiles of persons-of-interest. That could include information like user IDs, emails, IP addresses and telephone numbers. The tool would also allow the FBI to track people based on location, enable persistent keyword monitoring and provide access to personal social media history. According to the RFP, "The mission-critical exploitation of social media will enable the Bureau to detect, disrupt, and investigate an ever growing diverse range of threats to U.S. National interests."
Data Mining ex Wiki
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.[1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use.[1][2][3][4] Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.[5] Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.[1] The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the effectiveness of a marketing campaign, regardless of the amount of data; in contrast, data mining uses machine-learning and statistical models to uncover clandestine or hidden patterns in a large volume of data.[6]The term "data mining" is in fact a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself.[7] It also is a buzzword[8] and is frequently applied to any form of large-scale data or information processing (collection, extraction, warehousing, analysis, and statistics) as well as any application of computer decision support system, including artificial intelligence (e.g., machine learning) and business intelligence. The book Data mining: Practical machine learning tools and techniques with Java[9] (which covers mostly machine learning material) was originally to be named just Practical machine learning, and the term data mining was only added for marketing reasons.[10] Often the more general terms (large scale) data analysis and analytics – or, when referring to actual methods, artificial intelligence and machine learning – are more appropriate.
The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining, sequential pattern mining). This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics. For example, the data mining step might identify multiple groups in the data, which can then be used to obtain more accurate prediction results by a decision support system. Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, but do belong to the overall KDD process as additional steps.
The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These methods can, however, be used in creating new hypotheses to test against the larger data populations.
Palantir Technologies ex Wiki
Palantir Technologies is a private American software company that specializes in big data analytics. Headquartered in Palo Alto, California, it was founded by Peter Thiel, Nathan Gettings, Joe Lonsdale, Stephen Cohen, and Alex Karp. The company's name is derived from The Lord of the Rings: a palantír is an artifact used to communicate with or see faraway parts of the world.The company is known for three projects in particular: Palantir Gotham, Palantir Metropolis and Palantir Foundry. Palantir Gotham is used by counter-terrorism analysts at offices in the United States Intelligence Community (USIC) and United States Department of Defense, fraud investigators at the Recovery Accountability and Transparency Board, and cyber analysts at Information Warfare Monitor, while Palantir Metropolis is used by hedge funds, banks, and financial services firms.[3][4] Palantir Foundry is used by corporate clients such as Morgan Stanley, Merck KGaA, Airbus, and Fiat Chrysler Automobiles NV.[5] Palantir's original clients were federal agencies of the USIC. It has since expanded its customer base to serve state and local governments, as well as private companies in the financial and healthcare industries.[6] Karp, Palantir's chief executive officer, announced in 2013 that the company would not pursue an IPO, as going public would make "running a company like ours very difficult".[7] However, on October 18, 2018, the Wall Street Journal reported that Palantir was considering an IPO in the first half of 2019 following a $41 billion valuation.[8]
The company was valued at $9 billion in early 2014, with Forbes stating that the valuation made Palantir "among Silicon Valley's most valuable private technology companies".[7] As of December 2014, Thiel was Palantir's largest shareholder.[7] In January 2015, the company was valued at $15 billion after an undisclosed round of funding with $50 million in November 2014.[9] This valuation rose to $20 billion in late 2015 as the company closed an $880 million round of funding.[2] Palantir has never reported a profit, and in 2018 Morgan Stanley valued the company at $6 billion.[10]
Peter Thiel ex Wiki
Homosexual German, founded PayPal, very rich.