Page 50 - FIGI - Big data, machine learning, consumer protection and privacy

Capital Systems LLC, Civil No. 1:08-CV-1976-BBM-RGV, Stipulated Order for Permanent Injunction and Other Equitable
Relief Against Defendant CompuCredit Corporation, https:// www .ftc .gov/ sites/ default/ files/ documents/ cases/ 2008/
12/ 081219compucreditstiporder .pdf.
22 See generally, World Bank, New Forms of Data Processing Beyond Credit Reporting: Consumer and Privacy Aspects,
2018; and Responsible Finance Forum, Opportunities and Risks in Digital Financial Services: Protecting Consumer Data
and Privacy, 2017.
23 This paper does not cover all data privacy issues, or all consumer protection issues that arise in relation to personal data.
Nor does this paper cover all aspects of big data and machine learning. Many outputs of these techniques are general to
society and are useful for health, education and other policies, but do not have a direct impact through decisions made
about specific individuals. As a result, some rights and obligations are explored in more detail than others, focusing on
where big data and machine learning pose particular challenges to data privacy and consumer protection.
24 Harry Surden, Machine Learning and the Law, 89 WASH. L. REV. 87, 88 (2014).
25 F. Rosenblatt, Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain, Psychological
Review, Vol 65, No. 6, 1958 http:// citeseerx .ist .psu .edu/ viewdoc/ download ?doi = 10 .1 .1 .335 .3398 & rep = rep1 & type = pdf
26 Commonly known examples are IBM Watson, Google/Deepmind Alphago, Apple Siri and Amazon Alexa, all of which
rely on machine learning to advance their service for the user.
27 Peter Stone et al., Stanford Univ., Artificial Intelligence and Life in 2030: Report of the 2015-2016 Study Panel 50 (2016),
https:// ai100 .stanford .edu/ sites/ default/ files/ ai _100 _report _0831fnl .pdf.
28 Doug Laney, 3D Data Management: Controlling Data Volume, Velocity and Variety, Metra Group Research Note (2001)
6.
29 IBM, The Four V’s of Big Data (2014), http:// www .ibmbigdatahub .com/ infographic/ four -vs -big -data; Viktor Mayer-
Schönberger and Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work and Think (John
Murray 2013).
30 For example, Australia’s 2015 data retention law requires telecommunications operators and ISPs to retain metadata
about communications for two years to assist law enforcement agencies in crime and terrorism investigation.
31 The existing ePrivacy Directive applies to emails and text messages (SMS). The new ePrivacy Regulation applies more
broadly, covering data created or processed by newer forms of electronic communication including machine-to-
machine communication, internet telephony and internet access services.
32 This example is drawn from a cooperation agreement between a leading mobile network operator and a leading bank.
The agreement is on file with the author. The names have been kept confidential.
33 Reuben Binns, Ulrik Lyngs, Max Van Kleek, Jun Zhao, Timothy Libert, Nigel Shadbolt, Third Party Tracking in the Mobile
Ecosystem, arXiv: 1804 .03603v3 [cs.CY] 18 Oct 2018, https:// arxiv .org/ pdf/ 1804 .03603 .pdf; Aliya Ram, Aleksandra
Wisniewska, Joanna S. Kao, Ændrew Rininsland, Caroline Nevitt, How smartphone apps track users and share data,
Financial Times, 23 October 2018, https:// ig .ft .com/ mobile -app -data -trackers/ .
34 ZwillGen, Alternative Data: Best Practices, presented at the Privacy and Security Forum in Washington DC, 2018.
35 McKinsey estimated in 2014, “today’s car has the computing power of 20 personal computers, features about 100
million lines of programming code, and processes up to 25 gigabytes of data an hour.” What’s Driving the Connected
Car, MCKINSEY (Sept. 2014), https:// www .mckinsey .com/ industries/ automotiveand -assembly/ our -insights/ whats
-driving -the -connected -car.
36 Artificial Intelligence, Robotics, Privacy and Data Protection, 38th International Conference of Data Protection and
Privacy Commissioners, 2016, https:// edps .europa .eu/ sites/ edp/ files/ publication/ 16 -10 -19 _marrakesh _ai _paper _en .pdf.
37 GDPR, Article 4(4) defines “profiling” as “any form of automated processing of personal data consisting of the use
of personal data to evaluate certain personal aspects relating to a natural person, in particular to analyze or predict
aspects concerning that natural person's performance at work, economic situation, health, personal preferences,
interests, reliability, behaviour, location or movements.”
38 https:// www .compare .com/ .
39 https:// www .betterment .com/ .
40 https:// www .wealthfront .com/ .
41 https:// walnut .ai/ en/ .
42 https:// www .rentec .com/ Home .action ?index = true.
43 https:// www .quora .com/ Why -are -machine -learning -neural -networks -and -other -AI -approaches -for -instance -not -more
-widely -used -in -stock -market -predictions.

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