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Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center [email protected]

Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center [email protected] . Ninety

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Page 1: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center [email protected]

Page 2: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Ninety percent of corporate legal departments, law firms, and government lawyers note that data analytics are applied in their organizations, albeit in limited ways.

Page 3: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

The Legal Services Corporation recommended in 2012 that all states collect and assess data on case progress/outcomes to improve the delivery of legal services.

Page 4: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Data-use policies are prominently displayed on company or government websites, or required a part of a click-through consent for mobile apps and websites.

Page 5: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety
Page 6: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety
Page 7: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Sources… ¡  Electronic discovery

¡  Online lawyer/law firm evaluation/reviews and other activity

¡  Client management/case management tools

¡  Billing

¡  Government records

¡  Social media

¡  Drones

¡  And more…

Page 8: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Hypo #1

¡  Lawyer agrees to e-discovery in litigation defending Client against claims brought by Client’s Competitor. Opposing Counsel proposes a joint search of Client’s electronic records using a vendor selected by Opposing Counsel. The search terms provided seem reasonable, and Opposing Counsel offered a standard clawback agreement that would protect any inadvertently produced information subject to attorney-client privilege and the work product doctrine. Lawyer relies on the Client’s information technology staff to provide full access to the electronic records.

Page 9: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Hypo #2

¡  Law Firm regularly represents companies in intellectual property matters. Law Firm would like to expand its client base, and recently hired a marketing company to assist in this effort.

The marketing company was given access to Law Firm’s digital records in order to learn more about the existing client demographics and to determine potential ways of developing new clients. This information included the nature and outcome of representations, the size and industry of clients, and the timing of the representations, but not specific client names. Law Firm has no official policy about the use of its digital records, other than to require that all lawyers adhere to standard confidentiality requirements. The marketing company provided Law Firm with a data analytics report documenting that Competing Law Firm is regularly searched for more on the internet than Law Firm. The company recommends that Law Firm begin including the name “Competing Law Firm” as a keyword in the implementation of its new advertising campaign service with a major search-engine company.

Page 10: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

A Legal Ethics Agenda for Big Data Analytics

¡ Lawyers/law practices

¡ Bar associations/regulatory bodies

Page 11: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Professional Conduct Rules

Page 12: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Communication ABA Model Rule 1.4

¡ Duty to “consult with the client about the means by which the client’s objectives are to be accomplished;” “keep the client reasonably informed about the status of a matter;” and “promptly comply with reasonable requests for information.”

Page 13: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Competence ABA Model Rule 1.1

¡ Requires that lawyers “keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology.”

Page 14: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Confidentiality ABA Model Rule 1.6

¡ Protects confidentiality of all information relating to the representation of a client, including client data, and Comment 18 urges lawyers to consider state and federal laws on data privacy and notice requirements.

Page 15: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Marketing ABA Model Rules 7.1, 7.2 & 7.3

¡ Rule 7.1 prohibits lawyers from making false or misleading statements about their services. Rule 7.2 governs permissible advertising and Rule 7.3 covers permissible solicitation.

Page 16: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Record Preservation and Retention ABA Model Rules 1.15 & 1.16 ¡ Lawyers hold a duty to maintain

and preserve client records, including data analytics, as well as to deliver them promptly upon request, under Rule 1.15.

¡ Rule 1.16 specifies that upon termination of a representation, the lawyer must promptly return all papers and property to which the client is entitled.

Page 17: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Supervision ABA Model Rule 5.3

¡ A supervising lawyer must ensure that nonlawyers adhere to the lawyer’s professional conduct obligations. Lawyers must provide instruction about ethical obligations, and they are responsible for the nonlawyers’ work product.

Page 18: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Unanswered Ethical Questions…

Page 19: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Access/Ownership

¡ Who owns the original data—the individual source or the holder of the pooled information? Who owns the insights drawn from its analysis? Who should receive access to the data compilation and the results?

Page 20: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Anonymity/Identity

¡ Should all personally identifiable or sensitive information be removed from the data? What protections are necessary to respect individual autonomy? How should individuals be able to control and shape their electronic identity?

Page 21: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Consent

¡ Should individuals affirmatively consent to use of their personal data? Or is it sufficient to provide notice, perhaps with an opt-out provision?

Page 22: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Privacy/Security

¡ Should privacy be protected beyond the professional obligation of client confidentiality? How should data be secured?

Page 23: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Process

¡ How involved should lawyers be in the process of data collection and analysis?

Page 24: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Purpose ¡ Why was the data first collected

from individuals? What is the purpose for the current use? Is there a significant divergence between the original and secondary purposes? If so, is it necessary for the individuals to consent to the secondary purpose? How will unintended consequences be addressed?

Page 25: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Source

¡ What is the source of the data? Did the lawyer collect it directly from clients, or is the lawyer relying upon a third-party source?

Page 26: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Hypo #1

¡  Lawyer agrees to e-discovery in litigation defending Client against claims brought by Client’s Competitor. Opposing Counsel proposes a joint search of Client’s electronic records using a vendor selected by Opposing Counsel. The search terms provided seem reasonable, and Opposing Counsel offered a standard clawback agreement that would protect any inadvertently produced information subject to attorney-client privilege and the work product doctrine. Lawyer relies on the Client’s information technology staff to provide full access to the electronic records.

Page 27: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Hypo #2

¡  Law Firm regularly represents companies in intellectual property matters. Law Firm would like to expand its client base, and recently hired a marketing company to assist in this effort.

The marketing company was given access to Law Firm’s digital records in order to learn more about the existing client demographics and to determine potential ways of developing new clients. This information included the nature and outcome of representations, the size and industry of clients, and the timing of the representations, but not specific client names. Law Firm has no official policy about the use of its digital records, other than to require that all lawyers adhere to standard confidentiality requirements. The marketing company provided Law Firm with a data analytics report documenting that Competing Law Firm is regularly searched for more on the internet than Law Firm. The company recommends that Law Firm begin including the name “Competing Law Firm” as a keyword in the implementation of its new advertising campaign service with a major search-engine company.

Page 28: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

A Legal Ethics Agenda for Big Data Analytics

¡ Lawyers/law practices

¡ Bar associations/regulatory bodies

Page 29: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Read more…

¡ Renee Knake, How Big Data Analytics are Changing Lawyer Ethics, BLOOMBERG LAW, August 10, 2016

Page 30: Legal Ethics for Big Data - Amazon S3 · Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center rknake@uh.edu . Ninety

Legal Ethics for Big Data Renee Knake Professor of Law & Doherty Chair in Legal Ethics University of Houston Law Center [email protected]