What Does Information Governance Mean To An E-Discovery Lawyer?
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1 What Does Information Governance Mean To An E-Discovery Lawyer? ARMA Northern New Jersey Chapter Meeting Florham Park, N.J. April 23, 2014 Jason R. Baron, Esq. Information Governance and ediscovery Group Drinker Biddle & Reath LLP Washington, D.C Jason R. Baron 2014
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3 Information Governance Defined Information governance means an organization s coordinated, interdisciplinary approach to satisfying compliance requirements and managing information risks while optimizing information value. As such, Information Governance encompasses and reconciles the various legal and compliance requirements and risks addressed by different information-focused disciplines, such as records and information management, data privacy, information security, and e-discovery. Source: The Sedona Conference Commentary on Information Governance (Dec. 2013) Drinker Biddle & Reath, 2014
4 4
5 We have entered the era where Big Data is. 5
6 The World Has Changed We are not just managing thousands or millions of paper files We are at an inflection point in history in terms of data volume IDC Report: 1800 new exabytes this year (1 exabyte=data equivalent of 50,000 yrs of continuous movies) Open data policies vs. the iceberg : a vast amount of information is hidden underneath the web how is it to be reliably preserved and accessed?
7 Information governance is needed in a world where % of enterprise data is unstructured - 60% of documents are obsolete - 50% of documents are duplicate - 80% documents are not retrieved by traditional search
8 Reality: The era of information inflation and Big Data in litigation has just begun. Lehman Brothers Investigation 350 billion page universe (3 petabytes) Examiner narrowed collection by selecting key custodians, using dozens of Boolean searches Reviewed 5 million docs (40 million pages using 70 contract attorneys) Source: Report of Anton R. Valukas, Examiner, In re Lehman Brothers Holdings Inc., et al., Chapter 11 Case No (U.S. Bankruptcy Ct. S.D.N.Y. March 11, 2010), Vol. 7, Appx. 5, at 8
9 My own trek. From the tobacco litigation to Sedona (a mythical place not depicted here) To NIST, to found the TREC Legal Track And now, applying what we have learned in ediscovery to the information governance space 9
10 Emerging New Strategies: Predictive Analytics Improved review and case assessment: cluster docs thru use of software with minimal human intervention at front end to code seeded data set Slide adapted from Gartner Conference June 23, 2010 Washington, D.C. 10
11 Defining predictive coding or TAR A process for prioritizing or coding a collection of electronic documents using a computerized system that harnesses human judgments of one or more subject matter experts on a smaller set of documents and then extrapolates those judgments to the remaining document population. Also referred to as supervised or active machine learning, computer-assisted review or technology-assisted review Source: Adapted from Grossman-Cormack Glossary of Technology Assisted Review, v. 1.0 (Oct 2012) 11
12 Judicial endorsement of predictive analytics in document review by Judge Peck in da Silva Moore v. Publicis Groupe (SDNY Feb. 24, 2012) This opinion appears to be the first in which a Court has approved of the use of computer-assisted review.... What the Bar should take away from this Opinion is that computer-assisted review is an available tool and should be seriously considered for use in large-data-volume cases where it may save the producing party (or both parties) significant amounts of legal fees in document review. Counsel no longer have to worry about being the first or guinea pig for judicial acceptance of computer-assisted review... Computer-assisted review can now be considered judiciallyapproved for use in appropriate cases. 12
13 The da Silva Moore Protocol Supervised learning Random sampling Establishment of seed set Issue tags Iteration Random sampling of docs deemed irrelevant 13
14 A New Era of Government [P]roper records management is the backbone of open Government. President Obama s Memorandum dated November 28, 2011 re Managing Government Records governmentrecords 14
15 Archivist/OMB Directive M-12-18, Managing Government Records Directive, dated 8/24/12: 1.1 By 2019, Federal agencies will manage all permanent records in an electronic format. 1.2 By 2016, Federal agencies will manage both permanent and temporary records in an accessible electronic format. 15
16 is still the 800 lb. gorilla of ediscovery 16
17 Beyond text messaging, social media, etc. 17
18 Moving to the Cloud for with Embedded RM/Autocategorization 18
19 Process Optimization Problem: The transactional toll of user-based recordkeeping schemes ( as is RM) 19
20 . and the need for better, automated solutions. 20
21 The demise of RM. John Mancini, President of AIIM: If by traditional records management you mean manual systems even if they are computerized then I would say traditional records management is dead. The idea that we could get busy people to care about our complicated retention schedules, and drag and drop documents into folders, and manually apply metadata document by document according to an elaborate taxonomy will soon seem as ridiculous as asking a blacksmith to work on a Ferrari. 21
22 RM wish list for RM s easy button : the elusive goal of zero extra keystrokes to comply with RM requirements (capture) A technology app that automatically tags records in compliance with RM policies and practices (categorize) Supervised learning RM with minimal records officer or end user involvement (learn) Rule-based and role-based RM Advanced search 22
23 NARA s Capstone Policy: The Path Forward archiving in short term, synced to existing proprietary software on system Designation of key senior officials as creating permanent records, consistent with existing records schedules Additional designations of permanent records by agency component Smart filters/categorical rules built in based on content, to the extent feasible to do Non-senior official records and non-tagged records designated as temporary to be held for set retention period. 23
24 Capstone Officials Capstone officials may include: Officials at or near the top of an agency or an organizational subcomponent Capstone accounts Key staff accounts Key staff members that may be in positions that create or receive presumptively permanent records Other accounts Other accounts 24
25 How To Avoid A Train Wreck With Archiving. Capture But Utilize Records Management! 25
26 The Coming Age of Dark Archives (and the inability to provide access unless we have smart ways of extracting signal from noise) 26
27 Homage to Carl Linnaeus ( ) 27
28 Linnaean classification of the animal kingdom Kingdom: Animalia Phylum: Chordata Subphylum: Vertebrata Superclass: Tetrapoda Class: Mammalia Subclass: Theria Infraclass: Eutheria Cohort: Unguiculata Order: Primata Suborder: Anthropoidea Superfamily: Hominoidae Family: Hominidae Subfamily: Homininae Genus: Homo Subgenus: Homo (Homo) Specific epithet: sapiens 28
29 Which category? 29
30 Information Governance / Records Analytics Can advanced analytics techniques and technologies, including Auto-Categorization, Auto-redaction, Autoindexing, Auto-translation, etc., be applied and leveraged by Records Managers/Information Governance types? Yes, but. 30
31 We should be leveraging the power of predictive analytics to improve information governance RM: defensible disposal of low value information -- Regulatory compliance -- Risk mitigation segregating sensitive materials (PII, proprietary, etc.) -- Business intelligence -- E-discovery -- Collaboration across enterprise -- Providing access to dark data & archives 31
32 What is the IGI? The IGI is a cross-disciplinary think tank and consortium dedicated to advancing the adoption of Information Governance practices and technologies through research, publishing, advocacy, and peer-to-peer networking. It provides industry thought leadership and benchmarking designed to foster consensus and conversation It is a connector among the stakeholders of information governance It is a promoter of industry best practices and standards
33 Key IGI Activities IGI Research and Publishing. Develop benchmarking and research that advance the practice of IG. Also, developing research-based use cases for IG tools (e.g., checklists, templates) for IG practitioners. Advocacy. Advocacy and education through content, events, speaking, lobbying, and IG evangelism. Peer-to-Peer Networking. Foster and facilitate conversation among peers and stakeholders in the IG community.
34 The future is here. It is just not evenly distributed. --William Gibson 34
35 References Sources Referencing Information Governance, Autocategorization & Predictive Coding Bennett B. Borden & J.R. Baron, Finding the Signal in the Noise: Information Governance, Analytics, and the Future of Information Givernance, 20 Richmond J. Law & Technology 7 (2014), see J.R. Baron & Simon J. Attfield, Where Light in Darkness Lies: Preservation, Sensemaking, and Access Strategies for the Modern Digital Archive, UNESCO Memory of the World in the Digital Age Conference, Vancouver, B.C. (2012), available at J.R. Baron, Law in the Age of Exabytes: Some Further Thoughts on Information Inflation and Current Issues in E- Discovery Search, 17 Richmond J. Law & Technology (2011), see N. Pace, Where The Money Goes: Understanding Litigant Expenditures for Producing E-Discovery, RAND Publication (2012), see The Sedona Conference, The Sedona Conference Commentary on Information Governance (2013) Latest Supervised Learning/Predictive Coding Case Law: Da Silva Moore v. Publicis Groupe, 2012 WL (S.D.N.Y. Feb. 24, 2012), approved and adopted in Da Silva Moore v. Publicis Groupe, 2012 WL , at *2 (S.D.N.Y. Apr. 26, 2012) EORHB v HOA Holdings, Civ. No VCL (Del. Ch. Oct. 15, 2012) Global Aerospace Inc., et al. v. Landow Aviation, L.P., et al., 2012 WL (Va. Cir. Ct. Apr. 23, 2012). In re Actos (Pioglitazone) Products, 2012 WL (W.D. La. July 27, 2012) Kleen Products, LLC v. Packaging Corp. of America, 10 C 5711 (N.D. Ill.) (Nolan, M.J.) 35
36 Jason R. Baron, Esq. Drinker Biddle & Reath, LLP 1500 K Street Washington, D.C (202) jason.baron@dbr.com
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