1.

Record Nr.

UNINA9910357826903321

Autore

Steward Dwight

Titolo

Big Data Analytics in U.S. Courts : Uses, Challenges, and Implications / / by Dwight Steward, Roberto Cavazos

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Palgrave Pivot, , 2019

ISBN

9783030317805

3030317803

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (89 pages)

Collana

Palgrave Advances in the Economics of Innovation and Technology, , 2662-3870

Disciplina

347.736

347.73064

Soggetti

Law and economics

Economic development

Finance, Public

Law and Economics

Economic Development, Innovation and Growth

Public Economics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

1. Data Analytics and Litigation -- 2. History of Data Analysis in US Courts -- 3. Examples of Litigation Involving Big Data Analytics -- 4. The Courts as Gatekeeper of Big Data Evidence -- 5. Indirect Use of Big Data Analytics in US Courts -- 6. Future Challenges and Recommendations.

Sommario/riassunto

This Palgrave Pivot identifies the key legal, economic, and policy issues surrounding the allowance to use and interpret electronic data consistently and in a scientifically valid manner in U.S. courts. Evidence based on the analysis of large amounts of electronic data ("Big Data") plays an increasing role in civil court disputes, providing information that could not have been obtained from a witness stand. While Big Data evidence presents opportunities, it also presents legal and public policy challenges and concerns. How can one be sure that deviations found in Big Data fall outside the norm? If statistical analyses can be conducted



and presented different ways, how can judges and juries make sense of conflicting interpretations? When does Big Data extraction stop being investigative and instead become an invasion of privacy? This book traces the history of Big Data use in U.S. courts, couples current case studies with legal challenges to explore key controversies, and suggests how courts can change the way they handle Big Data to ensure that findings are statistically significant and scientifically sound.