Managing Artificial Intelligence Deployment in the Public Sector

Averill Campion; M. Gasco Hernández; Slava Mikhaylov Jankin; M. Esteve

doi:10.1109/MC.2020.2995644

Managing Artificial Intelligence Deployment in the Public Sector

Averill Campion
, M. Gasco Hernández
, Slava Mikhaylov Jankin
, M. Esteve

Producció científica: Article en revista no indexada › Article

26 Cites (Scopus)

Resum

There is a scarcity of empirical evidence surrounding the challenges and approaches to artificial intelligence deployment. Using data analytics, our study moves from speculation to gathering evidence. Our findings show that most challenges arise during implementation and relate to skills, culture, and resistance to share information driven by data challenges.

Idioma original	Anglès
Pàgines	28-37
Nombre de pàgines	10
Volum	53
Núm.	10
Publicació especialitzada	Computer
DOIs	https://doi.org/10.1109/MC.2020.2995644
Estat de la publicació	Publicada - d’oct. 2020
Publicat externament	Sí

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10.1109/MC.2020.2995644

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@misc{e1853668569f4465a0ec5cb7b5af0eee,

title = "Managing Artificial Intelligence Deployment in the Public Sector",

abstract = "There is a scarcity of empirical evidence surrounding the challenges and approaches to artificial intelligence deployment. Using data analytics, our study moves from speculation to gathering evidence. Our findings show that most challenges arise during implementation and relate to skills, culture, and resistance to share information driven by data challenges.",

author = "Averill Campion and \{Gasco Hern{\'a}ndez\}, M. and \{Mikhaylov Jankin\}, Slava and M. Esteve",

note = "Publisher Copyright: {\textcopyright} 1970-2012 IEEE.",

year = "2020",

month = oct,

doi = "10.1109/MC.2020.2995644",

language = "English",

volume = "53",

pages = "28--37",

journal = "Computer",

issn = "0018-9162",

publisher = "IEEE Computer Society",

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T1 - Managing Artificial Intelligence Deployment in the Public Sector

AU - Campion, Averill

AU - Gasco Hernández, M.

AU - Mikhaylov Jankin, Slava

AU - Esteve, M.

PY - 2020/10

Y1 - 2020/10

N2 - There is a scarcity of empirical evidence surrounding the challenges and approaches to artificial intelligence deployment. Using data analytics, our study moves from speculation to gathering evidence. Our findings show that most challenges arise during implementation and relate to skills, culture, and resistance to share information driven by data challenges.

AB - There is a scarcity of empirical evidence surrounding the challenges and approaches to artificial intelligence deployment. Using data analytics, our study moves from speculation to gathering evidence. Our findings show that most challenges arise during implementation and relate to skills, culture, and resistance to share information driven by data challenges.

UR - https://www.scopus.com/pages/publications/85094141639

U2 - 10.1109/MC.2020.2995644

DO - 10.1109/MC.2020.2995644

M3 - Article

AN - SCOPUS:85094141639

SN - 0018-9162

VL - 53

SP - 28

EP - 37

JO - Computer

JF - Computer

ER -

Managing Artificial Intelligence Deployment in the Public Sector

Resum

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