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| Original file line number | Diff line number | Diff line change |
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| %%% Digital technology %%% | ||
| @inproceedings{Weisha_2021_digtech, | ||
| author = {Weisha, Z.}, | ||
| title = {The Impact of Digital Technology on Enterprise Innovation by Knowledge Management Perspective}, | ||
| year = {2021}, | ||
| booktitle = {Proceedings - 2021 International Conference on Big Data and Intelligent Decision Making, BDIDM 2021}, | ||
| pages = {29 – 32}, | ||
| doi = {10.1109/BDIDM53834.2021.00013}, | ||
| publisher = {Institute of Electrical and Electronics Engineers Inc.} | ||
| } | ||
| @article{Forman_2019_digtech, | ||
| title = {Digital technology adoption and knowledge flows within firms: Can the {Internet} overcome geographic and technological distance?}, | ||
| journal = {Research Policy}, | ||
| volume = {48}, | ||
| number = {8}, | ||
| pages = {103697}, | ||
| year = {2019}, | ||
| issn = {0048-7333}, | ||
| doi = {https://doi.org/10.1016/j.respol.2018.10.021}, | ||
| url = {https://www.sciencedirect.com/science/article/pii/S0048733318302592}, | ||
| author = {Forman, C. and {van Zeebroeck}, N.}, | ||
| } | ||
| @ARTICLE{OMara_2012_digtech, | ||
| author = {O'Mara, B. and Gill, G.K. and Babacan, H. and Donahoo, D.}, | ||
| title = {Digital technology, diabetes and culturally and linguistically diverse communities: A case study with elderly women from the {Vietnamese} community}, | ||
| year = {2012}, | ||
| journal = {Health Education Journal}, | ||
| volume = {71}, | ||
| number = {4}, | ||
| pages = {491 – 504}, | ||
| doi = {10.1177/0017896911407054}, | ||
| } | ||
| @ARTICLE{Wang_2022_digtech, | ||
| author = {Wang, J. and Ma, X. and Zhang, J. and Zhao, X.}, | ||
| title = {Impacts of digital technology on energy sustainability: {China} case study}, | ||
| year = {2022}, | ||
| journal = {Applied Energy}, | ||
| volume = {323}, | ||
| doi = {10.1016/j.apenergy.2022.119329}, | ||
| publisher = {Elsevier Ltd} | ||
| } | ||
| @inproceedings{Wang_2020_digtech, | ||
| author = {Wang, W.}, | ||
| title = {Research on Design and Innovation based on network platform and Digital Technology}, | ||
| year = {2020}, | ||
| booktitle = {Proceedings - 2020 International Conference on Innovation Design and Digital Technology, ICIDDT 2020}, | ||
| pages = {401 – 404}, | ||
| doi = {10.1109/ICIDDT52279.2020.00080}, | ||
| publisher = {Institute of Electrical and Electronics Engineers Inc.} | ||
| } | ||
| @inproceedings{Grober_2020_digtech, | ||
| author = {Grober, T. and Grober, O.}, | ||
| title = {Improving the efficiency of farm management using modern digital technologies}, | ||
| year = {2020}, | ||
| booktitle = {E3S Web of Conferences}, | ||
| volume = {175}, | ||
| doi = {10.1051/e3sconf/202017513003}, | ||
| editor = {Rudoy D. and Ignateva S.}, | ||
| publisher = {EDP Sciences} | ||
| } | ||
| @ARTICLE{Mohapatra_2022_digtech, | ||
| author = {Mohapatra, B. and Tripathy, S. and Singhal, D. and Saha, R.}, | ||
| title = {Significance of digital technology in manufacturing sectors: Examination of key factors during {Covid}-19}, | ||
| year = {2022}, | ||
| journal = {Research in Transportation Economics}, | ||
| volume = {93}, | ||
| doi = {10.1016/j.retrec.2021.101134}, | ||
| publisher = {Emerald Group Holdings Ltd.} | ||
| } | ||
| @article{Kretschmer_2020_digtech, | ||
| author = {Kretschmer, T. and Khashabi, P.}, | ||
| title ={Digital Transformation and Organization Design: An Integrated Approach}, | ||
| journal = {California Management Review}, | ||
| volume = {62}, | ||
| number = {4}, | ||
| pages = {86-104}, | ||
| year = {2020}, | ||
| doi = {10.1177/0008125620940296}, | ||
| } | ||
| @misc{ross_2018_digtech, | ||
| author={Ross, J.W. and Mocker, M. and Beath, C.M.}, | ||
| title={Five building blocks of digital transformation}, | ||
| date = {2018-06-21}, | ||
| journal={MIT CISR}, | ||
| url={https://cisr.mit.edu/publication/2018_0601_BuildingBlocks_RossMockerBeath}, | ||
| urldate = {2022-12-15}, | ||
| } | ||
|
|
||
| %%% Artificial intelligence %%% | ||
| @article{Graham_2020_AIbackground, | ||
| author = {Graham, N.}, | ||
| title = {Artificial Intelligence}, | ||
| subtitle = {The next evolution of digital transformation}, | ||
| year = {2020}, | ||
| month = {05}, | ||
| url = {https://www.businessgoing.digital/artificial-intelligence-the-next-evolution-of-digital-transformation/}, | ||
| urldate = {2022-12-15}, | ||
| } | ||
| @article{Ellahham_2020_AIbackground, | ||
| title = {Artificial Intelligence: The Future for Diabetes Care}, | ||
| journal = {The American Journal of Medicine}, | ||
| volume = {133}, | ||
| number = {8}, | ||
| pages = {895-900}, | ||
| year = {2020}, | ||
| issn = {0002-9343}, | ||
| doi = {https://doi.org/10.1016/j.amjmed.2020.03.033}, | ||
| url = {https://www.sciencedirect.com/science/article/pii/S0002934320303399}, | ||
| author = {Ellahham, S.}, | ||
| } | ||
| @Article{Vinuesa_2020_AIbackground, | ||
| author={Vinuesa, R. and Azizpour, H. and Leite, I. and Balaam, M. and Dignum, V. and Domisch, S. and Felländer, A. and Langhans, S.D. and Tegmark, M. and {Fuso Nerini}, F.}, | ||
| title={The role of artificial intelligence in achieving the {Sustainable Development Goals}}, | ||
| journal={Nature Communications}, | ||
| year={2020}, | ||
| month={01}, | ||
| day={13}, | ||
| volume={11}, | ||
| number={1}, | ||
| pages={233}, | ||
| issn={2041-1723}, | ||
| doi={10.1038/s41467-019-14108-y}, | ||
| } | ||
| @ARTICLE{Cetinic_2022_AIbackground, | ||
| author = {Cetinic, E. and She, J.}, | ||
| title = {Understanding and Creating Art with {AI}: Review and Outlook}, | ||
| year = {2022}, | ||
| journal = {ACM Transactions on Multimedia Computing, Communications and Applications}, | ||
| volume = {18}, | ||
| number = {2}, | ||
| doi = {10.1145/3475799}, | ||
| publisher = {Association for Computing Machinery} | ||
| } | ||
| @ARTICLE{Xu_2018_AIbackground, | ||
| author = {Xu, L.D. and Xu, E.L. and Li, L.}, | ||
| title = {Industry 4.0: State of the art and future trends}, | ||
| year = {2018}, | ||
| journal = {International Journal of Production Research}, | ||
| volume = {56}, | ||
| number = {8}, | ||
| pages = {2941 – 2962}, | ||
| doi = {10.1080/00207543.2018.1444806}, | ||
| publisher = {Taylor and Francis Ltd.} | ||
| } | ||
| @ARTICLE{Lasi_2014_AIbackground, | ||
| author = {Lasi, H. and Fettke, P. and Kemper, H.G. and Feld, T. and Hoffmann, M.}, | ||
| title = {Industry 4.0}, | ||
| year = {2014}, | ||
| journal = {Business and Information Systems Engineering}, | ||
| volume = {6}, | ||
| number = {4}, | ||
| pages = {239 – 242}, | ||
| doi = {10.1007/s12599-014-0334-4}, | ||
| publisher = {Gabler Verlag} | ||
| } | ||
| @ARTICLE{Lu_2017_AIbackground, | ||
| author = {Lu, Y.}, | ||
| title = {Industry 4.0: A survey on technologies, applications and open research issues}, | ||
| year = {2017}, | ||
| journal = {Journal of Industrial Information Integration}, | ||
| volume = {6}, | ||
| pages = {1 – 10}, | ||
| doi = {10.1016/j.jii.2017.04.005}, | ||
| publisher = {Elsevier B.V.} | ||
| } | ||
|
|
||
| %%% Stakeholders %%% | ||
| @book{Freeman_1984_stakeholders, | ||
| title={Strategic Management: A Stakeholder Approach}, | ||
| author={Freeman, R.E.}, | ||
| isbn={9780273019138}, | ||
| lccn={gb84030734}, | ||
| series={Business and Public Policy Series}, | ||
| year={1984}, | ||
| publisher={Pitman} | ||
| } | ||
| @article{Freeman_1983_stakeholders, | ||
| author = {Freeman, R. and Reed, D.L.}, | ||
| year = {1983}, | ||
| month = {04}, | ||
| title = {Stockholders and Stakeholders: A New Perspective on Corporate Governance}, | ||
| volume = {25}, | ||
| journal = {California Management Review}, | ||
| doi = {10.2307/41165018} | ||
| } | ||
| @ARTICLE{Mitchell_1997_stakeholders, | ||
| author = {Mitchell, R.K. and Agle, B.R. and Wood, D.J.}, | ||
| title = {Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts}, | ||
| year = {1997}, | ||
| journal = {Academy of Management Review}, | ||
| volume = {22}, | ||
| number = {4}, | ||
| pages = {853 – 886}, | ||
| doi = {10.5465/AMR.1997.9711022105}, | ||
| publisher = {Academy of Management} | ||
| } | ||
| @ARTICLE{Hillman_2001_stakeholders, | ||
| author = {Hillman, A.J. and Keim, G.D.}, | ||
| title = {Shareholder value, stakeholder management, and social issues: What's the bottom line?}, | ||
| year = {2001}, | ||
| journal = {Strategic Management Journal}, | ||
| volume = {22}, | ||
| number = {2}, | ||
| pages = {125 – 139}, | ||
| doi = {10.1002/1097-0266(200101)22:2<125::AID-SMJ150>3.0.CO;2-H}, | ||
| } | ||
| @article{Keegan_2022_stakeholders, | ||
| author = {Keegan, P.}, | ||
| date = {2022-09-19}, | ||
| title = {Business Schools Are Beginning to Embrace Stakeholder Inclusion}, | ||
| url = {https://www.bloomberg.com/news/articles/2022-09-19/business-schools-teach-esg-to-win-gen-z?leadSource=uverify\%20wall}, | ||
| urldate = {2022-12-15}, | ||
| journal = {Bloomberg}, | ||
| } | ||
| @ARTICLE{Benn_2016_stakeholders, | ||
| author = {Benn, S. and Abratt, R. and O'Leary, B.}, | ||
| title = {Defining and identifying stakeholders: Views from management and stakeholders}, | ||
| year = {2016}, | ||
| journal = {South African Journal of Business Management}, | ||
| volume = {47}, | ||
| number = {2}, | ||
| pages = {1 – 11}, | ||
| doi = {10.4102/sajbm.v47i2.55}, | ||
| publisher = {Sabinet} | ||
| } | ||
| @article{Hoory_2022_stakeholders, | ||
| author = {Hoory, L. and Bottorff, C.}, | ||
| title = {What Is A Stakeholder Analysis?}, | ||
| subtitle = {Everything You Need To Know}, | ||
| journal = {Forbes Advisor}, | ||
| date = {2022-08-07}, | ||
| url = {https://www.forbes.com/advisor/business/what-is-stakeholder-analysis/}, | ||
| urldate = {2022-12-15}, | ||
| } | ||
| @ARTICLE{Reed_2009_stakeholders, | ||
| author = {Reed, M.S. and Graves, A. and Dandy, N. and Posthumus, H. and Hubacek, K. and Morris, J. and Prell, C. and Quinn, C.H. and Stringer, L.C.}, | ||
| title = {Who's in and why?}, | ||
| subtitle = {A typology of stakeholder analysis methods for natural resource management}, | ||
| year = {2009}, | ||
| journal = {Journal of Environmental Management}, | ||
| volume = {90}, | ||
| number = {5}, | ||
| pages = {1933 – 1949}, | ||
| doi = {10.1016/j.jenvman.2009.01.001}, | ||
| } | ||
|
|
||
|
|
||
| %%% Responsible Research and Innovation (RRI) %%% | ||
| @incollection{Werker_2020_RRI, | ||
| author = {Werker, C.}, | ||
| title = {Assessing {Responsible Research and Innovation} ({RRI}) systems in the digital age}, | ||
| booktitle = {Assessment of {Responsible Innovation}: Methods and Practices}, | ||
| page = {275 - 292}, | ||
| edition = {1}, | ||
| year = {2020}, | ||
| address = {London}, | ||
| publisher = {Routledge}, | ||
| editor = {Yaghmaei, E. and {van de Poel}, I.}, | ||
| ISBN = {9780429298998}, | ||
| } | ||
| @incollection{Schomberg_2013_RRI, | ||
| author = {Schomberg, R.}, | ||
| year = {2013}, | ||
| month = {06}, | ||
| day = {02}, | ||
| pages = {51-74}, | ||
| title = {A Vision of {Responsible Research and Innovation}}, | ||
| isbn = {978-1-119-96635-7}, | ||
| booktitle = {{Responsible Innovation}: Managing the Responsible Emergence of Science and Innovation in Society}, | ||
| doi = {10.1002/9781118551424.ch3}, | ||
| editor = {Owen, R. and Bessant, J. and Heintz, M.}, | ||
| } | ||
| @ARTICLE{Burget_2017_RRI, | ||
| author = {Burget, M. and Bardone, E. and Pedaste, M.}, | ||
| title = {Definitions and Conceptual Dimensions of {Responsible Research and Innovation}: A Literature Review}, | ||
| year = {2017}, | ||
| journal = {Science and Engineering Ethics}, | ||
| volume = {23}, | ||
| number = {1}, | ||
| doi = {10.1007/s11948-016-9782-1}, | ||
| publisher = {Springer Netherlands}, | ||
| } | ||
|
|
||
| %%% Ethics %%% | ||
| @ARTICLE{Allhoff_2011_ethics, | ||
| author = {Allhoff, F.}, | ||
| title = {What Are Applied Ethics?}, | ||
| year = {2011}, | ||
| journal = {Science and Engineering Ethics}, | ||
| volume = {17}, | ||
| number = {1}, | ||
| pages = {1 – 19}, | ||
| doi = {10.1007/s11948-010-9200-z}, | ||
| publisher = {Kluwer Academic Publishers} | ||
| } |
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| \section*{Abstract} | ||
| Artificial intelligence (AI) is everywhere, and has great potential for doing good, through its autonomous and scalable nature. However, several cases have shown that this nature also brings with it a potential for negative results, which, due to the vast reach of AI technology, can have large consequences for society. To avoid these negative results, AI systems should be developed to be responsible. | ||
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| \vfill | ||
| This paper reviews 54 papers on responsible AI, with the goal of creating an understanding of how AI systems can be designed to be responsible. This review results in a set of four core principles -- Autonomy, Beneficence, Non-maleficence and Justice -- that create responsible value by themselves, as well as seven instrumental principles for responsible AI -- Transparency, Accountability, Trust, Sustainability, Privacy and Others -- that create responsible value by facilitating for the core principles. Additionally, the reviewed literature included three clusters of antecedents for responsible AI, as well as three clusters of business advantages that can be gained by adopting responsible AI practices. | ||
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| The review also uncovered a gap between abstract principles and actual responsible AI development. To help bridge this, this paper introduces a project-level framework for responsible AI development, the EPNIS framework. This framework is compared to existing frameworks for responsible AI, to fit it into the current ecosystem of responsible AI methods. Finally, the results of the review are used to point out future research that is needed within the field of responsible AI | ||
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| \newpage | ||
| \section*{Oppsummering} | ||
| Kunstig intelligens (KI) er over alt, og har stort potensiale for gode resultater, via dets autonome og skalerbare natur. Flere hendelser har likevel vist at denne naturen også har potensiale for negative resultater, noe som, grunnet den store rekkevidden til kunstig intelligens, can ha store konsekvenser for samfunnet. For å unngå disse negative resultatene bør KI-systemer utvikles på en ansvarlig (engelsk: \textit{responsible}) måte. | ||
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| Denne oppgaven analyserer 54 dokumenter om ansvarlig kunstig intelligens, med mål om å skape en forståelse for hvordan KI-systemer kan utvikles på en ansvarlig måte. Analysen resulterer i fire kjerneprinsipper for ansvarlig kunstig intelligens -- Autonomi (\textit{Autonomy}), Velgjørighet (\textit{Beneficence}), Ikke-skade (\textit{Non-maleficence}) og Rettferdighet (\textit{Justice}) -- som skaper ansvarsverdi på egenhånd, samt syv instrumentelle prinsipper -- Åpenhet (\textit{Transparency}), Ansvarlighet (\textit{Accountability}), Pålitelighet (\textit{Trust}), Bærekraftighet (\textit{Sustainability}), Rett til privatliv (\textit{Privacy}) og Andre (\textit{Others}) -- som skaper verdi gjennom å støtte og fasilitere for kjerneprinsippene. I tillegg finner analysen tre grupper med årsaker (\textit{antecedents}) til at selskaper utvikler ansvarlig kunstig intelligens, samt tre grupper med fordeler (\textit{business advantages}) bedrifter kan oppnå ved å bruke metoder for ansvarlig kunstig intelligens. | ||
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| Analysen oppdaget også en avstand mellom abstrakte prinsipper og faktisk implementasjon av ansvarlig kunstig intelligens. For å minimere denne avstanden introduserer dette papiret et rammeverk for ansvarlig KI-utvikling på prosjektnivå, EPNIS-rammeverket. Dette sammenlignes med eksisterende rammeverk for ansvarlig kunstig intelligens, for å finne dets plass i det nåværende økosystemet for ansvarlig kunstig intelligens. Avslutningsvis brukes resultatene av analysen til å peke ut fremtidig forskning som behøves innenfor ansvarlig KI-feltet. | ||
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| \vfill | ||
| \newpage |
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