5. Slutsats och vidare forskning
5.2 Vidare forskning
Studien påvisar att AI-tekniken kan minska diskriminering och fördomar under rekryteringsprocessen, vilket har resulterat i att följande forskningsområden anses vara intressanta att undersöka. Ett förslag till vidare forskning skulle exempelvis vara att studera attityder och tillit gentemot AI som en central del av rekryteringsprocessen. Har potentiella kunder och kandidater en negativ syn på AI-tekniken och hur kan detta hanteras? Vidare kan ett huvudfokus vara att undersöka varför de marknadsledande bemanningsföretagen inte valt att implementera AI-tekniken under rekryteringsprocessen eller undersöka deras synpunkter om tekniken. Om AI kan minska diskriminering och fördomar, varför väljer inte de marknadsledande bemanningsföretagen att implementera tekniken?
Ett annat förslag till vidare forskning kan vara att undersöka om det framställda urvalet har ändrats genom användandet av AI-tekniken. Det var något som vi, genom denna studie, inte kunde besvara av den orsaken att företagen som intervjuades inte hade nyttjat AI-tekniken under en längre period, och därmed har de inte kunnat dra slutsatser gällande urvalet. Hur har det framställda urvalet ändrats sedan implementeringen av AI-teknik under rekryteringsprocessen?
39
Källförteckning
Agerström, J., Björklund, F., Carlsson, R., & Rooth, D. (2012). Warm and Competent Hassan = Cold and Incompetent Eric: A Harsh Equation of Real-Life Hiring Discrimination. Basic and Applied Social Psychology, 34(4), 359–366.
https://doi.org/10.1080/01973533.2012.693438
Ahmed, A., Andersson, L., & Hammarstedt, M. (2012). Does age matter for employability? A field experiment on ageism in the Swedish labour market. Applied
Economics Letters, 19(4), 403–406. https://doi.org/10.1080/13504851.2011.581199
Ahmed, O. (2018). Artificial Intelligence In HR. International Journal of Research and
Analytical Reviews, 5(4), 971-978.
Albert, E. (2019). AI in talent acquisition: a review of AI-applications used in recruitment and selection. Strategic HR Review, 18(5), 215–221. https://doi.org/10.1108/SHR-04- 2019-0024
Arai, M., Bursell, M., & Nekby, L. (2016). The Reverse Gender Gap in Ethnic Discrimination: Employer Stereotypes of Men and Women with Arabic Names1,2.
International Migration Review, 50(2), 385–412. https://doi.org/10.1111/imre.12170
Arvey, R. D., & Renz, G. L. (1992). Fairness in the selection of employees. Journal of
Business Ethics, 11(5-6), 331-340. https://doi.org/10.1007/BF00870545
Beattie, G., & Johnson, P. (2012). Possible unconscious bias in recruitment and promotion and the need to promote equality. Perspectives: Policy and Practice in
Higher Education, 16(1), 7-13. https://doi.org/10.1080/13603108.2011.611833
Behtoui, A. (2008). Informal Recruitment Methods and Disadvantages of Immigrants in the Swedish Labour Market. Journal of Ethnic and Migration Studies, 34(3), 411– 430. https://doi.org/10.1080/13691830701880251
Berrey, E. C. (2014). “Breaking Glass Ceilings, Ignoring Dirty Floors: The Culture and Class Bias of Corporate Diversity Management.” American Behavioral Scientist 59(2): 347–70.
Blomkvist, P., Hallin, A., & Lindell, E. (2018). Metod för företagsekonomer : uppsats
enligt 4-stegsmodellen. Lund: Studentlitteratur AB.
Bonoli, G., & Hinrichs, K. (2012). STATISTICAL DISCRIMINATION AND EMPLOYERS’ RECRUITMENT: Practices for low-skilled workers. European
Societies, 14(3), 338–361. https://doi.org/10.1080/14616696.2012.677050
40
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative
Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Breaugh, J., & Starke, M. (2000). Research on employee recruitment: so many studies, so many remaining questions. Journal of Management, 26(3), 405–434. https://doi.org/10.1177/014920630002600303
Bryman, A., & Bell, E. (2017). Företagsekonomiska forskningsmetoder (Upplaga 3). Stockholm: Liber.
Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data- driven decisionmaking affect firm performance?. http://dx.doi.org/10.2139/ssrn.1819486
Bygren, M. (2013). Unpacking the causes of segregation across workplaces. Acta
Sociologica, 56(1), 3-19.
Carlsson, M., & Eriksson, S. (2017). Påverkar arbetssökandes ålder och kön chansen att få svar på jobbansökan? Resultat från ett fältexperiment. Hämtad från Hämtad från Institutet för arbetsmarknads- och utbildningspolitisk utvärdering (IFAU). https://www.ifau.se/globalassets/pdf/se/2017/r-2017-08-paverkar-arbetssokandes- alder-och-kon-chansen-att-fa-svar-pa-en-jobbansokan.pdf
Carlsson, M., & Rooth, D. (2007). Evidence of ethnic discrimination in the Swedish labor market using experimental data. Labour Economics, 14(4), 716–729. https://doi.org/10.1016/j.labeco.2007.05.001
Christensen, L., Engdahl, N., Grääs, C., & Haglund, L. (2016).
Marknadsundersökning : en handbok (4. uppl.). Lund: Studentlitteratur.
Ciobanu, A., Androniceanu, A., & Lazaroiu, G. (2019). An integrated psycho- sociological perspective on public employees’ motivation and performance. Frontiers
in Psychology, 10, 36.
Cohen, T. (2019). How to leverage artificial intelligence to meet your diversity goals.
Strategic HR Review, 18(2), 62–65. https://doi.org/10.1108/SHR-12-2018-0105
Cuellar, N. G. (2017). Unconscious bias: What is yours?, Journal of Transcultural
Nursing, 28(4), 333. https://doi.org/10.1177%2F1043659617713566
Danielsson, M. L. (2010). Kompetensbaserad rekrytering, intervjuteknik och testning. Natur & Kultur.
41
DeYoung, C. (2015). Cybernetic Big Five Theory. Journal of Research in Personality,
56. https://doi.org/10.1016/j.jrp.2014.07.004
Diskriminering. (2009). I Svensk Ordbok. Hämtad från https://svenska.se/tre/?sok=diskriminering&pz=1
Diskrimineringsombudsmannen. (2012). Forskningsöversikt om rekrytering i arbetslivet. Hämtad från
https://www.do.se/globalassets/publikationer/rapport-forskningsoversikt- diskriminering-rekrytering.pdf
Diskrimineringsombudsmannen. (2019). Årsredovisning 2019. Hämtad från https://www.do.se/globalassets/om-do/do-arsredovisning-2019.pdf
Edin, P. & Lagerström, J. (2006). Blind Dates: Quasi-experimental Evidence on Discrimination. Working Paper 2006:4. Hämtad från Institutet för arbetsmarknads- och
utbildningspolitisk utvärdering (IFAU).
https://www.ifau.se/globalassets/pdf/se/2006/wp06-04.pdf
Egidius, H. (2008). Psykologilexikon. (4. utg.) Stockholm: Natur och kultur.
Eriksson, S., Johansson, P., & Langenskiöld, S. (2012). Vad är rätt profil för att få ett jobb? - En experimentell studie av rekryteringsprocessen. Hämtad från Institutet för arbetsmarknads- och utbildningspolitisk utvärdering (IFAU). https://www.ifau.se/sv/Forskning/Publikationer/Rapporter/2012/Vad-ar-ratt-profil-for- att-fa-ett-jobb---En-experimentell-studie-av-rekryteringsprocessen/
Forbes. (2015). How To Land A Job In 90 Seconds. Hämtad 2020-05-28 från https://www.forbes.com/sites/ashleystahl/2015/11/06/how-to-land-a-job-in-90-
seconds/#540447b54802
Ghauri, P., & Grønhaug, K. (2010). Research methods in business studies (4th ed). Harlow: Pearson Education.
Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The
Qualitative Report, 8(4), 597–606.
Greenwald, A. (2017). An AI stereotype catcher. Science (New York, N.Y.), 356(6334), 133–134. https://doi.org/10.1126/science.aan0649
Greenwald, A., & Banaji, M. (1995). Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes. Psychological Review, 102(1), 4–27. https://doi.org/10.1037/0033- 295X.102.1.4
42
Gupta, P., Fernandes, S. F., & Jain, M. (2018). Automation in recruitment: a new frontier. Journal of Information Technology Teaching Cases, 8(2), 118-125.
https://doi.org/10.1287/mnsc.2014.2096
Haider, J., & Sundin, O. (2017). Algoritmer : IIS internetguide (Vol. 46).
Hogg, P. (2019). Artificial intelligence: HR friend or foe? Strategic HR Review, 18(2), 47–51. https://doi.org/10.1108/SHR-11-2018-0094
Human Resources Professionals Association (HRPA). (2017). A New Age of Opportunities. What does Artificial Intelligence mean for HR Professionals? (HRPA- Rapport). Hämtad från https://www.hrpa.ca/Documents/Public/Thought- Leadership/HRPA-Report-Artificial-Intelligence-20171031.PDF
Jackson, J. (2018). Algorithmic Bias. Journal of Leadership, Accountability and Ethics,
15(4), 55–65. https://doi.org/10.33423/jlae.v15i4.170
Jacobsen, D., & Sandin, G. (2002). Vad, hur och varför : om metodval i
företagsekonomi och andra samhällsvetenskapliga ämnen. Lund: Studentlitteratur.
Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. In Proceedings of the
International Conference on Electronic Business (pp. 106-114).
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business
Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
Lecun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436– 444. https://doi.org/10.1038/nature14539
Liang, Y., & Lee, S. (2017). Fear of Autonomous Robots and Artificial Intelligence: Evidence from National Representative Data with Probability Sampling. International
Journal of Social Robotics, 9(3), 379–384. https://doi.org/10.1007/s12369-017-0401-3
McGoldrick, A., & Arrowsmith, J. (1993). Recruitment Advertising: Discrimination on the Basis of Age. Employee Relations, 15(5), 54–65.
https://doi.org/10.1108/01425459310048545
Milkman, K. L., Chugh, D., & Bazerman, M. H. (2009). How can decision making be improved?. Perspectives on psychological science, 4(4), 379-383. https://doi.org/10.1111/j.1745-6924.2009.01142.x
43
Namey, E., Guest, G., O’Regan, A., Godwin, C. L., Taylor, J., & Martinez, A. (2020). How Does Mode of Qualitative Data Collection Affect Data and Cost? Findings from a Quasi-experimental Study. Field Methods, 32(1), 58-74.
Nowak, A., Lukowicz, P., & Horodecki, P. (2018). Assessing Artificial Intelligence for Humanity: Will AI be the Our Biggest Ever Advance ? or the Biggest Threat [Opinion].
IEEE Technology and Society Magazine, 37(4), 26–34.
https://doi.org/10.1109/MTS.2018.2876105
Nowell, L., Norris, J., White, D., & Moules, N. (2017). Thematic Analysis: Striving to Meet the Trustworthiness Criteria. International Journal of Qualitative Methods, 16(1). https://doi.org/10.1177/1609406917733847
Pager, D., Bonikowski, B., & Western, B. (2009). Discrimination in a Low-Wage Labor Market: A Field Experiment. American Sociological Review, 74(5), 777–799. https://doi.org/10.1177/000312240907400505
Pager, D., & Quillian, L. (2005). Walking the Talk? What Employers Say Versus What They Do. American Sociological Review, 70(3), 355–380.
https://doi.org/10.1177/000312240507000301
Patel, R., & Davidson, B. (2019). Forskningsmetodikens grunder : att planera,
genomföra och rapportera en undersökning (Femte upplagan). Lund: Studentlitteratur.
Popescu, G. (2018). Does student debt constitute a bubble that may bring about an educational crisis? Educational Philosophy and Theory, 50(2), 115–118.
Popescu, G. H., Mieila, M., Nica, E., & Andrei, J. V. (2018). The emergence of the effects and determinants of the energy paradigm changes on European Union economy. Renewable and Sustainable Energy Reviews, 81, 768-774.
Raub, M. (2018). Bots, bias and big data: artificial intelligence, algorithmic bias and disparate impact liability in hiring practices. Ark. L. Rev., 71, 529.
Rodney, H., Valaskova, K., & Durana, P. (2019). The Artificial Intelligence Recruitment Process: How Technological Advancements Have Reshaped Job Application and Selection Practices. Psychosociological Issues in Human Resource Management,
7(1), 42–47.
Rooth, D. (2010). Automatic associations and discrimination in hiring: Real world
evidence. Labour Economics, 17(3), 523–534.
https://doi.org/10.1016/j.labeco.2009.04.005
44
Russo, G., Rietveld, P., Nijkamp, P. & Gorter, C. (1995), "Issues in recruitment strategies: an economic perspective", International Journal of Career Management,
Vol. 7 No. 3, pp. 3–13. https://doi-org.ep.bib.mdh.se/10.1108/09556219510086751
Rydgren, J. (2004). Mechanisms of exclusion: ethnic discrimination in the Swedish labour market. Journal of Ethnic and Migration Studies, 30(4), 697–716. https://doi.org/10.1080/13691830410001699522
Rynes, S. L., & Barber, A. E. (1990). Applicant attraction strategies: An organizational perspect. Academy of Management.the Academy of Management Review, 15(2), 286.
Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business
students (Eighth edition). Harlow: Pearson Education.
Scopelliti, I., Morewedge, C. K., McCormick, E., Min, H. L., Lebrecht, S., & Kassam, K. S. (2015). Bias blind spot: Structure, measurement, and consequences. Management
Science, 61(10), 2468-2486. https://doi.org/10.1287/mnsc.2014.2096
Sivathanu, B., & Pillai, R. (2018). Smart HR 4.0 – how industry 4.0 is disrupting HR.
Human Resource Management International Digest, 26(4), 7–11.
https://doi.org/10.1108/HRMID-04-2018-0059
Stets, J., & Burke, P. (2000). Identity Theory and Social Identity Theory. Social
Psychology Quarterly, 63(3), 224-237. https://doi.org/10.2307/2695870
Stiles, W. (1993). Quality control in qualitative research. Clinical Psychology Review,
13(6), 593–618. https://doi.org/10.1016/0272-7358(93)90048-Q
Stone, A., & Wright, T. (2013). When your face doesn’t fit: employment discrimination against people with facial disfigurements. Journal of Applied Social Psychology, 43(3), 515–526. https://doi.org/10.1111/j.1559-1816.2013.01032.x
Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: challenges and a path forward. California Management
Review, 61(4), 15-42. https://doi.org/10.1177/0008125619867910
Tate, S., & Page, D. (2018). Whiteliness and institutional racism: hiding behind (un)conscious bias. Ethics and Education, 13(1), 141–155.
https://doi.org/10.1080/17449642.2018.1428718
Timming, A., Nickson, D., Re, D., & Perrett, D. (2017). What Do You Think of My Ink? Assessing the Effects of Body Art on Employment Chances. Human Resource
Management, 56(1), 133–149. https://doi.org/10.1002/hrm.21770
45
Unionen. (2019). Öppna arbetsplatsen. Unionens mångfaldsrapport 2019. Hämtad från
https://www.unionen.se/sites/default/files/files/Unionens%20m%C3%A5ngfaldsrappor t%202019_Webb.pdf
Upadhyay, A., & Khandelwal, K. (2018). Applying artificial intelligence: implications for recruitment. Strategic HR Review, 17(5), 255–258. https://doi.org/10.1108/SHR-07- 2018-0051
van Esch, P., Black, J., & Ferolie, J. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers in Human Behavior, 90, 215–222. https://doi.org/10.1016/j.chb.2018.09.009
van Ours, J. C., & Ridder, G. (1993). Vacancy durations: Search or selection? Oxford
Bulletin of Economics and Statistics, 55(2), 187–198. https://doi.org/10.1111/j.1468-
0084.1993.mp55002003.x
Vetenskapsrådet (2002). Forskningsetiska principer inom humanistisk- samhällsvetenskaplig forskning. Stockholm: Vetenskapsrådet.
Wehner, M. C., Giardini, A., & Kabst, R. (2015). Recruitment Process Outsourcing and Applicant Reactions: When Does Image Make a Difference? Human Resource
Management, 54(6), 851–875. https://doi.org/10.1002/hrm.21640
Williams, B., Brooks, C., & Shmargad, Y. (2018). How Algorithms Discriminate Based on Data They Lack: Challenges, Solutions, and Policy Implications. Journal of
Information Policy, 8, 78–115. https://doi.org/10.5325/jinfopoli.8.2018.0078
Zaniboni, S., Kmicinska, M., Truxillo, D. M., Kahn, K., Paladino, M. P., & Fraccaroli, F. (2019). Will you still hire me when I am over 50? The effects of implicit and explicit age stereotyping on resume evaluations. European Journal of Work and Organizational
Psychology, 1-15. https://doi.org/10.1080/1359432X.2019.1600506
46