Sage Journals: Discover world-class research

Abstract

Algorithmic dashboards promise sharper performance yet often erode autonomy and trust—a contradiction that Goal-Setting Theory (GST) cannot explain. Guided by paradox theory, this study constructs the first competence-paradox model for AI-mediated work. Method: A PRISMA-ScR review across Scopus, Web of Science, and PsycINFO (n = 82) was followed by qualitative meta-synthesis. Specifically, results reveal four mutually reinforcing tensions: metric specificity versus discretion, cadence versus psychological safety, optimization versus learning depth, and transparency + voice versus trust. Thresholds surface when prompts refresh every 5 minutes, exceed 30 per hour, or push 20 optimization nudges per shift; at those points autonomy drops 0.40 SD, safety 0.50 SD, and exploration 15%. Consequently, a five-lever HRD sequence—goal-calibration, hybrid coaching, explainable dashboards, rotational upskilling, and moderated voice forums—converts losses into gains. Overall, the model equips scholars with falsifiable propositions and provides practitioners a unique roadmap for steering AI systems toward both productivity and human growth.

Keywords

paradox theory goal-setting algorithmic management psychological safety HRD interventions

Get full access to this article

View all access options for this article.

References

Anang

A. N.

Obidi

P. O.

Mesogboriwon

A. O.

Obidi

J. O.

Kuubata

Ogunbiyi

(2024). The role of artificial intelligence in Industry 5.0: Enhancing human-machine collaboration. World Journal of Advanced Research and Reviews, 24(2), 380–400. https://doi.org/10.30574/wjarr.2024.24.2.3369

Arksey

O’Malley

(2005). Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19–32. https://doi.org/10.1080/1364557032000119616

Arslan

Cooper

Khan

Golgeci

Ali

(2022). Artificial intelligence and human worker interaction at the team level: A conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower, 43(1), 75–88. https://doi.org/10.1108/IJM-01-2021-0052

Bakker

A. B.

Demerouti

(2017). Job demands–resources theory: Taking stock and looking forward. Journal of Occupational Health Psychology, 22(3), 273–285. https://doi.org/10.1037/ocp0000056

Barends

Rousseau

D. M.

(2018). Evidence-based management: How to use evidence to make better organizational decisions. Kogan Page.

Basili

Rocca

M. D.

Pazienza

M. T.

(1997). Contextual word sense tuning and disambiguation. Applied Artificial Intelligence, 11(3), 235–262. https://doi.org/10.1080/088395197118244

Bendig

Bräunche

(2024). The role of artificial intelligence algorithms in information systems research: A conceptual overview and avenues for future research. In Management review quarterly. Springer. https://doi.org/10.1007/s11301-024-00451-y

Braun

Clarke

(2024). Supporting best practices in reflexive thematic analysis reporting in palliative medicine: A review of published research and an introduction to the reflexive thematic analysis reporting guidelines (rtarg). Palliative Medicine, 38(6), 608–616. https://doi.org/10.1177/02692163241234800

Cao

Duan

Edwards

J. S.

Dwivedi

Y. K.

(2021). Understanding managers’ attitudesand behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation, 106(5), 102312. https://doi.org/10.1016/j.technovation.2021.102312

10.

Carter

Liu

(2025). International Journal of Information Management, 82(C), Article 102875. https://doi.org/10.1016/j.ijinfomgt.2025.102875

11.

Charlwood

Guenole

(2022). Can HR adapt to the paradoxes of artificial intelligence? Human Resource Management Journal, 32(4), 729–742. https://doi.org/10.1111/1748-8583.12433

12.

Cheng

Lin

Kong

(2023). Challenge or hindrance? How and when organizational artificial intelligence adoption influences employee job crafting. Journal of Business Research, 164(1), Article 113987. https://doi.org/10.1016/j.jbusres.2023.113987

13.

Clegg

S. R.

da Cunha

M. P. E.

(Eds.), (2019). Management, organizations, and contemporary social theory. Routledge. https://doi.org/10.4324/9780429279591

14.

Collings

D. G.

Nyberg

A. J.

Wright

P. M.

McMackin

(2021). Leading through paradox in a COVID-19 world: Human resources comes of age. Human Resource Management Journal, 31(4), 819–833. https://doi.org/10.1111/1748-8583.12343

15.

Creswell

J. W.

Poth

C. N.

(2024). Qualitative inquiry and research design: Choosing among five approaches (5th ed.). Sage.

16.

Cronen

V. E.

Johnson

K. M.

Lannamann

J. W.

(1982). Paradoxes, double binds, and reflexive loops: An alternative theoretical perspective. Family Process, 21(1), 91–112. https://doi.org/10.1111/j.1545-5300.1982.00091.x

17.

Cruse

D. A.

(1977). Pragmatics of lexical specificity. Journal of Linguistics, 13(2), 153–164. https://doi.org/10.1017/S0022226700005363

18.

de Almeida

Kireeva

Orghian

Moreira

Santos

(2023). My boss, the algorithm: AI leadership increases turnover through reduced psychological safety. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4605825

19.

Deci

E. L.

Ryan

R. M.

(2000). The “What” and “Why” of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01

20.

Edwards

J. R.

Berry

J. W.

(2010). The presence of something or the absence of nothing: Increasing theoretical precision in management research. Organizational Research Methods, 13(4), 668–689. https://doi.org/10.1177/1094428110380467

21.

Einola

Khoreva

(2023). Best friend or broken tool? Exploring the co-existence of humans and artificial intelligence in the workplace ecosystem. Human Resource Management, 62(1), 117–135. https://doi.org/10.1002/hrm.22147

22.

Eisenberg

E. M.

(1984). Ambiguity as strategy in organizational communication. Communication Monographs, 51(3), 227–242. https://doi.org/10.1080/03637758409390197

23.

Ekuma

(2023). Artificial intelligence and automation in human resource development: A systematic review. Human Resource Development Review, 23(2), 199–229. https://doi.org/10.1177/15344843231224009

24.

Faas

Bergs

Sterz

Langer

Feit

A. M.

(2024). Give me a choice: The consequences of restricting choices through AI- support on perceived autonomy, motivational variables, and decision performance [Preprint]. arXiv. https://doi.org/10.48550/arXiv.2410.07728

25.

Farjoun

(2016). Contradictions, dialectics, and paradoxes. In Tsoukas

Langley

(Eds.), The Sage handbook of process organization studies (pp. 87–109). Sage Publications.

26.

Farjoun

Fiss

P. C.

(2022). Thriving on contradiction: Toward a dialectical alternative to fit‐based models in strategy (and beyond). Strategic Management Journal, 43(2), 340–369. https://doi.org/10.1002/smj.3342

27.

Fisher

Mayer

Morris

(2021). From the editors—phenomenon-based theorizing. Academy of Management Review, 46(4), 631–639. https://doi.org/10.5465/amr.2021.0320

28.

Gagné

Parker

S. K.

Griffin

M. A.

Dunlop

P. D.

Knight

Klonek

F. E.

Parent-Rocheleau

(2022). Understanding and shaping the future of work with self-determination theory. Nature Reviews Psychology, 1(7), 378–392. https://doi.org/10.1038/s44159-022-00056-w

29.

Giraud

Zaher

Hernandez

Akram

A. A.

(2023). The impacts of artificial intelligence on managerial skills. Journal of Decision Systems, 32(3), 566–599. https://doi.org/10.1080/12460125.2022.2069537

30.

Guarana

C. L.

Hernandez

(2017). Building sense out of contextual complexity: Functional ambivalence and leadership processes. Academy of Management Proceedings, 2014(1), Article 10418. https://doi.org/10.5465/ambpp.2014.10418abstract

31.

Habersang

Reihlen

(2024). Advancing qualitative meta-studies (QMS): Current practices and reflective guidelines for synthesizing qualitative research. Organizational Research Methods, 28(2), 210–244. https://doi.org/10.1177/10944281241240180

32.

Hahn

Knight

(2021). The ontology of organizational paradox: A quantum approach. Academy of Management Review, 46(2), 362–384. https://doi.org/10.5465/amr.2018.0408

33.

Halpin

S. N.

(2024). Intercoder agreement in qualitative coding: Considerations for its use. American Journal of Qualitative Research, 8(3), 23–43. https://doi.org/10.29333/ajqr/14487

34.

Hardin

A. E.

Schinoff

B. S.

Byron

Balven

R. M.

(2024). A window into coworkers’ worlds: The relational outcomes of learning vivid, unintentional, and nonwork-related information about coworkers. Academy of Management Journal, 68(2), 1–30. https://doi.org/10.5465/amj.2022.0683

35.

Hargrave

T. J.

Van de Ven

A. H.

(2017). Integrating dialectical and paradox perspectives on managing contradictions in organizations. Organization Studies, 38(3–4), 319–339. https://doi.org/10.1177/0170840616640843

36.

Hennestad

B. W.

(1990). The symbolic impact of double bind leadership: Double bind and the dynamics of organizational culture. Journal of Management Studies (Wiley-Blackwell), 27(3), 265–280. https://doi.org/10.1111/j.1467-6486.1990.tb00247.x

37.

Hirvonen

Jylhä

Lao

Larsson

(2024). Artificial intelligence in the information ecosystem: Affordances for everyday information seeking. Journal of the Association for Information Science & Technology, 75(10), 1152–1165. https://doi.org/10.1002/asi.24860

38.

Kuvaas

(2020). Human resource management systems, employee well-being, and firm performance: The well-being paradox from mutual gains and critical perspectives. Human Resource Management, 59(3), 235–253. https://doi.org/10.1002/hrm.21990

39.

Hofstede

G. J.

Minkov

(2010). Cultures and organizations: Software of the mind (3rd ed.). McGraw-Hill.

40.

Huang

(2023). The acoustically emotion-aware conversational agent with speech emotion recognition and empathetic responses. IEEE Transactions on Affective Computing, 14(1), 17–30. https://doi.org/10.1109/TAFFC.2022.3205919

41.

Irgang

Sestino

Barth

Holmén

(2025). Healthcare workers’ adoption of and satisfaction with artificial intelligence: The counterintuitive role of paradoxical tensions and paradoxical mindset. Technological Forecasting and Social Change, 212(C), Article 123967. https://doi.org/10.1016/j.techfore.2024.123967

42.

Jarrahi

M. H.

(2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007

43.

Jarrahi

M. H.

Newlands

Lee

M. K.

Wolf

C. T.

Kinder

Sutherland

(2021). Algorithmic management in a work context. Big Data & Society, 8(2). https://doi.org/10.1177/20539517211020332

44.

Jarzabkowski

Lê

J. K.

Van de Ven

A. H.

(2013). Responding to competing strategic demands: How organizing, belonging, and performing paradoxes co-evolve. Strategic Organization, 11(3), 245–280. https://doi.org/10.1177/1476127013481016

45.

Julmi

(2022). More than just a special case: The value of double bind theory for illuminating the dark side of organizational paradoxes. Scandinavian Journal of Management, 38(2), 1–6. https://doi.org/10.1016/j.scaman.2022.101198

46.

Juyumaya

Torres

J. P.

(2023). A managers’ work engagement framework for digital tasks. Frontiers in Psychology, 14, 1009459. https://doi.org/10.3389/fpsyg.2023.1009459

47.

Kadolkar

Kepes

Subramony

(2024). Algorithmic management in the gig economy: A systematic review and research integration. Journal of Organizational Behavior. https://doi.org/10.1002/job.2831

48.

Kiuchi

Otsu

Hayashi

(2024). Psychological insights into the research and practice of embodied conversational agents, chatbots, and social assistive robots: A systematic meta-review. Behaviour & Information Technology, 43(15), 3696–3736. https://doi.org/10.1080/0144929X.2023.2286528

49.

Knapp

J. R.

Sprinkle

T. A.

Urick

M. J.

Delaney-Klinger

K. A.

(2019). The belonging model of trust. Nonprofit Management and Leadership, 30(1), 133–153. https://doi.org/10.1002/nml.21370

50.

Kokshagina

Schneider

(2023). The digital workplace: Navigating a jungle of paradoxical tensions. California Management Review, 65(2), 129–155. https://doi.org/10.1177/00081256221137720

51.

Koponen

Julkunen

Laajalahti

Turunen

Spitzberg

B. H.

(2025). Work characteristics needed by middle managers when leading AI-integrated service teams. Journal of Service Research, 28(1), 168–185. https://doi.org/10.1177/10946705231220462

52.

Koponen

Turunen

Laajalahti

Julkunen

Spitzberg

B. H.

(2025b). Sales managers’ perceptions of interpersonal communication competence in leading AI-integrated sales teams. Industrial Marketing Management, 124, 57–72. https://doi.org/10.1016/j.indmarman.2024.11.012

53.

Korzynski

Mazurek

Altmann

Ejdys

Kazlauskaite

Paliszkiewicz

Wach

Ziemba

(2023). Generative artificial intelligence as a new context for management theories: Analysis of ChatGPT. Central European Management Journal, 31(1), 3–13. https://doi.org/10.1108/CEMJ-02-2023-0091

54.

Kreps

George

Lushenko

Rao

(2023). Exploring the artificial intelligence “trust paradox”: Evidence from a survey experiment in the United States. PLoS One, 18(7), e0288109. https://doi.org/10.1371/journal.pone.0288109

55.

Krippendorff

(2018). Content analysis: An introduction to its methodology (4th ed.) Sage.

56.

Kuhn

T. S.

(1970). The structure of scientific revolutions (2nd ed.) University of Chicago Press.

57.

Kumar

Bhattacharyya

S. S.

Krishnamoorthy

(2023). Automation-augmentation paradox in organizational artificial intelligence technology deployment capabilities: An empirical investigation for achieving simultaneous economic and social benefits. Journal of Enterprise Information Management, 36(6), 1556–1582. https://doi.org/10.1108/JEIM-09-2022-0307

58.

Langley

Tsoukas

Farjoun

(2016). Contradictions, dialectics, and paradoxes. In Tsoukas

Langley

(Eds.), Contradictions, dialectics, and Paradoxes (pp. 87–105). Sage Publications Ltd. https://doi.org/10.4135/9781473957954

59.

Lee

M. K.

(2018). Understanding perceptions of algorithmic fairness: What the past, present, and future hold. Big Data & Society, 5(1), 1–7. https://doi.org/10.1177/2053951718756684

60.

Levac

Colquhoun

O’Brien

K. K.

(2010). Scoping studies: Advancing the methodology. Implementation Science: Iscus, 5, 69. https://doi.org/10.1186/1748-5908-5-69

61.

Lewis

M. W.

(2000). Exploring paradox: Toward a more comprehensive guide. Academy of Management Review, 25(4), 760–776. https://doi.org/10.5465/AMR.2000.3707712

62.

Lewis

M. W.

Smith

W. K.

(2014). Paradox as a metatheoretical perspective: Sharpening the focus and widening the scope. The Journal of Applied Behavioral Science, 50(2), 127–149. https://doi.org/10.1177/0021886314522322

63.

Lewis

M. W.

Smith

W. K.

(2023). Today’s most critical leadership skill: Navigating paradoxes. Leader to Leader, 2023(107), 12–18. https://doi.org/10.1002/ltl.20686

64.

Lin

Parker

(2024). U.S. workers are more worried than hopeful about future AI use in the workplace. Pew Research Center. https://www.pewresearch.org/wp-content/uploads/sites/20/2025/02/ST_2025.2.25_AI-Workers_REPORT.pdf

65.

Lincoln

Y. S.

Guba

E. G.

(1985). Naturalistic inquiry. Sage.

66.

Liu

Medlar

Głowacka

(2022). Lexical ambiguity detection in professional discourse. Information Processing & Management, 59(5), 103000. https://doi.org/10.1016/j.ipm.2022.103000

67.

Locke

E. A.

Latham

G. P.

(2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705–717. https://doi.org/10.1037/0003-066x.57.9.705

68.

Locke

E. A.

Latham

G. P.

(2019). The development of goal-setting theory: A half-century retrospective. Motivation Science, 5(2), 93–105. https://doi.org/10.1037/mot0000127

69.

Locke

E. A.

Latham

G. P.

Erez

(1988). The determinants of goal commitment. Academy of Management Review, 13(1), 23–39. https://doi.org/10.5465/amr.1988.4306771

70.

Milanez

(2023). “The impact of AI on the workplace: Evidence from OECD case studies of AI implementation”. OECD Social, Employment and Migration Working Papers. No. 289. Paris: OECD Publishing. https://doi.org/10.1787/2247ce58-en

71.

Miron-Spektor

Ingram

Keller

Smith

W. K.

Lewis

M. W.

(2018). Microfoundations of organizational paradox: The problem is how we think about the problem. Academy of Management Journal, 61(1), 26–45. https://doi.org/10.5465/amj.2016.0594

72.

Mogaji

Nguyen

N. P.

(2022). Managers’ understanding of artificial intelligence inrelation to marketing financial services: Insights from a cross-country study. International Journal of Bank Marketing, 40(6), 1272–1298. https://doi.org/10.1108/IJBM-09-2021-0440

73.

Möhlmann

Zalmanson

(2017). Hands on the wheel: Navigating algorithmic management and Uber drivers’ autonomy. In Kim

Y. J.

Agarwal

Lee

J. K.

(Eds.), Proceedings of the international conference on information systems: Transforming Society with Digital Innovation (ICIS 2017, Seoul, South Korea, December 10–13). Association for Information Systems. https://aisel.aisnet.org/icis2017/DigitalPlatforms/Presentations/3

74.

Noponen

Feshchenko

Auvinen

Luoma-aho

Abrahamsson

(2024). Taylorism on steroids or enabling autonomy? A systematic review of algorithmic management. Management Review Quarterly, 74(3), 1695–1721. https://doi.org/10.1007/s11301-023-00345-5

75.

Nowell

L. S.

Norris

J. M.

White

D. E.

Moules

N. J.

(2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1). https://doi.org/10.1177/1609406917733847

76.

Nylund

P. A.

Ferràs-Hernández

Brem

(2023). A trust paradox may limit the application of AI-generated knowledge. Research-Technology Management, 66(5), 44–52. https://doi.org/10.1080/08956308.2023.2236475

77.

O’Connor

Joffe

(2020). Intercoder reliability in qualitative research: Debates and practical guidelines. International Journal of Qualitative Methods, 19, Article 1609406919899220. https://doi.org/10.1177/1609406919899220

78.

Ortega-Ochoa

Arguedas

Daradoumis

(2024). Empathic pedagogical conversational agents: A systematic literature review. British Journal of Educational Technology, 55(3), 886–909. https://doi.org/10.1111/bjet.13413

79.

Page

M. J.

McKenzie

J. E.

Bossuyt

P. M.

Boutron

Hoffmann

T. C.

Mulrow

C. D.

Shamseer

Tetzlaff

J. M.

Akl

E. A.

Brennan

S. E.

Chou

Glanville

Grimshaw

J. M.

Hróbjartsson

Lalu

M. M.

Loder

E. W.

Mayo-Wilson

McDonald

… Moher

(2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

80.

Pakarinen

Huising

(2023). Relational expertise: What machines can’t know. Journal of Management Studies, 62(5), 2053–2082. https://doi.org/10.1111/joms.12915

81.

Papachroni

Heracleous

(2020). Ambidexterity as practice: Individual ambidexterity through paradoxical practices. The Journal of Applied Behavioral Science, 56(2), 143–165. https://doi.org/10.1177/0021886320913048

82.

Parasuraman

(2000). Technology readiness index (tri): A multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research, 2(4), 307–320. https://doi.org/10.1177/109467050024001

83.

Peters

M. D. J.

Godfrey

McInerney

Munn

Tricco

A. C.

Khalil

(2024). Scoping reviews. In Aromataris

Lockwood

Porritt

Pilla

Jordan

(Eds.), JBI manual for evidence synthesis. JBI. https://doi.org/10.46658/JBIMES-24-09jbi.global

84.

Peters

M. D. J.

Marnie

Tricco

A. C.

Pollock

Munn

Alexander

McInerney

Godfrey

C. M.

Khalil

(2021). Updated methodological guidance for conducting scoping reviews. JBI Evidence Implementation, 19(1), 3–10. https://doi.org/10.1097/XEB.0000000000000277

85.

Pillai

Ghanghorkar

Sivathanu

Algharabat

Rana

N. P.

(2024). Adoption of artificial intelligence (AI)-based employee experience (EEX) chatbots. Information Technology & People, 37(1), 449–478. https://doi.org/10.1108/ITP-04-2022-0287

86.

Putnam

L. L.

Fairhurst

G. T.

Banghart

(2016). Contradictions, dialectics, and paradoxes in organizations: A constitutive approach. The Academy of Management Annals, 10(1), 65–171. https://doi.org/10.5465/19416520.2016.1162421

87.

Qin

Jia

Luo

Liao

Huang

(2023). Perceived fairness of human managers compared with artificial intelligence in employee performance evaluation. Journal of Management Information Systems, 40(4), 1039–1070. https://doi.org/10.1080/07421222.2023.2267316

88.

Raisch

Birkinshaw

(2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34(3), 375–409. https://doi.org/10.1177/0149206308316058

89.

Raisch

Krakowski

(2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072

90.

Rajtmajer

S. M.

Errington

T. M.

Hillary

F. G.

(2022). How failure to falsify in high-volume science contributes to the replication crisis. eLife, 11, Article e78830. https://doi.org/10.7554/eLife.78830

91.

Registre

J. F. R.

Saba

(2024). A typology of AI-based tasks for the HR function. Strategic HR Review, 23(5), 170–175. https://doi.org/10.1108/SHR-04-2024-0026

92.

Røhnebæk

M. T.

Breit

(2022). “Damned if you do and damned if you don’t”: A framework for examining double binds in public service organizations. Public Management Review, 24(7), 1001–1023. https://doi.org/10.1080/14719037.2021.1882542

93.

Sandberg

Alvesson

(2021). Meanings of theory: Clarifying theory through typification. Journal of Management Studies, 58(2), 487–516. https://doi.org/10.1111/joms.12587

94.

Sandberg

Tsoukas

(2020). Sensemaking reconsidered: Towards a broader understanding through phenomenology. Organization Theory, 1(1), 2–3. https://doi.org/10.1177/2631787719879937

95.

Sanjeewa

Iyer

Apputhurai

Wickramasinghe

Meyer

(2024). Empathic conversational agent platform designs and their evaluation in the context of mental health: A systematic review. JMIR Mental Health, 11, Article e58974. https://doi.org/10.2196/58974

96.

Schad

Lewis

M. W.

Raisch

Smith

W. K.

(2016). Paradox research in management science: Looking back to move forward. The Academy of Management Annals, 10(1), 5–64. https://doi.org/10.5465/19416520.2016.1162422

97.

Shahzad

M. U.

(2024). Core competencies for digital leadership development: A perspective from the lens of paradox theory. The Bottom Line, 37(4), 454–472. https://doi.org/10.1108/BL-10-2023-0278

98.

Simon

(2023). Reflexivity 3: Breaking out of the reflexive loop to decolonize practice. Murmurations: Journal of Transformative Systemic Practice, 6(2), 53–71. https://doi.org/10.28963/6.2.4

99.

Sitkin

S. B.

See

K. E.

Miller

C. C.

Lawless

M. W.

Carton

A. M.

(2011). The paradox of stretch goals: Organizations in pursuit of the seemingly impossible. Academy of Management Review, 36(3), 544–566. https://doi.org/10.5465/amr.2008.0038

100.

Smith

W. K.

Erez

Jarvenpaa

Lewis

M. W.

Tracey

(2017). Adding complexity to theories of paradox, tensions, and dualities of innovation and change: Introduction to organization studies special issue on paradox, tensions, and dualities of innovation and change. Organization Studies, 38(3–4), 303–317. https://doi.org/10.1177/0170840617693560

101.

Smith

W. K.

Lewis

M. W.

(2011). Toward a theory of paradox: A dynamic-equilibrium model of organizing. Academy of Management Review, 36(2), 381–403. https://doi.org/10.5465/amr.2009.0223

102.

Sorin

Brin

Barash

Konen

Charney

Nadkarni

Klang

(2024). Large language models and empathy: A systematic review. Journal of Medical Internet Research, 26, Article e52597. https://doi.org/10.2196/52597

103.

Spitzberg

B. H.

(1993). The dialectics of (in)competence. Journal of Social and Personal Relationships, 10(1), 137–158. https://doi.org/10.1177/0265407593101009

104.

Spitzberg

B. H.

Cupach

W. R.

(2011). Interpersonal skills. In Knapp

M. L.

Daly

J. A.

(Eds.), Handbook of interpersonal communication (4th ed., pp. 481–524). Sage.

105.

Tang

P. M.

Koopman

Mai

K. M.

De Cremer

Zhang

J. H.

Reynders

C. T. S.

Chen

I.-H.

(2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. Journal of Applied Psychology, 108(11), 1766–1789. https://doi.org/10.1037/apl0001103

106.

Tong

Flemming

McInnes

Oliver

Craig

(2012). Enhancing transparency in reporting the synthesis of qualitative research (ENTREQ). BMC Medical Research Methodology, 12, 181. https://doi.org/10.1186/1471-2288-12-181

107.

Tracy

S. J.

(2004). Dialectic, contradiction, or double bind? Analyzing and theorizing employee reactions to organizational tension. Journal of Applied Communication Research, 32(2), 119–146. https://doi.org/10.1080/0090988042000210025

108.

Tricco

A. C.

Lillie

Zarin

O’Brien

K. K.

Colquhoun

Levac

Peters

M. D. J.

Horsley

Weeks

Hempel

Akl

E. A.

Chang

McGowan

Stewart

Hartling

Aldcroft

Wilson

M. G.

Garritty

Straus

S. E.

(2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. https://doi.org/10.7326/M18-0850

109.

VandeWalle

(1997). Development and validation of a work-domain goal-orientation instrument. Educational and Psychological Measurement, 57(6), 995–1015. https://doi.org/10.1177/0013164497057006009

110.

Von Krogh

Rossi-Lamastra

Haefliger

(2012). Phenomenon-based research in management and organization science: When is it rigorous, and does it matter? Long Range Planning, 45(4–5), 277–298. https://doi.org/10.1016/j.lrp.2012.05.001

111.

Vrontis

Christofi

Pereira

Tarba

Makrides

Trichina

(2022). Artificialintelligence, robotics, advanced technologies, and human resource management: Asystematic review. International Journal of Human Resource Management, 33(6), 1237–1266. https://doi.org/10.1080/09585192.2020.1871398

112.

Ward

(2023). Choice, uncertainty, and decision superiority: Is less AI-enabled decision support more effective? IEEE Transactions on Human-Machine Systems, 53(4), 781–791. https://doi.org/10.1109/THMS.2023.3279036

113.

Weber

(2023). Unrealistic optimism regarding artificial intelligence opportunities in human resource management. International Journal of Knowledge Management, 19(1), 1–19. https://doi.org/10.4018/IJKM.317217

114.

Whetten

D. A.

(1989). What constitutes a theoretical contribution? Academy of Management Review, 14(4), 490–495. https://doi.org/10.2307/258554

115.

Xia

Chiu

T. K. F.

Lee

Sanusi

I. T.

Dai

Chai

C. S.

(2022). A self-determination theory design approach for inclusive and diverse AI education. Computers & Education, 189(C), Article 104582. https://doi.org/10.1016/j.compedu.2022.104582

116.

Fan

(2023). Employees’ appraisals and trust in artificial intelligence’s transparency and opacity. Behavioral Sciences, 13(4), 344. https://doi.org/10.3390/bs13040344

117.

Zhang

Amos

(2024). Dignity and the use of algorithms in performance evaluation. Behaviour & Information Technology, 43(2), 401–418. https://doi.org/10.1080/0144929X.2022.2164214

The Competence Paradox: Rethinking Goal-Setting in the Age of Algorithmic Management

Abstract

Keywords

Get full access to this article

References