Abstract
Investments in artificial intelligence, autonomous robotics, and similar technical systems continue to accelerate as organizations pursue opportunities to strengthen their performance and create even greater value for stakeholders. Despite voluminous guidance and best practices on designing and operationalizing such technical systems, many organizations are not achieving their expected returns and performance levels. The problem might be a biased view of organizations as primarily human-centric systems, which can place unnecessary limits on the performance of intelligent robots, artificial intelligence, and similar technical systems. Reimagining and purposefully designing organizations as systems composed of human and non-human knowledge workers co-performing tasks for organizational goal attainment can generate more robust performance and strengthen corporate returns on investments in such sophisticated systems. Non-human knowledge workers (NHKWs) are synthetic computational agents characterized by the conjunction of four attributes—information processing power, knowledge work, task-level employment, and more comprehensive organizational integration—distinguishing them from more common artificial intelligence, autonomous robotics systems, and autonomous vehicles frameworks. More gainful employment of NHKWs, and similar systems, is primarily a design issue and one that is largely separate from the capabilities NHKWs might possess. Using an organizational technology framework, this paper offers managers and organizational designers a systematic approach that can harness NHKW capabilities more effectively, thereby producing stronger organizational performance.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Availability of data and materials
Not applicable.
Notes
Humans gather, process, and exchange information for a variety of purposes (Schroder et al. 1967), which makes humans, themselves, information systems. The term AIS is used to distinguish artificial systems, such as intelligent robots (Burton et al. 2021, 2023) and intelligent autonomous systems (Burton et al. 2020; Kuru and Khan 2021), that similarly gather, process, and exchange information from humans and other natural information systems. The benefits of using the term AIS to assist distinguishing between natural and artificial systems, and for concision seem to outweigh potential issues resulting from its use elsewhere.
The terms human, person, individual, and their plural forms are used interchangeably, for the most part, in this paper.
Deliveroo and Uber Eats are food delivery companies, and Lyft and Uber are rideshare companies; studies generally recognize the four firms for their strategic use of AIS (Burton et al. 2021; Lee et al. 2015; Rosenblat 2018; Rosenblat and Stark 2016). This discussion treats each firm as using a single AIS to perform the organizational tasks described; this seems reasonable because of the extent to which the firms have systematically integrated the AIS into their organizational technologies, which is described subsequently.
References
Agrawal A, Gans J, Goldfarb A (2018) Prediction machines: the simple economics of artificial intelligence. Harvard Business Review Press, Boston
Arrow K (1974) The limits of organization. W. W. Norton & Co., New York
Arrow K (1996) The economics of information: an exposition. Empirica 23:119–128. https://doi.org/10.1007/BF00925335
Barnard C (1938) The functions of the executive. Harvard University Press, Cambridge
Bartoš M, Bulej V, Bohušík M, Stanček J, Ivanov V, Macek P (2021) An overview of robot applications in automotive industry. Transp Res Procedia 55:837–844. https://doi.org/10.1016/j.trpro.2021.07.052
Baumann O, Wu B (2023) Managerial hierarchy in AI-driven organizations. J of Organ Des 12:1–5. https://doi.org/10.1007/s41469-023-00147-9
Blake R (2023) Rise of warehouse robots spurs efficiencies—and safety concerns. Forbes. https://www.forbes.com/sites/richblake1/2023/11/24/rise-of-warehouse-robots-spurs-efficiencies-and-safety-concerns. Accessed 30 Apr 2024
Buettner, Jr RR (2007) The impact of communal knowledge mechansims [sic] on project work. Dissertation, Stanford University
Burton RM, Obel B (2004) Strategic organizational diagnosis and design: The dynamics of fit, 3rd edn. Springer, New York. https://doi.org/10.1007/978-1-4419-9114-0
Burton RM, Obel B (2018) The science of organizational design: fit between structure and coordination. J Org Des 7(5):1–13. https://doi.org/10.1186/s41469-018-0029-2
Burton RM, Obel B, Håkonsson DD (2023) Expanding the organization design space: the emergence of AI robot bosses. J Org Des. https://doi.org/10.1007/s41469-023-00155-9
Burton JW, Stein MK, Jensen TB (2019) A systematic review of algorithm aversion in augmented decision making. J Behav Decis Mak 33(2):220–239. https://doi.org/10.1002/bdm.2155
Burton S, Habli I, Lawton T, McDermid J, Morgan P, Porter Z (2020) Mind the gaps: assuring the safety of autonomous systems from an engineering, ethical, and legal perspective. Artif Intell 279(2020):1–16. https://doi.org/10.1016/j.artint.2019.103201
Burton RM, Obel B, Håkonsson DD (2021) Organizational design: A step-by-step approach, 4th edn. Cambridge University Press, Cambridge
Cao G, Duan Y, Edwards JS, Dwivedi YK (2021) Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making. Technovation 106(2021):1–15. https://doi.org/10.1016/j.technovation.2021.102312
Carley K, Gasser L (1999) Computational organization theory. In: Weiss G (ed) Multi-agent systems: A modern approach to distributed artificial intelligence. MIT Press, Cambridge, pp 299–330
Choudhary V, Marchetti A, Shrestha YR, Puranam P (2023) Human-AI ensembles: when can they work? J Manag 2023:1–34. https://doi.org/10.1177/01492063231194968
Christensen M, Knudsen T (2013) How decisions can be organized – and why it matters. J Org Des 2(3):41–50. https://doi.org/10.7146/jod.8566
Cohen MD, March JG (1974) Leadership and ambiguity: The American college president. McGraw-Hill, New York
Cummings TG, Markus ML (1979) A socio-technical systems view of organizations. In: Cooper CL (ed) Behavioral problems in organizations. Prentice Hall, Hoboken, pp 59–77
Cyert RM, March JG (1963) A behavioral theory of the firm. Cambridge University Press, Cambridge
D’Silva, V, Lawler, B (2022) What makes a company successful at using AI? Harvard Bus Rev. https://hbr.org/2022/02/what-makes-a-company-successful-at-using-ai. Accessed 29 Jan 2024
Daft RL, Lengel RH (1986) Organizational information requirements, media richness and structural design. Manag Sci 32(5):554–571. https://doi.org/10.1287/mnsc.32.5.554
Datta P (2020) Why do most AI projects fail? Forbes. https://www.forbes.com/sites/forbestechcouncil/2020/10/14/why-do-most-ai-projects-fail. Accessed 29 Jan 2024
Davenport TH (2016) Rise of the strategy machines. MIT Sloan Manag Rev 58(1):29–30. https://sloanreview.mit.edu/article/rise-of-the-strategy-machines. Accessed 29 Jan 2024
Davenport TH, Guha A, Grewal D, Bressgott T (2020) How artificial intelligence will change the future of marketing. J Acad Mark Sci 48(1):24–42. https://doi.org/10.1007/s11747-019-00696-0
Davies A, Oca A, Pireto I, Sarilar U (2023) Getting warehouse automation right. McKinsey & Company. https://www.mckinsey.com/capabilities/operations/our-insights/getting-warehouse-automation-right. Accessed 29 Jan 2024
De Cremer D, McGuire J (2022) Human–algorithm collaboration works best if humans lead (because it is fair!). Soc Justice Res 35(1):33–55. https://doi.org/10.1007/s11211-021-00382-z
Dellermann D, Calma A, Lipusch N, Weber T, Weigel S, Ebel P (2019) The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems. Proc Annual Hawaii Int Conf Sys Sci. https://doi.org/10.24251/hicss.2019.034
Drucker PF (1988) The coming of the new organization. Harvard Bus Rev 66(1):45–53. https://hbr.org/1988/01/the-coming-of-the-new-organization. Accessed 29 Jan 2024
Drucker PF (1993) The rise of the knowledge society. Wilson Q 17(2):52–71. https://archive.wilsonquarterly.com/essays/rise-knowledge-society-0. Accessed 29 Jan 2024
Endsley MR (2017) From here to autonomy. Hum Factors 59(1):5–27. https://doi.org/10.1177/0018720816681350
Fayol H (1916) General principles of management. In: Shafritz JM, Ott JS (eds) Classics of organization theory, 4th edn. Harcourt Brace College Publishers, New York, pp 52–65
Fountaine T, McCarthy B, Tamim S (2019) Building the AI-powered organization. Harvard Bus Rev:62–73. https://hbr.org/2019/07/building-the-ai-powered-organization. Accessed 29 Jan 2024
Frick W (2015) When your boss wears metal pants. Harvard Bus Rev. https://hbr.org/2015/06/when-your-boss-wears-metal-pants. Accessed 25 Jan 2024
Galbraith JR (1977) Organization design. Addison-Wesley Publishing Co., Menlo Park
Glikson E, Woolley AW (2020) Human trust in artificial intelligence: review of empirical research. Acad Manag Annals 14(2):627–660. https://doi.org/10.5465/annals.2018.0057
Grønsund T, Aanestad M (2020) Augmenting the algorithm: emerging human-in-the-loop work configurations. J Strateg Inf Sys 29(2):1–16. https://doi.org/10.1016/j.jsis.2020.101614
Gulick L (1937) Notes on the theory of organization. In: Shafritz JM, Ott JS (eds) Classics of organization theory, 4th edn. Harcourt Brace College Publishers, New York, pp 86–95
Haesevoets T, De Cremer D, Dierckx K, van Hiel A (2021) Human-machine collaboration in managerial decision making. Comput Hum Behav 119. https://doi.org/10.1016/j.chb.2021.106730
Huang MH, Rust R, Maksimovic V (2019) The feeling economy: managing in the next generation of artificial intelligence (AI). Calif Manag Rev 61(4):43–65. https://doi.org/10.1177/0008125619863436
Iansiti, M, Lakhani KR (2020) Competing in the age of AI. Harvard Bus Rev. https://hbr.org/2020/01/competing-in-the-age-of-ai. Accessed 30 Apr 2024
Jain R, Garg N, Khera SN (2022) Effective human-AI work design for collaborative decision-making. Kybernetes 52(11):5017–5040. https://doi.org/10.1108/K-04-2022-0548
Jansen E (2000) Work processes: Tasks and technology [PowerPoint slides].
Jarrahi MH (2018) Artificial intelligence and the future of work: human-AI symbiosis in organizational decision making. Bus Horiz 61(4):577–586. https://doi.org/10.1016/j.bushor.2018.03.007
Kahneman D (2013) Thinking, fast and slow. Farrar, Straus and Giroux, New York
Kuru K, Khan W (2021) A framework for the synergistic integration of fully autonomous ground vehicles with smart city. IEEE Access 9:923–948. https://doi.org/10.1109/ACCESS.2020.3046999
Lawrence PR, Lorsch JW (1967) Differentiation and integration in complex organizations. Adm Sci Q 12(1):1–47. https://doi.org/10.2307/2391211
Lee MK (2018) Understanding perception of algorithmic decisions: fairness, trust, and emotion in response to algorithmic management. Big Data Soc 2018:1–16. https://doi.org/10.1177/2053951718756684
Lee MK, Kusbit D, Metsky E, Dabbish L (2015) Working with machines: The impact of algorithmic and data-driven management on human works. Proc 2015 33rd Annu ACM Conf on Human Factors in Comput Syst (CHI). ACM, New York, pp 1603–1612. https://doi.org/10.1145/2702123.2702548
Levitt RE, Cohen GP, Kunz JC, Nass CI, Christiansen T, Jin Y (1994) The “Virtual Design Team”: simulating how organization structure and information processing tools affect team performance. In: Carley K, Prietula M (eds) Computational organization theory. Lawrence Erlbaum Associates, Mahwah, pp 1–18
Mahmud H, Islam AN, Ahmed SI, Smolander K (2022) What influences algorithmic decision-making? A systematic literature review on algorithm aversion. Technol Forecast and Soc Change 175(2022):1–26. https://doi.org/10.1016/j.techfore.2021.121390
Makarius EE, Mukherjee D, Fox JD, Fox AK (2020) Rising with the machines: a sociotechnical framework for bringing artificial intelligence into the organization. J Bus Res 120(2020):262–273. https://doi.org/10.1016/j.jbusres.2020.07.045
Malone TW, Crowston K (1991) Toward an interdisciplinary theory of coordination [MIT Sloan Working Paper #3294-91-MSA]. http://hdl.handle.net/1721.1/2356. Accessed 29 Jan 2024
March JG, Simon HA (1958) Organizations. John Wiley & Sons Inc, New York
Mayo E (1945) The social problems of an industrial civilization. The Andover Press, Andover
Mintzberg H (1973) The nature of managerial work. HarperCollins College Div, New York
Mintzberg H (1993) Structure in fives: Designing effective organizations. Prentice Hall, Englewood Cliffs
Mittal N, Saif I, Ammanath B (2022) State of AI in the Enterprise, 5th edn. Deloitte. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/deloitte-analytics/us-ai-institute-state-of-ai-fifth-edition.pdf. Accessed 29 Jan 2024
Mortimore D, Aten K, Buettner Jr. RR (2023a) A new technology rises: non-human knowledge workers and decision-making in a system of complex systems. Proc 2023 18th Annu Syst of Syst Eng Conf (SoSE). IEEE, New York, pp 1–8. https://doi.org/10.1109/SoSE59841.2023.10178624
Mortimore D, Buettner Jr RR, Chabot E (2023b) Designing organizations of human and non-human knowledge workers. In: Thomson R, Al-khateeb S, Burger A, Pyke A (eds) Lecture notes in computer science: Vol. 14161. Proc 16th Int Conf on Soc Comput, Behav-Cult Model & Predict and Behav Represent in Model and Simul (SBP-BRiMS). Springer Nature, Berlin, pp 179–188. https://doi.org/10.1007/978-3-031-43129-6_18
Murray A, Rhymer J, Sirmon DG (2021) Humans and technology: forms of conjoined agency in organizations. Acad Manag Rev 46(3):552–571. https://doi.org/10.5465/amr.2019.0186
Nadler D, Tushman M (1988) Strategic organization design: concepts, tools, & processes. Scott, Foresman and Co, Glenview
Narayanan J, Puranam P, Van Vugt M (2022) Human-centric organizing: A perspective from evolutionary psychology [Institut Européen d'Administration des Affaires (INSEAD) Working Paper]. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3959703#. Accessed 28 Jan 2024
National Academies of Sciences, Engineering, and Medicine (NASEM) (2019) A decadal survey of the social and behavioral sciences: A research agenda for advancing intelligence analysis. The National Academies Press, Washington, DC. https://doi.org/10.17226/25335
O’Connor S (2016) When your boss is an algorithm. FT Mag (2016):1–17. https://www.ft.com/content/88fdc58e-754f-11e6-b60a-de4532d5ea35. Accessed 30 Apr 2024
Parker SK, Grote G (2022) Automation, algorithms, and beyond: why work design matters more than ever in a digital world. Appl Psychol 71(4):1169–1653. https://doi.org/10.1111/apps.12241
Parry K, Cohen M, Bhattacharya S (2016) Rise of the machines: a critical consideration of automated leadership decision making in organizations. Gr Organ Manag 41(5):571–594. https://doi.org/10.1177/1059601116643442
Perrow C (1967) A framework for the comparative analysis of organizations. Am Sociol Rev 32(2):194–208. https://doi.org/10.2307/2091811
Perrow C (1973) The short and glorious history of organization theory. Organ Dyn 2(1):2–15. https://doi.org/10.1016/0090-2616(73)90007-7
Perrow C (1999) Normal accidents: Living with high-risk technologies. Princeton University Press, Princeton
Puranam P (2021) Human–AI collaborative decision-making as an organization design problem. J Org Des 10:75–80. https://doi.org/10.1007/s41469-021-00095-2
Puranam P, Mehra R (2022) Better human-AI collaboration may depend on workflow design. Institut Européen d'Administration des Affaires (INSEAD). https://knowledge.insead.edu/operations/better-human-ai-collaboration-may-depend-workflow-design. Accessed 28 Jan 2024
Puranam P, Raveendran M, Knudsen T (2012) Organization design: the epistemic interdependence perspective. Acad of Manag Review 37(3):419–440. https://doi.org/10.5465/amr.2010.0535
Rabb N, Fernbach PM, Sloman SA (2019) Individual representation in a community of knowledge. Trends Cogn Sci 23(10):891–902. https://doi.org/10.1016/j.tics.2019.07.011
Rosenblat A (2018) Uberland: How algorithms are rewriting the rules of work. University of California Press, Oakland
Rosenblat A, Stark L (2016) Algorithmic labor and information asymmetries: a case study of Uber’s drivers. Int J Commun. 10(2016):3758–3784
Saran C (2022) Why some businesses are failing at AI. ComputerWeekly.com. https://www.computerweekly.com/news/252526204/Why-some-businesses-are-failing-at-AI. Accessed 29 Jan 2024
Schroder HM, Driver MJ, Streufert S (1967) Human information processing: Individuals and groups functioning in complex social situations. Holt, Rinehart and Winston, Inc, New York
Seeber I, Bittner E, Briggs RO, De Vreede T, De Vreede GJ, Elkins A, Maier R, Merz AB, Oeste-Reiß S, Randrup N, Schwabe G, Sollner M (2020) Machines as teammates: a research agenda on AI in team collaboration. Inf and Manag 57(2):1–22. https://doi.org/10.1016/j.im.2019.103174
Selznick P (1948) Foundations of the theory of organization. Am Sociol Rev 13(1):25–35. https://doi.org/10.2307/2086752
Simon HA (1947) Administrative behavior: A study of decision-making processes in administrative organization, 4th edn. Free Press, New York
Simon HA (1973) Applying information technology to organization design. Public Adm Rev 33(3):268–278. https://doi.org/10.2307/974804
Sloman SA, Fernbach PM (2017) The knowledge illusion: Why we never think alone. Riverhead Books, New York
Smith A (1776) The wealth of nations. Penguin Random House, New York
Snow CC, Øystein DF, Langer AM (2017) Designing the digital organization. J Organ Des 6(7):1–13. https://doi.org/10.1186/s41469-017-0017-y
Taylor FW (1911) The Principles of scientific management. Cosimo, New York
Thomas KW, Velthouse BA (1990) Cognitive elements of empowerment: an “interpretive” model of intrinsic task motivation. The Acad Manag Rev 15(4):666–681. https://doi.org/10.2307/258687
Thompson JD (1967) Organizations in action. Routledge, New York
Tinguely PN, Lee J, He VF (2023) Designing human resource management systems in the age of AI. J Organ Des 2023:1–7. https://doi.org/10.1007/s41469-023-00153-x
van Dongen K, van Maanen P-P (2013) A framework for explaining reliance on decision aids. Int J Hum-Comput Stud 71(4):410–424. https://doi.org/10.1016/j.ijhcs.2012.10.018
von Krogh G (2018) Artificial intelligence in organizations: new opportunities for phenomenon-based theorizing. Acad Manag Discov 4(4):404–409. https://doi.org/10.5465/amd.2018.0084
Wang N, Pynadath DV, Hill SG (2016) Trust calibration within a human-robot team: comparing automatically generated explanations. Proc 2016 11th ACM/IEEE Int Conf on Hum-Robot Interact. IEEE, New York. https://doi.org/10.1109/hri.2016.7451741
Weber M (1964) The theory of social and economic organization (Henderson AM, Parsons T, Trans). Free Press, New York
Wegner DM, Giuliano T, Hertel PT (1985) Cognitive interdependence in close relationships. In: Ickes WJ (ed) Compatible and incompatible relationships. Springer-Verlag, Amsterdam, pp 253–276. https://doi.org/10.1007/978-1-4612-5044-9_12
Wegner DM, Raymond P, Erber R (1991) Transactive memory in close relationships. J of Pers and Soc Psychol 61(6):923–929. https://doi.org/10.1037/0022-3514.61.6.923
Willcox G, Rosenberg L (2019) Swarm intelligence amplifies the IQ of collaborating teams. Proc of the 2019 Second Int Conf on Artif Intell for Ind. IEEE, New York, pp 1–6. https://doi.org/10.1109/ai4i46381.2019.00036
Xu W, Dainoff MJ, Ge L, Gao Z (2022) Transitioning to human interaction with AI systems: new challenges and opportunities for HCI professionals to enable human-centered AI. Int J Hum-Comput Interact 39(3):494–518. https://doi.org/10.1080/10447318.2022.2041900
Acknowledgements
I thank Kathleen Carley, Kathryn Aten, Cheryldee Huddleston, Dan Boger, and Raymond Buettner, Jr. for their recommendations and the opportunity to work with them. I am particularly grateful for the critical feedback and time invested by the anonymous reviewers and Richard Burton, Associate Editor: their insights strengthened this paper, considerably. This research is supported by the Office of Naval Research Cognitive Science and Human & Machine Teaming, Cooperative Autonomous Swarm Technology, and In-House Laboratory Independent Research programs.
Funding
This research is funded by the Office of Naval Research Cognitive Science and Human & Machine Teaming, Cooperative Autonomous Swarm Technology, and In-House Laboratory Independent Research programs.
Author information
Authors and Affiliations
Contributions
The author conceputalized the non-human knowledge worker (NHKW) construct, formulated the theoretical arguments, and wrote the manuscript.
Corresponding author
Ethics declarations
Competing interests
The author declares that he has no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mortimore, D. Moving beyond human-centric organizational designs. J Org Design (2024). https://doi.org/10.1007/s41469-024-00167-z
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s41469-024-00167-z
Keywords
- Artificial intelligence
- Computational agents
- Robots
- AI boss
- Algorithmic manager
- Cognitive bias
- Team performance
- Organizational design