Substance, discourse, and practice: a review of communication research on automation

References

• Aakhus, M. (2007). Communication as design. Communication Monographs, 74(1), 112–117. https://doi.org/10.1080/03637750701196383
   Web of Science ®Google Scholar
• Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716
   Web of Science ®Google Scholar
• Adamson, A. S., & Smith, A. (2018). Machine learning and health care disparities in dermatology. JAMA Dermatology, 154(11), 1247–1248. https://doi.org/10.1001/jamadermatol.2018.2348
   PubMed Web of Science ®Google Scholar
• Alaimo, C., & Kallinikos, J. (2021). Managing by data: Algorithmic categories and organizing. Organization Studies, 42(9), 1385–1407. https://doi.org/10.1177/0170840620934062
   Web of Science ®Google Scholar
• Al-Khateeb, M. T. (2021). Toward a rhetorical account of refugee encounters: Biometric screening technologies and failed promises of mobility. Rhetoric Society Quarterly, 51(1), 15–26. https://doi.org/10.1080/02773945.2020.1841276
   Web of Science ®Google Scholar
• Alorwu, A., Savage, S., van Berkel, N., Ustalov, D., Drutsa, A., Oppenlaender, J., Bates, O., Hettiachchi, D., Gadiraju, U., Goncalves, J., & Hosio, S. (2022). REGROW: Reimagining global crowdsourcing for better human-AI collaboration. Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3491101.3503725.
   Google Scholar
• Andrejevic, M., Dencik, L., & Treré, E. (2020). From pre-emption to slowness: Assessing the contrasting temporalities of data-driven predictive policing. New Media & Society, 22(9), 1528–1544. https://doi.org/10.1177/1461444820913565
   Web of Science ®Google Scholar
• Applebaum, E., & Albin, P. (1989). Computer rationalization and the transformation of work: Lessons from the insurance industry. In S. Wood (Ed.), The transformation of work? Skill, flexibility, and the labour process (pp. 247–265). Routledge.
   Google Scholar
• Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3
   Web of Science ®Google Scholar
• Bader, V., & Kaiser, S. (2019). Algorithmic decision-making? The user interface and its role for human involvement in decisions supported by artificial intelligence. Organization, 26(5), 655–672. https://doi.org/10.1177/1350508419855714
   Web of Science ®Google Scholar
• Bailey, D. E., & Barley, S. R. (2020). Beyond design and use: How scholars should study intelligent technologies. Information and Organization, 30(2), 100286. https://doi.org/10.1016/j.infoandorg.2019.100286
   Web of Science ®Google Scholar
• Bailey, D. E., & Leonardi, P. M. (2015). Technology choices: Why occupations differ in their embrace of new technology. The MIT Press.
   Google Scholar
• Bailey, D. E., Leonardi, P. M., & Chong, J. (2010). Minding the gaps: Understanding technology interdependence and coordination in knowledge work. Organization Science, 21(3), 713–730. https://doi.org/10.1287/orsc.1090.0473
   Web of Science ®Google Scholar
• Bainbridge, L. (1983). Ironies of automation. Automatica, 19(6), 775–779. https://doi.org/10.1016/0005-1098(83)90046-8
   Web of Science ®Google Scholar
• Barbour, J. B., Treem, J. W., & Kolar, B. (2018). Analytics and expert collaboration: How individuals navigate relationships when working with organizational data. Human Relations, 71(2), 256–284. https://doi.org/10.1177/0018726717711237
   Web of Science ®Google Scholar
• Barcellos Almeida, M., & Farinelli, F. (2017). Ontologies for the representation of electronic medical records: The obstetric and neonatal ontology. Journal of the Association for Information Science and Technology, 68(11), 2529–2542. https://doi.org/10.1002/asi.23900
   Web of Science ®Google Scholar
• Barge, J. K., Lee, M., Maddux, K., Nabring, R., & Townsend, B. (2008). Managing dualities in planned change initiatives. Journal of Applied Communication Research, 36(4), 364–390. https://doi.org/10.1080/00909880802129996
   Web of Science ®Google Scholar
• Barrett, A. (2020). ‘I can tell you right now, EHR does not improve communication. It does not improve healthcare’: Understanding how providers make sense of advanced information technology workarounds. Journal of Applied Communication Research, 48(5), 537–557. https://doi.org/10.1080/00909882.2020.1820551
   Web of Science ®Google Scholar
• Barrett, M., Oborn, E., Orlikowski, W. J., & Yates, J. (2012). Reconfiguring boundary relations: Robotic innovations in pharmacy work. Organization Science, 23(5), 1448–1466. https://doi.org/10.1287/orsc.1100.0639
   Web of Science ®Google Scholar
• Beam, M. A. (2014). Automating the news: How personalized news recommender system design choices impact news reception. Communication Research, 41(8), 1019–1041. https://doi.org/10.1177/0093650213497979
   Web of Science ®Google Scholar
• Beane, M. (2019). Learning to work with intelligent machines. Harvard Business Review, 97(5), 140–148. https://hbr.org/2019/09/learning-to-work-with-intelligent-machines
   Web of Science ®Google Scholar
• Beattie, A., Edwards, A. P., & Edwards, C. (2020). A bot and a smile: Interpersonal impressions of chatbots and humans using emoji in computer-mediated communication. Communication Studies, 71(3), 409–427. https://doi.org/10.1080/10510974.2020.1725082
   Web of Science ®Google Scholar
• Belair-Gagnon, V., Lewis, S. C., & Agur, C. (2020). Failure to launch: Competing institutional logics, intrapreneurship, and the case of chatbots. Journal of Computer-Mediated Communication, 25(4), 291–306. https://doi.org/10.1093/jcmc/zmaa008
   Web of Science ®Google Scholar
• Benjamin, R. (2019). Race after technology: Abolitionist tools for the New Jim Code. Polity Press.
   Google Scholar
• Berkelaar, B. L. (2017). Different ways new information technologies influence conventional organizational practices and employment relationships: The case of cybervetting for personnel selection. Human Relations, 70(9), 1115–1140. https://doi.org/10.1177/0018726716686400
   Web of Science ®Google Scholar
• Bisel, R. S., & Barge, J. K. (2011). Discursive positioning and planning change in organizations. Human Relations, 64(2), 257–283. https://doi.org/10.1177/0018726710375996
   Web of Science ®Google Scholar
• Blauner, R. (1964). Alienation and freedom: The factory worker and his industry. University of Chicago Press.
   Google Scholar
• Bolsover, G., & Howard, P. (2019). Chinese computational propaganda: Automation, algorithms and the manipulation of information about Chinese politics on Twitter and Weibo. Information, Communication & Society, 22(14), 2063–2080. https://doi.org/10.1080/1369118X.2018.1476576
   Web of Science ®Google Scholar
• boyd, d., & Crawford, K. (2012). Critical questions for big data. Information, Communication & Society, 15(5), 662–679. https://doi.org/10.1080/1369118X.2012.678878
   Web of Science ®Google Scholar
• Brandtzaeg, P. B., Skjuve, M., & Følstad, A. (2022). My AI friend: How users of a social chatbot understand their human–AI friendship. Human Communication Research, 48(3), 404–429. https://doi.org/10.1093/hcr/hqac008
   Web of Science ®Google Scholar
• Brynjolfsson, E., & McAfee, A. (2016). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company.
   Google Scholar
• Brynjolfsson, E., & Mitchell, T. (2017). What can machine learning do? Workforce implications. Science, 358(6370), 1530–1534. https://doi.org/10.1126/science.aap8062
   PubMed Web of Science ®Google Scholar
• Carlson, M. (2018). Automating judgment? Algorithmic judgment, news knowledge, and journalistic professionalism. New Media & Society, 20(5), 1755–1772. https://doi.org/10.1177/1461444817706684
   Web of Science ®Google Scholar
• Carlson, P. A. (2001). Information technology and organizational change. Journal of Technical Writing and Communication, 31(1), 77–95. https://doi.org/10.2190/0LRE-8DKQ-JF8E-49RE
   Google Scholar
• Carter, M., & Egliston, B. (2021). What are the risks of virtual reality data? Learning analytics, algorithmic bias and a fantasy of perfect data. New Media & Society, 1–20. https://doi.org/10.1177/14614448211012794
   Google Scholar
• Chapanis, A. (1965). On the allocation of functions between men and machines. Occupational Psychology, 39, 1–11.
   Google Scholar
• Chaplin, C. (Director). (1936). Modern Times. United Artists.
   Google Scholar
• Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503
   Web of Science ®Google Scholar
• Chen, M. (2019, November 27). The robots are coming for our jobs. The Nation. https://www.thenation.com/article/archive/work-automation-jobs/
   Google Scholar
• Chen, Y. K., & Wen, C.-H. R. (2021). Impacts of attitudes toward government and corporations on public trust in artificial intelligence. Communication Studies, 72(1), 115–131. https://doi.org/10.1080/10510974.2020.1807380
   Web of Science ®Google Scholar
• Chui, M., Manyika, J., & Miremadi, M. (2015). Four fundamentals of workplace automation. McKinsey Quarterly, 1–9. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/four-fundamentals-of-workplace-automation
   Google Scholar
• Collins, H. M. (2001). Tacit knowledge, trust and the Q of sapphire. Social Studies of Science, 31(1), 71–85. https://doi.org/10.1177/030631201031001004
   Web of Science ®Google Scholar
• Crawford. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
   Google Scholar
• Crowston, K., Erickson, I., & Nickerson, J. (2022). The work in the age of intelligent machines research coordination network. https://waim.network/about.
   Google Scholar
• Curchod, C., Patriotta, G., Cohen, L., & Neysen, N. (2020). Working for an algorithm: Power asymmetries and agency in online work settings. Administrative Science Quarterly, 65(3), 644–676. https://doi.org/10.1177/0001839219867024
   Web of Science ®Google Scholar
• Darr, A. (2018). Automatons, sales-floor control and the constitution of authority. Human Relations, 72(5), 889–909. https://doi.org/10.1177/0018726718783818
   Web of Science ®Google Scholar
• Demo, A. T. (2017). Hacking agency: Apps, autism, and neurodiversity. Quarterly Journal of Speech, 103(3), 277–300. https://doi.org/10.1080/00335630.2017.1321135
   Web of Science ®Google Scholar
• Diakopoulos, N. (2019). Automating the news: How algorithms are rewriting the media. Harvard University Press.
   Google Scholar
• Dodel, M., & Mesch, G. S. (2020). Perceptions about the impact of automation in the workplace. Information, Communication & Society, 23(5), 665–680. https://doi.org/10.1080/1369118X.2020.1716043
   Web of Science ®Google Scholar
• Dougherty, D., & Dunne, D. D. (2012). Digital science and knowledge boundaries in complex innovation. Organization Science, 23(5), 1467–1484. Business Source Complete. https://doi.org/10.1287/orsc.1110.0700
   Web of Science ®Google Scholar
• Duan, Z., Li, J., Lukito, J., Yang, K.-C., Chen, F., Shah, D. V., & Yang, S. (2022). Algorithmic agents in the hybrid media system: Social bots, selective amplification, and partisan news about COVID-19. Human Communication Research, 48(3), 516–542. https://doi.org/10.1093/hcr/hqac012
   Web of Science ®Google Scholar
• Edwards, A., Edwards, C., & Gambino, A. (2020). The social pragmatics of communication with social robots: Effects of robot message design logic in a regulative context. International Journal of Social Robotics, 12(4), 945–957. https://doi.org/10.1007/s12369-019-00538-7
   Web of Science ®Google Scholar
• Edwards, C., Edwards, A., Spence, P. R., & Westerman, D. (2016). Initial interaction expectations with robots: Testing the human-to-human interaction script. Communication Studies, 67(2), 227–238. https://doi.org/10.1080/10510974.2015.1121899
   Web of Science ®Google Scholar
• Endacott, C. G. (2021, November 18–21). How AI technologies enable and constrain the enactment of multiple identities. Annual meetings of the National Communication Association, Seattle, WA.
   Google Scholar
• Endacott, C. G., & Leonardi, P. M. (2022). Artificial intelligence and impression management: Consequences of autonomous conversational agents communicating on one’s behalf. Human Communication Research, 48(3), 462–490. https://doi.org/10.1093/hcr/hqac009
   Web of Science ®Google Scholar
• Eubanks, V. (2017). Automating inequality: How high-tech tools profile, police, and punish the poor. St. Martin’s Press.
   Google Scholar
• Faunce, W. (1965). Automation and the division of labor. Social Problems, 13(2), 149–160. https://doi.org/10.2307/798900
   Web of Science ®Google Scholar
• Fleming, P. (2018). Robots and organization studies: Why robots might not want to steal your job. Organization Studies, 40(1), 23–38. https://doi.org/10.1177/0170840618765568
   Web of Science ®Google Scholar
• Flyverbom, M. (2019). The digital prism: Transparency and managed visibilities in a datafied world. Cambridge University Press.
   Google Scholar
• Flyverbom, M., & Murray, J. (2018). Datastructuring—organizing and curating digital traces into action. Big Data & Society, 5(2), 1–12. https://doi.org/10.1177/2053951718799114
   Web of Science ®Google Scholar
• Fortunati, L. (2018). Robotization and the domestic sphere. New Media & Society, 20(8), 2673–2690. https://doi.org/10.1177/1461444817729366
   Web of Science ®Google Scholar
• Furman, J. L., & Teodoridis, F. (2020). Automation, research technology, and researchers’ trajectories: Evidence from computer science and electrical engineering. Organization Science, 31(2), 330–354. https://doi.org/10.1287/orsc.2019.1308
   Web of Science ®Google Scholar
• Gambino, A., & Liu, B. (2022). Considering the context to build theory in HCI, HRI, and HMC: Explicating differences in processes of communication and socialization with social technologies. Human-Machine Communication, 4, 111–130. https://doi.org/10.30658/hmc.4.6
   Google Scholar
• Garson, B. (1988). The electronic sweatshop: How computers are transforming the office of the future into the factory of the past. Penguin Books.
   Google Scholar
• Geiger, R. S. (2016). Bot-based collective blocklists in Twitter: The counterpublic moderation of harassment in a networked public space. Information, Communication & Society, 19(6), 787–803. https://doi.org/10.1080/1369118X.2016.1153700
   Web of Science ®Google Scholar
• Gibbs, J. L., Kirkwood, G. L., Fang, C., & Wilkenfeld, J. N. (2021). Negotiating agency and control: Theorizing human-machine communication from a structurational perspective. Human-Machine Communication, 2, 153–171. https://doi.org/10.30658/hmc.2.8
   Google Scholar
• Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627–660. https://doi.org/10.5465/annals.2018.0057
   Web of Science ®Google Scholar
• Graham, S. S. (2022). The doctor and the algorithm: Promise, peril, and the future of health AI. Oxford University Press.
   Google Scholar
• Groleau, C., Demers, C., Lalancette, M., & Barros, M. (2012). From hand drawings to computer visuals: Confronting situated and institutionalized practices in an architecture firm. Organization Science, 23(3), 651–671. https://doi.org/10.1287/orsc.1110.0667
   Web of Science ®Google Scholar
• Gupta, A., Ip, I. K., Raja, A. S., Andruchow, J. E., Sodickson, A., & Khorasani, R. (2014). Effect of clinical decision support on documented guideline adherence for head CT in emergency department patients with mild traumatic brain injury. Journal of the American Medical Informatics Association, 21(e2), e347–e351. https://doi.org/10.1136/amiajnl-2013-002536
   PubMed Web of Science ®Google Scholar
• Guzman, A. L., & Lewis, S. C. (2020). Artificial intelligence and communication: A Human–Machine Communication research agenda. New Media & Society, 22(1), 70–86. https://doi.org/10.1177/1461444819858691
   Web of Science ®Google Scholar
• Hancock, J. T., Naaman, M., & Levy, K. (2020). AI-mediated communication: Definition, research agenda, and ethical considerations. Journal of Computer-Mediated Communication, 25(1), 89–100. https://doi.org/10.1093/jcmc/zmz022
   Web of Science ®Google Scholar
• Hanusch, F. (2017). Web analytics and the functional differentiation of journalism cultures: Individual, organizational and platform-specific influences on newswork. Information, Communication & Society, 20(10), 1571–1586. https://doi.org/10.1080/1369118X.2016.1241294
   Web of Science ®Google Scholar
• Hasan, S., Ferguson, J.-P., & Koning, R. (2015). The lives and deaths of jobs: Technical interdependence and survival in a job structure. Organization Science, 26(6), 1665–1681. https://doi.org/10.1287/orsc.2015.1014
   Web of Science ®Google Scholar
• Hemon-Hildgen, A., Rowe, F., & Monnier-Senicourt, L. (2020). Orchestrating automation and sharing in DevOps teams: A revelatory case of job satisfaction factors, risk and work conditions. European Journal of Information Systems, 29(5), 474–499. https://doi.org/10.1080/0960085X.2020.1782276
   Web of Science ®Google Scholar
• Henderson, K. (1998). The role of material objects in the design process: A comparison of two design cultures and how they contend with automation. Science, Technology, & Human Values, 23(2), 139–174. https://doi.org/10.1177/016224399802300201
   Web of Science ®Google Scholar
• Henriksen, A., & Bechmann, A. (2020). Building truths in AI: Making predictive algorithms doable in healthcare. Information, Communication & Society, 23(6), 802–816. https://doi.org/10.1080/1369118X.2020.1751866
   Web of Science ®Google Scholar
• Hensmans, M. (2020). How digital fantasy work induces organizational ideal reversal? Long-term conditioning and enactment of digital transformation fantasies at a large alternative bank (1963–2019). Organization, 28(1), 132–163. https://doi.org/10.1177/1350508420968185
   Web of Science ®Google Scholar
• Herkert, J., Borenstein, J., & Miller, K. (2020). The Boeing 737 MAX: Lessons for engineering ethics. Science and Engineering Ethics, 26(6), 2957–2974. https://doi.org/10.1007/s11948-020-00252-y
   PubMed Web of Science ®Google Scholar
• Hilbert, M., & Darmon, D. (2020). Large-scale communication is more complex and unpredictable with automated bots. Journal of Communication, 70(5), 670–692. https://doi.org/10.1093/joc/jqaa021
   Web of Science ®Google Scholar
• Horstmann, A. C., & Krämer, N. C. (2019). Great expectations? Relation of previous experiences with social robots in real life or in the media and expectancies based on qualitative and quantitative assessment. Frontiers in Psychology, 10, 939. https://doi.org/10.3389/fpsyg.2019.00939.
   PubMed Web of Science ®Google Scholar
• Hsieh, S.-J. (2016, June 26). Skill sets needed for industrial automation careers. ASEE annual Conference, New Orleans, LA.
   Google Scholar
• Jackson, S., & Aakhus, M. (2014). Becoming more reflective about the role of design in communication. Journal of Applied Communication Research, 42(2), 125–134. https://doi.org/10.1080/00909882.2014.882009
   Web of Science ®Google Scholar
• Jensen, J. T., Rolison, S. L., & Barbour, J. B. (2022). Temporal dominance: Controlling activity cycles when time is scarce, sudden, and squeezed. Management Communication Quarterly, 36(1), 30–61. https://doi.org/10.1177/08933189211023471
   Web of Science ®Google Scholar
• Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267–2270. https://doi.org/10.1002/asi.23867
   Web of Science ®Google Scholar
• Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
   Web of Science ®Google Scholar
• Kelly, C. R. (2021). White pain. Quarterly Journal of Speech, 107(2), 209–233. https://doi.org/10.1080/00335630.2021.1903537
   Web of Science ®Google Scholar
• Klatzky, S. R. (1970). Automation, size, and the locus of decision making: The cascade effect. The Journal of Business, 43(2), 141–151. https://doi.org/10.1086/295261
   Google Scholar
• Krumholz, H. M. (2014). Big data and new knowledge in medicine: The thinking, training, and tools needed for a learning health system. Health Affairs, 33(7), 1163–1170. https://doi.org/10.1377/hlthaff.2014.0053
   PubMed Web of Science ®Google Scholar
• Kushner, S. (2013). The freelance translation machine: Algorithmic culture and the invisible industry. New Media & Society, 15(8), 1241–1258. https://doi.org/10.1177/1461444812469597
   Web of Science ®Google Scholar
• Laapotti, T., & Raappana, M. (2022). Algorithms and organizing. Human Communication Research, 48(3), 491–515. https://doi.org/10.1093/hcr/hqac013
   Web of Science ®Google Scholar
• Laitinen, K., Laaksonen, S.-M., & Koivula, M. (2021). Slacking with the bot: Programmable social bot in virtual team interaction. Journal of Computer-Mediated Communication, 26(6), 343–361. https://doi.org/10.1093/jcmc/zmab012
   Web of Science ®Google Scholar
• Lammi, I. J. (2020). Automating to control: The unexpected consequences of modern automated work delivery in practice. Organization, 28(1), 115–131. https://doi.org/10.1177/1350508420968179
   Web of Science ®Google Scholar
• Lange, A.-C., Lenglet, M., & Seyfert, R. (2018). On studying algorithms ethnographically: Making sense of objects of ignorance. Organization, 26(4), 598–617. https://doi.org/10.1177/1350508418808230
   Web of Science ®Google Scholar
• Lazer, D. M. J., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721–723. https://doi.org/10.1126/science.1167742
   PubMed Web of Science ®Google Scholar
• Lazer, D. M. J., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., Freelon, D., Gonzalez-Bailon, S., King, G., Margetts, H., Nelson, A., Salganik, M. J., Strohmaier, M., Vespignani, A., & Wagner, C. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060–1062. https://doi.org/10.1126/science.aaz8170
   PubMed Web of Science ®Google Scholar
• Lee, J., & Berente, N. (2012). Digital innovation and the division of innovative labor: Digital controls in the automotive industry. Organization Science, 23(5), 1428–1447. https://doi.org/10.1287/orsc.1110.0707
   Web of Science ®Google Scholar
• Lee, M. K., Kusbit, D., Metsky, E., & Dabbish, L. (2015). Working with machines: The impact of algorithmic and data-driven management on human workers. In: Bo Begole, Jinwoo Kim, Kori Inkpen, & Woontack Woo (Eds.), Proceedings of the 33rd annual ACM conference on human factors in computing systems (pp. 1603–1612). https://dl.acm.org/doi/proceedings/10 .1145/2702123
   Google Scholar
• Lee, S., Nah, S., Chung, D. S., & Kim, J. (2020). Predicting AI news credibility: Communicative or social capital or both? Communication Studies, 71(3), 428–447. https://doi.org/10.1080/10510974.2020.1779769
   Web of Science ®Google Scholar
• Leonardi, P. M. (2009a). Crossing the implementation line: The mutual constitution of technology and organizing across development and use activities. Communication Theory, 19(3), 278–310. https://doi.org/10.1111/j.1468-2885.2009.01344.x
   Web of Science ®Google Scholar
• Leonardi, P. M. (2009b). Why do people reject new technologies and organizational changes of which they are in favor? Exploring misalignments between social interactions and materiality. Human Communication Research, 35(3), 407–441. https://doi.org/10.1111/j.1468-2958.2009.01357.x
   Web of Science ®Google Scholar
• Leonardi, P. M. (2011). Innovation blindness: Culture, frames, and cross-boundary problem construction in the development of new technology concepts. Organization Science, 22(2), 347–369. https://doi.org/10.1287/orsc.1100.0529
   Web of Science ®Google Scholar
• Leonardi, P. M. (2012). Car crashes without cars: Lessons about simulation technology and organizational change from automotive design. MIT Press.
   Google Scholar
• Leonardi, P. M. (2013). When does technology use enable network change in organizations? A comparative study of feature use and shared affordances. MIS Quarterly, 37(3), 749–775. https://doi.org/10.25300/MISQ/2013/37.3.04
   Web of Science ®Google Scholar
• Leonardi, P. M., & Contractor, N. (2018). Better people analytics: Measure who they know not just who they are. Harvard Business Review, 96(6), 70–81. https://hbr.org/2018/11/better-people-analytics
   Web of Science ®Google Scholar
• Leonardi, P. M., & Treem, J. W. (2020). Behavioral visibility: A new paradigm for organization studies in the age of digitization, digitalization, and datafication. Organization Studies, 41(12), 1601–1625. https://doi.org/10.1177/0170840620970728
   Web of Science ®Google Scholar
• Leonardi, P. M., Woo, D., & Barley, W. C. (2021). On the making of crystal balls: Five lessons about simulation modeling and the organization of work. Information and Organization, 31(1), 100339. https://doi.org/10.1016/j.infoandorg.2021.100339
   Web of Science ®Google Scholar
• Lepore, J. (2019, March 4). The robot caravan. The New Yorker. https://www.newyorker.com/magazine/2019/03/04/are-robots-competing-for-your-job
   Google Scholar
• Lewis, L. K. (2019). Organizational change: Creating change through strategic communication (2nd ed.). Wiley-Blackwell.
   Google Scholar
• Lewis, L. K., & Russ, T. L. (2011). Soliciting and using input during organizational change initiatives: What are practitioners doing? Management Communication Quarterly, 26(2), 267–294. https://doi.org/10.1177/0893318911431804
   Web of Science ®Google Scholar
• Liang, Y., & Lee, S. A. (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
   Web of Science ®Google Scholar
• Liberatore, M. J., & Luo, W. (2010). The analytics movement: Implications for operations research. Interfaces, 40(4), 313–324. https://doi.org/10.1287/inte.1100.0502
   Web of Science ®Google Scholar
• Lin, W., Yueh, H.-P., Wu, H.-Y., & Fu, L.-C. (2014). Developing a service robot for a children’s library: A design-based research approach. Journal of the Association for Information Science and Technology, 65(2), 290–301. https://doi.org/10.1002/asi.22975
   Web of Science ®Google Scholar
• Liu, B. (2021). In AI we trust? Effects of agency locus and transparency on uncertainty reduction in human–AI interaction. Journal of Computer-Mediated Communication, 26(6), 384–402. https://doi.org/10.1093/jcmc/zmab013
   Web of Science ®Google Scholar
• Lobera, J., Fernández Rodríguez, C. J., & Torres-Albero, C. (2020). Privacy, values and machines: Predicting opposition to artificial intelligence. Communication Studies, 71(3), 448–465. https://doi.org/10.1080/10510974.2020.1736114
   Web of Science ®Google Scholar
• Lucas, G. M., Gratch, J., King, A., & Morency, L.-P. (2014). It’s only a computer: Virtual humans increase willingness to disclose. Computers in Human Behavior, 37, 94–100. https://doi.org/10.1016/j.chb.2014.04.043
   Web of Science ®Google Scholar
• Lucas, G. M., Rizzo, A., Gratch, J., Scherer, S., Stratou, G., Boberg, J., & Morency, L.-P. (2017). Reporting mental health symptoms: Breaking down barriers to care with virtual human interviewers. Frontiers in Robotics and AI, 4, 51. https://doi.org/10.3389/frobt.2017.00051
   Web of Science ®Google Scholar
• Lupton, D. (2016). The quantified self. Polity Press.
   Google Scholar
• Lycett, M. (2013). ‘Datafication’: Making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381–386. https://doi.org/10.1057/ejis.2013.10
   Web of Science ®Google Scholar
• Maiers, C. (2017). Analytics in action: Users and predictive data in the neonatal intensive care unit. Information, Communication & Society, 20(6), 915–929. https://doi.org/10.1080/1369118X.2017.1291701
   Web of Science ®Google Scholar
• Marchland, D. A., & Peppard, J. (2013). Why IT fumbles analytics: Tech projects should focus less on technology and more on information. Harvard Business Review, 91, 104–112. https://hbr.org/2013/01/why-it-fumbles-analytics
   Google Scholar
• McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90, 60–68. https://hbr.org/2012/09/big-datas-management-revolutio
   PubMed Web of Science ®Google Scholar
• McGuigan, L. (2019). Automating the audience commodity: The unacknowledged ancestry of programmatic advertising. New Media & Society, 21(11–12), 2366–2385. https://doi.org/10.1177/1461444819846449
   Web of Science ®Google Scholar
• Meng, J., & Dai, Y. (N.). (2021). Emotional support from AI chatbots: Should a supportive partner self-disclose or not? Journal of Computer-Mediated Communication, 26(4), 207–222. https://doi.org/10.1093/jcmc/zmab005
   Web of Science ®Google Scholar
• Meyer, M. W. (1968). Automation and bureaucratic structure. American Journal of Sociology, 74(3), 256–264. https://doi.org/10.1086/224639
   Web of Science ®Google Scholar
• Miller, C. R. (2007). What can automation tell us about agency? Rhetoric Society Quarterly, 37(2), 137–157. https://doi.org/10.1080/02773940601021197
   Google Scholar
• Morath, E. (2020, February 23). AI is the next workplace disrupter—and it’s coming for high-skilled jobs. Wall Street Journal. https://www.wsj.com/articles/ai-is-the-next-workplace-disrupterand-its-coming-for-high-skilled-jobs-11582470000
   Google Scholar
• Muller, J. Z. (2018). The tyranny of metrics. Princeton University Press.
   Google Scholar
• Murdock, G. (2018). Media materialties: For a moral economy of machines. Journal of Communication, 68(2), 359–368. https://doi.org/10.1093/joc/jqx023
   Web of Science ®Google Scholar
• Nafus, D., & Sherman, J. (2014). This one does not go up to 11: The Quantified Self movement as an alternative big data practice. International Journal of Communication, 8, 1784–1794. https://ijoc.org/index.php/ijoc/article/view/2170/1157
   Web of Science ®Google Scholar
• Neff, G., & Nafus, D. (2016). Self-tracking. MIT Press.
   Google Scholar
• Nelson, H. G., & Stolterman, E. (2012). The design way: Intentional change in an unpredictable world (2nd ed.). MIT Press.
   Google Scholar
• Newlands, G. (2020). Algorithmic surveillance in the gig economy: The organization of work through Lefebvrian conceived space. Organization Studies, 42(5), 719–737. https://doi.org/10.1177/0170840620937900
   Web of Science ®Google Scholar
• Noble, D. F. (2011). Forces of production: A social history of industrial automation. Taylor & Francis.
   Google Scholar
• Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447–453. https://doi.org/10.1126/science.aax2342
   PubMed Web of Science ®Google Scholar
• Ohl, J. J. (2015). Nothing to see or fear: Light war and the boring visual rhetoric of U.S. drone imagery. Quarterly Journal of Speech, 101(4), 612–632. https://doi.org/10.1080/00335630.2015.1128115
   Web of Science ®Google Scholar
• Oliver, N., Calvard, T., & Potočnik, K. (2017). Cognition, technology, and organizational limits: Lessons from the Air France 447 disaster. Organization Science, 28(4), 729–743. https://doi.org/10.1287/orsc.2017.1138
   Web of Science ®Google Scholar
• O’Neill, C. (2016). Weapons of math destruction. Crown Books.
   Google Scholar
• Orlikowski, W. J. (1992). The duality of technology: Rethinking the concept of technology in organizations. Organization Science, 3(3), 398–427. https://doi.org/10.1287/orsc.3.3.398
   Web of Science ®Google Scholar
• Pääkkönen, J., Laaksonen, S.-M., & Jauho, M. (2020). Credibility by automation: Expectations of future knowledge production in social media analytics. Convergence: The International Journal of Research Into New Media Technologies, 26(4), 790–807. https://doi.org/10.1177/1354856520901839
   Web of Science ®Google Scholar
• Pachidi, S., Berends, H., Faraj, S., & Huysman, M. (2020). Make way for the algorithms: Symbolic actions and change in a regime of knowing. Organization Science, 32(1), 18–41. https://doi.org/10.1287/orsc.2020.1377
   Web of Science ®Google Scholar
• Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, 30(3), 286–297. https://doi.org/10.1109/3468.844354
   PubMed Web of Science ®Google Scholar
• Park, S., & Humphry, J. (2019). Exclusion by design: Intersections of social, digital and data exclusion. Information, Communication & Society, 22(7), 934–953. https://doi.org/10.1080/1369118X.2019.1606266
   Web of Science ®Google Scholar
• Peña Gangadharan, S., & Niklas, J. (2019). Decentering technology in discourse on discrimination. Information, Communication & Society, 22(7), 882–899. https://doi.org/10.1080/1369118X.2019.1593484
   Web of Science ®Google Scholar
• Pentland, B. T., Haerem, T., & Hillison, D. (2011). The (n)ever-changing world: Stability and change in organizational routines. Organization Science, 22(6), 1369–1383. https://doi.org/10.1287/orsc.1110.0624
   Web of Science ®Google Scholar
• Pentland, B. T., Hærem, T., & Hillison, D. (2010). Comparing organizational routines as recurrent patterns of action. Organization Studies, 31(7), 917–940. https://doi.org/10.1177/0170840610373200
   Web of Science ®Google Scholar
• Pew Research Center. (2017). Automation in everyday life. https://www.pewresearch.org/internet/2017/10/04/automation-in-everyday-life/.
   Google Scholar
• Pezzullo, P. C., & Hunt, K. P. (2020). Agribusiness futurism and food atmospheres: Reimagining corn, pigs, and transnational negotiations on Khrushchev’s 1959 U.S. tour. Quarterly Journal of Speech, 106(4), 399–426. https://doi.org/10.1080/00335630.2020.1828605
   Web of Science ®Google Scholar
• Piercy, C. W., & Gist-Mackey, A. N. (2021). Automation anxieties: Perceptions about technological automation and the future of pharmacy work. Human-Machine Communication, 2, 191–208. https://doi.org/10.30658/hmc.2.10
   Google Scholar
• Poole, M. S., & Holmes, M. E. (1995). Decision development in computer-assisted group decision making. Human Communication Research, 22(1), 90–127. https://doi.org/10.1111/j.1468-2958.1995.tb00363.x
   Web of Science ®Google Scholar
• Popejoy, A. B., & Fullerton, S. M. (2016). Genomics is failing on diversity. Nature, 538(7624), 161–164. https://doi.org/10.1038/538161a
   PubMed Web of Science ®Google Scholar
• Rahman, H. A. (2021). The invisible cage: Workers’ reactivity to opaque algorithmic evaluations. Administrative Science Quarterly, 66(4), 945–988. https://doi.org/10.1177/00018392211010118
   Web of Science ®Google Scholar
• Ratcliff, C. L., Kaphingst, K. A., & Jensen, J. D. (2018). When personal feels invasive: Foreseeing challenges in precision medicine communication. Journal of Health Communication, 23(2), 144–152. https://doi.org/10.1080/10810730.2017.1417514
   PubMed Web of Science ®Google Scholar
• Rawley, E., & Simcoe, T. S. (2013). Information technology, productivity, and asset ownership: Evidence from taxicab fleets. Organization Science, 24(3), 831–845. https://doi.org/10.1287/orsc.1120.0758
   Web of Science ®Google Scholar
• Reeves, B., & Nass, C. (1996). The media equation: How people treat computers, television, and new media like real people and places. Cambridge University Press.
   Google Scholar
• Ringel, S., & Davidson, R. (2020). Proactive ephemerality: How journalists use automated and manual tweet deletion to minimize risk and its consequences for social media as a public archive. New Media & Society, 24(5), 1216–1233. https://doi.org/10.1177/1461444820972389
   Web of Science ®Google Scholar
• Ringel, S., & Ribak, R. (2021). ‘Place a book and walk away’: Archival digitization as a socio-technical practice. Information, Communication & Society, 24(15), 2293–2306. https://doi.org/10.1080/1369118X.2020.1766534
   Web of Science ®Google Scholar
• Rydenfelt, H. (2021). Transforming media agency? Approaches to automation in Finnish legacy media. New Media & Society, 24(12), 2598–2613. https://doi.org/10.1177/1461444821998705
   Web of Science ®Google Scholar
• Sandberg, J., Holmström, J., & Lyytinen, K. (2020). Digitization and phase transitions in platform organizing logics: Evidence from the process automation industry. MIS Quarterly, 44(1), 129–153. https://doi.org/10.25300/MISQ/2020/14520
   Web of Science ®Google Scholar
• Santini, R. M., Salles, D., Tucci, G., Ferreira, F., & Grael, F. (2020). Making up audience: Media bots and the falsification of the public sphere. Communication Studies, 71(3), 466–487. https://doi.org/10.1080/10510974.2020.1735466
   Web of Science ®Google Scholar
• Sardar, M. R., Badri, M., Prince, C. T., Seltzer, J., & Kowey, P. R. (2014). Underrepresentation of women, elderly patients, and racial minorities in the randomized trials used for cardiovascular guidelines. JAMA Internal Medicine, 174(11), 1868–1870. https://doi.org/10.1001/jamainternmed.2014.4758
   PubMed Web of Science ®Google Scholar
• Scherr, C. L., Dean, M., Clayton, M. F., Hesse, B. W., Silk, K., Street, R. L. J., & Krieger, J. (2017). A research agenda for communication scholars in the precision medicine era. Journal of Health Communication, 22(10), 839–848. https://doi.org/10.1080/10810730.2017.1363324
   PubMed Web of Science ®Google Scholar
• Schmitt, J. B., Rieger, D., Rutkowski, O., & Ernst, J. (2018). Counter-messages as prevention or promotion of extremism?! The potential role of YouTube recommendation algorithms. Journal of Communication, 68(4), 780–808. https://doi.org/10.1093/joc/jqy029
   Web of Science ®Google Scholar
• Seeber, I., Bittner, E., Briggs, R. O., de Vreede, T., de Vreede, G.-J., Elkins, A., Maier, R., Merz, A. B., Oeste-Reiß, S., Randrup, N., Schwabe, G., & Söllner, M. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information & Management, 57(2), 103174. https://doi.org/10.1016/j.im.2019.103174
   Web of Science ®Google Scholar
• Seering, J., Flores, J. P., Savage, S., & Hammer, J. (2018). The social roles of bots: Evaluating impact of bots on discussions in online communities. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW), 1–29. https://doi.org/10.1145/3274426
   Google Scholar
• Sennett, R. (2009). The craftsman. Yale University Press.
   Google Scholar
• Shestakofsky, B. (2017). Working algorithms: Software automation and the future of work. Work and Occupations, 44(4), 376–423. https://doi.org/10.1177/0730888417726119
   Web of Science ®Google Scholar
• Sholler, D., Bailey, D. E., & Rennecker, J. (2016). Big data in medicine: Potential, reality, and implications. In C. R. Sugimoto, H. R. Ekbia, & M. Mattioli (Eds.), Big data is not a monolith (pp. 173–185). The MIT Press.
   Google Scholar
• Shorey, S., & Howard, P. N. (2016). Automation, algorithms, and politics: A research review. International Journal of Communication, 10, 5032–5055. https://ijoc.org/index.php/ijoc/article/view/6233/1812
   Web of Science ®Google Scholar
• Soffer, O. (2021). Algorithmic personalization and the two-step flow of communication. Communication Theory, 31(3), 297–315. https://doi.org/10.1093/ct/qtz008
   Web of Science ®Google Scholar
• Sproull, L., & Kiesler, S. (1991). Two-level perspective on electronic mail in organizations. Journal of Organizational Computing, 1(2), 125–134. https://doi.org/10.1080/10919399109540154
   Google Scholar
• Sundar, S. S. (2020). Rise of machine agency: A framework for studying the psychology of human–AI interaction (HAII). Journal of Computer-Mediated Communication, 25(1), 74–88. https://doi.org/10.1093/jcmc/zmz026
   Web of Science ®Google Scholar
• Sundar, S. S., & Lee, E.-J. (2022). Rethinking communication in the era of artificial intelligence. Human Communication Research, 48(3), 379–385. https://doi.org/10.1093/hcr/hqac014
   Web of Science ®Google Scholar
• Taipale, S., de Luca, F., Sarrica, M., & Fortunati, L. (2015). Robot shift from industrial production to social reproduction. In J. Vincent, S. Taipale, B. Sapio, G. Lugano & L. Fortunati (Eds.), (pp. 11–24). Springer International Publishing. https://doi.org/10.1007/978-3-319-15672-9_2
   Google Scholar
• Topol, E. J. (2019a). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.
   Google Scholar
• Topol, E. J. (2019b). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7
   PubMed Web of Science ®Google Scholar
• Treem, J. W., & Leonardi, P. M. (2016). Expertise, communication, and organizing. Oxford University Press.
   Google Scholar
• Treem, J. W., Leonardi, P. M., & van den Hooff, B. (2020). Computer-mediated communication in the age of communication visibility. Journal of Computer-Mediated Communication, 25(1), 44–59. https://doi.org/10.1093/jcmc/zmz024
   Web of Science ®Google Scholar
• van Dijck, J. (2014). Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208. https://doi.org/10.24908/ss.v12i2.4776
   Google Scholar
• Velkova, J., & Kaun, A. (2021). Algorithmic resistance: Media practices and the politics of repair. Information, Communication & Society, 24(4), 523–540. https://doi.org/10.1080/1369118X.2019.1657162
   Web of Science ®Google Scholar
• Vergeer, M. (2020). Artificial intelligence in the Dutch press: An analysis of topics and trends. Communication Studies, 71(3), 373–392. https://doi.org/10.1080/10510974.2020.1733038
   Web of Science ®Google Scholar
• Wajcman, J. (2019). The digital architecture of time management. Science, Technology, & Human Values, 44(2), 315–337. https://doi.org/10.1177/0162243918795041
   Web of Science ®Google Scholar
• Weber, M. S., Barley, W. C., & Kahn, E. (2021, May). Artificial intelligence and the power of the past to predict the future of work. International Communication Association.
   Google Scholar
• Westerman, D., Edwards, A. P., Edwards, C., Luo, Z., & Spence, P. R. (2020). I-it, I-thou, I-robot: The perceived humanness of AI in human-machine communication. Communication Studies, 71(3), 393–408. https://doi.org/10.1080/10510974.2020.1749683
   Web of Science ®Google Scholar
• Witteborn, S. (2022). Digitalization, digitization and datafication: The “three D” transformation of forced migration management. Communication, Culture and Critique, 15(2), 157–175. https://doi.org/10.1093/ccc/tcac007
   Web of Science ®Google Scholar
• Wojcieszak, M., Thakur, A., Ferreira Gonçalves, J. F., Casas, A., Menchen-Trevino, E., & Boon, M. (2021). Can AI enhance people’s support for online moderation and their openness to dissimilar political views? Journal of Computer-Mediated Communication, 26(4), 223–243. https://doi.org/10.1093/jcmc/zmab006
   Web of Science ®Google Scholar
• Wolf, Z. (2019, September 3). The robots are coming for your job, too. CNN. https://www.cnn.com/2019/08/24/politics/economy-us-workforce-automation/index.html
   Google Scholar
• Woolley, S., Shorey, S., & Howard, P. N. (2018). The bot proxy: Designing automated self-expression. In Z. Papacharissi (Ed.), A networked self and platforms, stories, connections (pp. 59–76). Routledge.
   Google Scholar
• Wright, B. D. (2016, March 28). Robots are coming for your job. Los Angeles Times. https://www.latimes.com/opinion/op-ed/la-oe-wright-robots-jobs-data-mining-20160328-story.html
   Google Scholar
• Yu, J., & Couldry, N. (2022). Education as a domain of natural data extraction: Analysing corporate discourse about educational tracking. Information, Communication & Society, 25(1), 127–144. https://doi.org/10.1080/1369118X.2020.1764604
   Web of Science ®Google Scholar
• Zuboff, S. (1985). Automatefin-fonnate: The two faces of intelligent technology. Organizational Dynamics, 14(2), 5–18. https://doi.org/10.1016/0090-2616(85)90033-6
   Web of Science ®Google Scholar
• Zuboff, S. (1988). In the age of the smart machine: The future of work and power. Basic Books.
   Google Scholar
• Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. Hachette Book Group.
   Google Scholar