Hybrid collective intelligence in a human–AI society

Peeters, Marieke M. M.; van Diggelen, Jurriaan; van den Bosch, Karel; Bronkhorst, Adelbert; Neerincx, Mark A.; Schraagen, Jan Maarten; Raaijmakers, Stephan

doi:10.1007/s00146-020-01005-y

Open Forum
Published: 25 June 2020

Hybrid collective intelligence in a human–AI society

Marieke M. M. Peeters^1,4,
Jurriaan van Diggelen¹,
Karel van den Bosch¹,
Adelbert Bronkhorst¹,
Mark A. Neerincx^1,2,
Jan Maarten Schraagen^1,3 &
Stephan Raaijmakers^1,5

AI & SOCIETY volume 36, pages 217–238 (2021)Cite this article

3657 Accesses
20 Citations
5 Altmetric
Metrics details

Abstract

Within current debates about the future impact of Artificial Intelligence (AI) on human society, roughly three different perspectives can be recognised: (1) the technology-centric perspective, claiming that AI will soon outperform humankind in all areas, and that the primary threat for humankind is superintelligence; (2) the human-centric perspective, claiming that humans will always remain superior to AI when it comes to social and societal aspects, and that the main threat of AI is that humankind’s social nature is overlooked in technological designs; and (3) the collective intelligence-centric perspective, claiming that true intelligence lies in the collective of intelligent agents, both human and artificial, and that the main threat for humankind is that technological designs create problems at the collective, systemic level that are hard to oversee and control. The current paper offers the following contributions: (a) a clear description for each of the three perspectives, along with their history and background; (b) an analysis and interpretation of current applications of AI in human society according to each of the three perspectives, thereby disentangling miscommunication in the debate concerning threats of AI; and (c) a new integrated and comprehensive research design framework that addresses all aspects of the above three perspectives, and includes principles that support developers to reflect and anticipate upon potential effects of AI in society.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Notes

References

Adamson G, Havens JC, Chatila R (2019) Designing a value-driven future for ethical autonomous and intelligent systems. Proc IEEE 107(3):518–525
Article Google Scholar
Ali AR (2019) Deep learning in oncology—applications in fighting cancer. EMERJ. https://emerj.com/ai-sector-overviews/deep-learning-in-oncology/. Accessed 26 Feb 2019
Ashby WR (1961) An introduction to cybernetics. Chapman & Hall Ltd
MATH Google Scholar
Awad E, Dsouza S, Bonnefon JF, Shariff A, Rahwan I (2020) Crowdsourcing moral machines. Commun ACM 63(3):48–55
Article Google Scholar
Bailey I, Wilson GA (2009) Theorising transitional pathways in response to climate change: technocentrism, ecocentrism, and the carbon economy. Environ Plan 41(10):2324–2341
Article Google Scholar
Balistreri H (2018) Credit as a social technology: black mirror, China, and the case for social credit. Medium. https://medium.com/@harrison.tb/credit-as-a-social-technology-black-mirror-china-and-the-case-for-social-credit-d6a6db609ea5. Accessed 17 Jun 2020
Basem W (2018) Audi A8 L review|brilliant engineering in an unassuming wrapper. https://www.autoblog.com/2018/10/16/2019-audi-a8-l-review-first-drive/. Accessed 3 Apr 2019
Baum SD (2017) On the promotion of safe and socially beneficial artificial intelligence. AI & Soc 32(4):543–551
Article Google Scholar
Bostrom N (2016) Superintelligence. Oxford University Press, Oxford
Google Scholar
Bostrom N, Yudkowsky E (2014) The ethics of artificial intelligence. Camb Handb Artif Intell 316:334
Google Scholar
Botsman R (2017) Big data meets Big Brother as China moves to rate its citizens. https://www.wired.co.uk/article/chinese-government-social-credit-score-privacy-invasion. Accessed 17 Jun 2020
Bresnick J (2017) Deep learning network 100% accurate at identifying breast cancer. https://healthitanalytics.com/news/deep-learning-network-100-accurate-at-identifying-breast-cancer. Accessed 28 Mar 2019
Brown N, Sandholm T (2018) Superhuman AI for heads-up no-limit poker: libratus beats top professionals. Science 359(6374):418–424. https://doi.org/10.1126/science.aao1733
MathSciNet MATH Article Google Scholar
Brynjolfsson E, McAfee A (2014) The second machine age: work, progress, and prosperity in a time of brilliant technologies. WW Norton & Company, New York
Google Scholar
Brynjolfsson E, Mitchell T (2017) What can machine learning do? Workforce implications. Science 358(6370):1530–1534
Article Google Scholar
Bughin J, Hazan E, Ramaswamy S, Chui M, Allas T, Dahlström P, Henke N, Trench M (2017) Artificial Intelligence: the next digital frontier?. McKinsey Global Institute, New York
Google Scholar
Campbell M, Hoane AJ Jr, Hsu FH (2002) Deep blue. Artif Intell 134(1–2):57–83
MATH Article Google Scholar
Carse J (2011) Finite and infinite games. Simon and Schuster, New York
Google Scholar
Case N (2018) How to become a centaur. Journal of Design and Science
Cavoukian A (2013) Privacy by design: leadership, methods, and results. In: European Data Protection: Coming of Age (pp. 175-202). Springer, Dordrecht
Chapter Google Scholar
Chen Y, Elenee Argentinis J, Weber G (2016) IBM Watson: how cognitive computing can be applied to big data challenges in life sciences research. Clin Ther 38(4):688–701. https://doi.org/10.1016/j.clinthera.2015.12.001
Article Google Scholar
Clark C, Chalmers D (1998) The extended mind. Analysis 58(1):7–19
Article Google Scholar
Constine J (2016) How Facebook news feed works. http://social.techcrunch.com/2016/09/06/ultimate-guide-to-the-news-feed/. Accessed 28 Mar 2019
Crosman P (2017) Beyond robo-advisers: how AI could rewire wealth management. https://www.americanbanker.com/news/beyond-robo-advisers-how-ai-could-rewire-wealth-management. Accessed 28 Feb 2019
Dar P (2018) Major AI and ML breakthroughs in 2018 and trends to look out for in 2019. https://www.analyticsvidhya.com/blog/2018/12/key-breakthroughs-ai-ml-2018-trends-2019/. Accessed 27 Mar 2019
Dastin J (2018) Amazon scraps secret AI recruiting tool that showed bias against women. Reuters Business News. https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G. Accessed 6 Jan 2020
Davids A (2002) Urban search and rescue robots: from tragedy to technology. IEEE Intell Syst 17(2):81–83
Google Scholar
Davies A (2018) What is a self-driving car? The complete WIRED guide. Wired. https://www.wired.com/story/guide-self-driving-cars/. Accessed 17 Jun 2020
de Visser EJ, Peeters MMM, Jung MF, Kohn S, Shaw TH, Pak R, Neerincx MA (2019) Towards a theory of longitudinal trust calibration in human-robot teams. Int J Soc Robot. https://doi.org/10.1007/s12369-019-00596-x
Article Google Scholar
de Winter JC, Dodou D (2014) Why the Fitts list has persisted throughout the history of function allocation. Cogn Technol Work 16(1):1–11
Article Google Scholar
Deahl D (2018) Google’s NSynth super is an AI-backed touchscreen synth. Verge. https://www.theverge.com/circuitbreaker/2018/3/13/17114760/google-nsynth-super-ai-touchscreen-synth. Accessed 17 Jun 2020
Dellermann D, Ebel P, Söllner M, Leimeister JM (2019) Hybrid intelligence. Bus Inf Syst Eng 61(5):637–643
Article Google Scholar
Department of Defense (2015) Technical assessment: autonomy. Office of Technical Intelligence, Department of Defense, Washington, DC
Dickson B (2018) There’s a huge difference between AI and human intelligence—so let’s stop comparing them. Tech Talks Blog. https://bdtechtalks.com/2018/08/21/artificial-intelligence-vs-human-mind-brain/. Accessed 17 Jun 2020
Dorado GL, Blockwood JC, Persons TM, Sanford S (2018) Artificial intelligence—emerging opportunities, challenges, and implications. United States Government Accountability Office
Ekelhof, M. A. (2018). LIFTING THE FOG OF TARGETING. Naval War College Review 71(3):61-95
Endsley MR (2018) Level of automation forms a key aspect of autonomy design. J Cognit Eng Decis Mak 12(1):29–34
Article Google Scholar
Engel D, Woolley AW, Jing LX, Chabris CF, Malone TW (2014) Reading the mind in the eyes or reading between the lines? Theory of mind predicts collective intelligence equally well online and face-to-face. PLoS ONE 9(12):e115212. https://doi.org/10.1371/journal.pone.0115212
Article Google Scholar
Engelbart DC (1962) Augmenting human intellect: a conceptual framework. Stanford Research Institute, Menlo Park
Book Google Scholar
Feltovich PJ, Prietula MJ, Anders Ericsson K (2006) Studies of expertise from psychological perspectives. In: Anders Ericsson K, Charness N, Feltovich PJ, Hoffman RR (eds) The Cambridge handbook of expertise and expert performance. Cambridge University Press, New York, pp 41–68
Chapter Google Scholar
Ferrucci DA (2012) Introduction to “This is Watson”. IBM J Res Dev 56(3.4):1:1–1:15. https://doi.org/10.1147/JRD.2012.2184356
Article Google Scholar
Fitts PM (ed) (1951) Human engineering for an effective air navigation and traffic control system. National Research Council, Washington, DC
Google Scholar
Ford M (2018) Architects of intelligence: the truth about AI from the people building it. Packt Publishing, Birmingham
Google Scholar
Friedman B, Kahn PH, Borning A, Huldtgren A (2013) Value sensitive design and information systems. In: Early engagement and new technologies: opening up the laboratory. Springer, Dordrecht, pp 55–95
Future of Life Institute (FLI) (2015) Research priorities for robust and beneficial artificial intelligence: an open letter. http://futureoflife.org/AI/open_letter. Accessed 3 Aug 2015
González RJ (2017) Hacking the citizenry?: personality profiling, ‘Big Data’ and the election of donald trump. Anthropol Today 33:9–12. https://doi.org/10.1111/1467-8322.12348
Article Google Scholar
Hadfield-Menell D, Dragan A, Abbeel P, Russell S (2017) The off-switch game. In: Workshop at the thirty-first AAAI conference on artificial intelligence. https://www.aaai.org/ocs/index.php/WS/AAAIW17/paper/view/15156. Accessed 17 Jun 2020
Hao K (2019) DeepMind wants to teach AI to play a card game that is harder than Go. MIT Technol Rev. https://www.technologyreview.com/s/612886/deepmind-wants-to-teach-ai-how-to-play-a-card-game-thats-harder-than-go/. Accessed 17 Jun 2020
Hawkins AJ (2018) Riding in Waymo One, the Google spinoff’s first self-driving taxi service. Verge. https://www.theverge.com/2018/12/5/18126103/waymo-one-self-driving-taxi-service-ride-safety-alphabet-cost-app. Accessed 17 Jun 2020
Henrich J (2015) The secret of our success: how culture is driving human evolution, domesticating our species, and making us smarter. Princeton University Press, Princeton
Book Google Scholar
High R (2012) The era of cognitive systems: an inside look at IBM Watson and how it works. IBM, New York, p 16
Google Scholar
Hollnagel E, Woods DD (2005) Joint cognitive systems: foundations of cognitive systems engineering. CRC Press, Boca Raton
Book Google Scholar
Holloway D, Green L (2016) The internet of toys. Commun Res Pract 2(4):506–519. https://doi.org/10.1080/22041451.2016.1266124
Article Google Scholar
Horton H (2016) Microsoft deletes “teen girl” AI after it became a Hitler loving sex robot within 24 hours. Telegraph. https://www.telegraph.co.uk/technology/2016/03/24/microsofts-teen-girl-ai-turns-into-a-hitler-loving-sex-robot-wit/. Accessed 17 Jun 2020
Hüllermeier E, Fober T, Mernberger M (2013) Inductive bias. In: Dubitzky W, Wolkenhauer O, Cho KH, Yokota H (eds) Encyclopaedia of systems biology. Springer, New York
Google Scholar
HumBL: Bias-aware humans-in-the-loop (HumBL) workshops. https://humlworkshop.github.io/HumBL-WWW2019
Isaak J, Hanna MJ (2018) User data privacy: Facebook, Cambridge analytica, and privacy protection. Computer 51(8):56–59. https://doi.org/10.1109/MC.2018.3191268
Article Google Scholar
Ito J (2019) Forget about artificial intelligence, extended intelligence is the future. Wired UK. https://www.wired.co.uk/article/artificial-intelligence-extended-intelligence. Accessed 17 Jun 2020
Jiang H, Nachum O (2019) Identifying and correcting label bias in machine learning. https://arxiv.org/abs/1901.04966
Johnson M, Vera A (2019) No AI is an island: the case for teaming intelligence. AI Mag 40(1):16–28
Article Google Scholar
Johnson M, Bradshaw JM, Feltovich PJ, Jonker CM, van Riemsdijk MB, Sierhuis M (2014) Coactive design: designing support for interdependence in joint activity. J Hum-Rob t Interact 3(1):43–69
Article Google Scholar
Kahneman D (2011) Thinking, fast and slow, vol 1. Farrar, Straus, and Giroux, New York
Google Scholar
Kamar E (2016) Directions in hybrid intelligence: complementing AI systems with human intelligence. In: IJCAI, pp 4070–4073
Kamphorst BA (2012) The primacy of human autonomy: understanding agent rights through the human rights framework. In: Proceedings of the 1st workshop on rights and duties of autonomous agents (RDA2), vol 885, pp 19–24
Kamphorst B, Kalis A (2015) Why option generation matters for the design of autonomous e-coaching systems. AI & Soc 30(1):77–88
Article Google Scholar
Keller AJ (2012) Robocops: regulating high frequency trading after the flash crash of 2010. Ohio State Law J 73:1457
Google Scholar
Klein G, Shneiderman B, Hoffman RR, Wears RL (2020) The “war” on expertise: five communities that seek to discredit expertise. In: Ward P, Schraagen JM, Gore J, Roth E (eds) The Oxford handbook of expertise. Oxford University Press, Oxford, pp 1157–1192
Google Scholar
Kobie N (2019) The complicated truth about China’s social credit system. Wired UK. https://www.wired.co.uk/article/china-social-credit-system-explained. Accessed 17 Jun 2020
Kunze L, Hawes N, Duckett T, Hanheide M, Krajník T (2018) Artificial intelligence for long-term robot autonomy: a survey. ArXiv:http://arxiv.org/abs/1807.05196 [Cs]. http://arxiv.org/abs/1807.05196
Kurzweil R (2005) The singularity is near: when humans transcend biology. Penguin, New York
Google Scholar
Lanier J (2018) Excerpt from “Ten arguments for deleting your social media accounts right now”. Henry Holt. https://www.barnesandnoble.com/readouts/ten-arguments-for-deleting-your-social-media-accounts-right-now/. Accessed 26 May 2019
LeBeau P (2018) GM is seeking approval for an autonomous car that has no steering wheel or pedals. CNBC. https://www.cnbc.com/2018/01/12/gm-is-seeking-approval-for-an-autonomous-car-that-has-no-steering-wheel-or-pedals.html. Accessed 17 Jun 2020
Legg S, Hutter M (2007) A collection of definitions of intelligence. Front Artif Intell Appl 157:17
Google Scholar
Licklider JC (1960) Man-computer symbiosis. IRE Trans Hum Fact Electron 1:4–11
Article Google Scholar
Lin P (2013) The ethics of autonomous cars. Atlantic. https://www.theatlantic.com/technology/archive/2013/10/the-ethics-of-autonomous-cars/280360/. Accessed 17 Jun 2020
Lin P (2014) The robot car of tomorrow may just be programmed to hit you. Wired. https://www.wired.com/2014/05/the-robot-car-of-tomorrow-might-just-be-programmed-to-hit-you/. Accessed 17 Jun 2020
Lin P (2014) Here’s a terrible idea: robot cars with adjustable ethics settings. Wired. https://www.wired.com/2014/08/heres-a-terrible-idea-robot-cars-with-adjustable-ethics-settings/. Accessed 17 Jun 2020
Liu KA, Dipietro Mager NA (2016) Women’s involvement in clinical trials: historical perspective and future implications. Pharmacy Practice (Granada) 14(1):
Lloyd K (2018) Bias amplification in artificial intelligence systems. https://arxiv.org/abs/1809.07842
López G, Quesada L, Guerrero LA (2018) Alexa vs. Siri vs. Cortana vs. Google assistant: a comparison of speech-based natural user interfaces. In: Nunes IL (ed) Advances in human factors and systems interaction. Springer International Publishing, Berlin, pp 241–250
Chapter Google Scholar
Loucks J, Hupfer S, Jarvis D, Murphy T (2019) Future in the balance? How countries are pursuing an AI advantage [Deloitte Insights]. Deloitte, London
Google Scholar
Ma A (2018) China has started ranking citizens with a creepy “social credit” system—here’s what you can do wrong, and the embarrassing, demeaning ways they can punish you. https://www.businessinsider.com/china-social-credit-system-punishments-and-rewards-explained-2018-4. Accessed 17 Apr 2019
Madrigal AC (2018) The perfect selfishness of mapping apps. Atlantic. https://www.theatlantic.com/technology/archive/2018/03/mapping-apps-and-the-price-of-anarchy/555551/. Accessed 17 Jun 2020
Maheshwari S (2017) Burger king “Ok, Google” ad doesn’t seem ok with Google. New York Times. https://www.nytimes.com/2017/04/12/business/burger-king-tv-ad-google-home.html. Accessed 17 Jun 2020
Malone TW (2018) How human-computer ‘Superminds’ are redefining the future of work. MIT Sloan Manag Rev 59(4):33–42
Google Scholar
Malone TW, Bernstein MS (2015) Handbook of collective intelligence. MIT Press, London
Google Scholar
Maurer M, Gerdes JC, Lenz B, Winner H (2016) Autonomous driving—technical, legal and social aspects. Springer, Berlin
Google Scholar
Metz C (2016) How Google’s AI viewed the move no human could understand. https://www.wired.com/2016/03/googles-ai-viewed-move-no-human-understand/. Accessed 20 Mar 2019
Metz C (2018) How will we outsmart A.I. liars? New York Times. https://www.nytimes.com/2018/11/19/science/artificial-intelligence-deepfakes-fake-news.html. Accessed 17 June 2020
Miller AP (2018) Want less-biased decisions? Use algorithms. Harvard business review, 2.
Mittrick M, Richardson J, Dennison Jr M, Trout T, Heilman E, Hanratty T (2019) Investigating immersive collective intelligence. In: Artificial intelligence and machine learning for multi-domain operations applications. International Society for Optics and Photonics, vol 11006
Morgan S (2018) Fake news, disinformation, manipulation, and online tactics to undermine democracy. J Cyber Policy 3(1):39–43
Article Google Scholar
Mulgan G (2017) Big mind: how collective intelligence can change our world. Princeton University Press, Princeton
Book Google Scholar
Neerincx MA, van der Waa J, Kaptein F, van Diggelen J (2018) Using perceptual and cognitive explanations for enhanced human-agent team performance. In: International conference on engineering psychology and cognitive ergonomics. Springer, Cham, pp 204–214
Newton-Rex E (2017) 59 impressive things artificial intelligence can do today. https://www.businessinsider.com/artificial-intelligence-ai-most-impressive-achievements-2017-3. Accessed 27 Mar 2019
Ng, A. (2016). What artificial intelligence can and can’t do right now. Harvard Business Review, 9.
O’Neil C (2017) Weapons of math destruction: how big data increases inequality and threatens democracy. Broadway Books, New York
MATH Google Scholar
Osoba OA., Welser W (2017). The risks of artificial intelligence to security and the future of work. RAND.
Article Google Scholar
Papernot N, McDaniel P, Goodfellow I, Jha S, Celik ZB, Swami A (2017) Practical black-box attacks against machine learning. In: Proceedings of the 2017 ACM on Asia conference on computer and communications security. ACM, pp 506–519. https://doi.org/10.1145/3052973.3053009
Pariser E (2011) The filter bubble: how the new personalized web is changing what we read and how we think. Penguin, New York
Google Scholar
Polya G (1945) How to solve it: a new aspect of mathematical method. Princeton University Press, Princeton
MATH Book Google Scholar
Pressler SJ (2016) Women with heart failure are disproportionately studied as compared with prevalence: a review of published studies from 2013. J Cardiovasc Nurs 31(1):84–88
Article Google Scholar
Price R (2016) Microsoft is deleting its AI chatbot’s incredibly racist tweets. Bus Insider. https://www.businessinsider.com/microsoft-deletes-racist-genocidal-tweets-from-ai-chatbot-tay-2016-3. Accessed 17 Jun 2020
Raaijmakers S, Sappelli M, Kraaij W (2017) Investigating the interpretability of hidden layers in deep text mining. In: Proceedings of semantics 2017, Amsterdam
Rahwan I, Cebrian M, Obradovich N, Bongard J, Bonnefon JF, Breazeal C, Crandall JW, Christakis A, Couzin ID, Jackson MO, Jennings NR, Kamar E, Kloumann IM, Larochelle H, Lazer D, McElreath R, Mislove A, Parkes DC, Pentland AS, Roberts ME, Shariff A, Tenenbaum JB, Wellman M (2019) Machine behaviour. Nature 568(7753):477
Article Google Scholar
Reilly P (2018) The impact of artificial intelligence on the HR function. In: IES perspectives on HR 2018, Institute of Employment Studies, UK, Member Paper 142
Rushkoff D (2010) Program or be programmed: ten commands for a digital age. Or Books
Rushkoff D (2019) Team human. Norton & Company Inc, New York
Google Scholar
Russell S (2019) Human compatible: artificial intelligence and the problem of control. Penguin, New York
Google Scholar
Russell S, Dewey D, Tegmark M (2015) Research priorities for robust and beneficial artificial intelligence. AI Mag 36(4):105. https://doi.org/10.1609/aimag.v36i4.2577
Article Google Scholar
Sage A (2018) Waymo unveils self-driving taxi service in Arizona for paying customers Reuters. Bus News. https://www.reuters.com/article/us-waymo-selfdriving-focus-idUSKBN1O41M2. Accessed 17 Jun 2020
Santos JC, Tarrit K, Mirakhorli M (2017) A catalog of security architecture weaknesses. In: 2017 IEEE international conference on software architecture workshops (ICSAW). IEEE, pp 220–223
Schank R (2017). Ten questions for (and about AI). https://www.linkedin.com/pulse/ten-questions-ai-roger-schank/. Accessed 20 Mar 2019
Searle JR (1980) Minds, brains, and programs. Behav Brain Sci 3(3):417–424
Article Google Scholar
Sesay A, Steffen J (2020) Wearables as augmentation means: conceptual definition, pathways, and research framework. In: Proceedings of the 53rd Hawaii international conference on system sciences
Sharkey N (2017) Why robots should not be delegated with the decision to kill. Connect Sci 29(2):1771–1786. https://doi.org/10.1080/09540091.2017.1310183
MathSciNet Article Google Scholar
Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, Hubert T, Baker L, Lai M, Bolton A, Chen Y, Lillicrap T, Hui F, Sifre L, van den Driesse G, Graepel T, Hassabis D (2017) Mastering the game of go without human knowledge. Nature 550(7676):354–359
Article Google Scholar
Simonite T (2017) Sorry, banning ‘killer robots’ just isn’t practical. Wired. https://www.wired.com/story/sorry-banning-killer-robots-just-isnt-practical/. Accessed 22 Aug 2017
Sloman S, Fernbach P (2018) The knowledge illusion: why we never think alone. Penguin, New York
Google Scholar
Smirnov A, Ponomarev A (2019) Decision support based on human-machine collective intelligence: Major challenges. In Internet of Things, Smart Spaces, and Next Generation Networks and Systems (pp. 113-124). Springer, Cham
Smit, S. K., Vries, A. D., Kleij, R., & van Vliet, P. J. (2016). Van predictive naar prescriptive policing: Verder dan vakjes voorspellen. TNO, The Hague
Google Scholar
Streitfeld D (2018) Computer stories: A.I. is beginning to assist novelists. New York Times. https://www.nytimes.com/2018/10/18/technology/ai-is-beginning-to-assist-novelists.html
Surden H, Williams MA (2016) Technological opacity, predictability, and self-driving cars. Cardozo L. Rev 38:121
Google Scholar
Sutton J, Harris CB, Keil PG, Barnier AJ (2010) The psychology of memory, extended cognition, and socially distributed remembering. Phenomenol Cognit Scinces 9(4):521–560
Article Google Scholar
Thai J, Laurent-Brouty N, Bayen AM (2016) Negative externalities of GPS-enabled routing applications: a game theoretical approach. In: 2016 IEEE 19th international conference on intelligent transportation systems (ITSC), 595–601. https://doi.org/10.1109/ITSC.2016.7795614
Theiner G, Allen C, Goldstone RL (2010) Recognizing group cognition. Cognit Syst Res 11(4):378–395
Article Google Scholar
van Diggelen J, Neerincx M, Peeters M, Schraagen JM (2018) Developing effective and resilient human-agent teamwork using team design patterns. IEEE intelligent systems, 34(2), 15-24
van Diggelen J, Barnhoorn JS, Peeters MMM, van Staal W, van Stolk M, van der Vecht B, van der Waa J, Schraagen JM (2019) Pluggable social artificial intelligence for enabling human-agent teaming. arXiv:1909.04492
van Panhuis WG, Paul P, Emerson C, Grefenstette J, Wilder R, Herbst AJ, Heymann D, Burke DS (2014) A systematic review of barriers to data sharing in public health. BMC Public Health 14(1):1144
Article Google Scholar
Surowiecki J (2005) The wisdom of crowds. Anchor Books, New York
Google Scholar
van Wynsberghe A, Robbins S (2018) Critiquing the reasons for making artificial moral agents. Sci Eng Ethics. https://doi.org/10.1007/s11948-018-0030-8
Article Google Scholar
Wallis KF (2014) Revisiting Francis Galton’s forecasting competition. Stat Sci 29:420–424
MathSciNet MATH Article Google Scholar
Weise E (2017) Waze and other traffic dodging apps prompt cities to game the algorithms. USA Today. https://eu.usatoday.com/story/tech/news/2017/03/06/mapping-software-routing-waze-google-traffic-calming-algorithmsi/98588980/. Accessed 17 Jun 2020
Weizenbaum J (1966) ELIZA—a computer program for the study of natural language communication between man and machine. Commun ACM 9(1):36–45
Article Google Scholar
Winter C (2017) “Killer robots”: autonomous weapons pose moral dilemma. Deutsche Welle. https://www.dw.com/en/killer-robots-autonomous-weapons-pose-moral-dilemma/a-41342616. Accessed 17 Jun 2020
Wolfson S (2018) Amazon’s Alexa recorded private conversation and sent it to random contact. Guardian. https://www.theguardian.com/technology/2018/may/24/amazon-alexa-recorded-conversation. Accessed 17 Jun 2020
Woods DD (2016) The risks of autonomy: Doyle’s catch. J Cognit Eng Decis Mak 10(2):131–133
Article Google Scholar
Woolley SC, Howard PN (2017) Computational propaganda worldwide: executive summary. In: Woolley S, Howard PN (eds) Working Paper, 2017. Project on Computational Propaganda, Oxford. https://comprop.oii.ox.ac.uk/
Woolley AW, Chabris CF, Pentland A, Hashmi N, Malone TW (2010) Evidence for a collective intelligence factor in the performance of human groups. Science 330(6004):686–688
Article Google Scholar
Yampolskiy RV, Spellchecker MS (2016) Artificial intelligence safety and cybersecurity: a timeline of AI failures. http://arxiv.org/abs/1610.07997 [Cs], October 25, 2016. http://arxiv.org/abs/1610.07997

Download references

Acknowledgments

This material is based upon work supported by the Dutch Ministry of Defence’s exploratory research program (project Human-AI Teaming).

Author information

Authors and Affiliations

TNO, Kampweg 55, 3769 DE, Soesterberg, The Netherlands
Marieke M. M. Peeters, Jurriaan van Diggelen, Karel van den Bosch, Adelbert Bronkhorst, Mark A. Neerincx, Jan Maarten Schraagen & Stephan Raaijmakers
Delft University of Technology, Van Mourik Broekmanweg 6, 2628 XE, Delft, The Netherlands
Mark A. Neerincx
University of Twente, De Zul 10, 7522 NJ, Enschede, The Netherlands
Jan Maarten Schraagen
Xomnia, Raamstraat 7-I, 1016 XL, Amsterdam, The Netherlands
Marieke M. M. Peeters
Leiden University, Van Wijkplaats 4, 2311 BX, Leiden, The Netherlands
Stephan Raaijmakers

Authors

Marieke M. M. Peeters
View author publications
You can also search for this author in PubMed Google Scholar
Jurriaan van Diggelen
View author publications
You can also search for this author in PubMed Google Scholar
Karel van den Bosch
View author publications
You can also search for this author in PubMed Google Scholar
Adelbert Bronkhorst
View author publications
You can also search for this author in PubMed Google Scholar
Mark A. Neerincx
View author publications
You can also search for this author in PubMed Google Scholar
Jan Maarten Schraagen
View author publications
You can also search for this author in PubMed Google Scholar
Stephan Raaijmakers
View author publications
You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jurriaan van Diggelen.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Peeters, M.M.M., van Diggelen, J., van den Bosch, K. et al. Hybrid collective intelligence in a human–AI society. AI & Soc 36, 217–238 (2021). https://doi.org/10.1007/s00146-020-01005-y

Download citation

Received: 14 January 2020
Accepted: 08 June 2020
Published: 25 June 2020
Issue Date: March 2021
DOI: https://doi.org/10.1007/s00146-020-01005-y

Keywords

Artificial intelligence
Hybrid intelligence
Collective intelligence
Human intelligence
Human–AI collaboration
Human–AI society