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Articles

Clearing the way for participatory data stewardship in artificial intelligence development: a mixed methods approach

ORCID Icon, , &
Pages 1782-1799 | Received 10 May 2023, Accepted 28 Nov 2023, Published online: 18 Dec 2023

References

  • Ajzen, I. 1991. “The Theory of Planned Behavior.” Organizational Behavior and Human Decision Processes 50 (2): 179–211. doi:10.1016/0749-5978(91)90020-T.
  • Ajzen, I., and M. Fishbein. 1975. “A Bayesian Analysis of Attribution Processes.” Psychological Bulletin 82 (2): 261–277. doi:10.1037/h0076477.
  • Andreoni, J. 1990. “Impure Altruism and Donations to Public Goods: A Theory of Warm-Glow Giving.” The Economic Journal 100 (401): 464–477. doi:10.2307/2234133.
  • Andrews, J.E., H. Ward, and J. Yoon. 2021. “UTAUT as a Model for Understanding Intention to Adopt AI and Related Technologies among Librarians.” The Journal of Academic Librarianship 47 (6): 102437. doi:10.1016/j.acalib.2021.102437.
  • Araujo, T., J. Ausloos, W. van Atteveldt, F. Loecherbach, J. Moeller, J. Ohme, D. Trilling, B. van de Velde, C. de Vreese, and K. Welbers. 2022. “Osd2f: An Open-Source Data Donation Framework.” Computational Communication Research 4 (2): 372–387. doi:10.31235/osf.io/xjk6t.
  • Beck, T.W. 2013. “The Importance of a Priori Sample Size Estimation in Strength and Conditioning Research.” Journal of Strength and Conditioning Research 27 (8): 2323–2337. doi:10.1519/JSC.0b013e318278eea0.
  • Belanche, D., L.V. Casalo, and C. Flavian. 2019. “Artificial Intelligence in FinTech: understanding Robo-Advisors Adoption among Customers.” Industrial Management & Data Systems 119 (7): 1411–1430. doi:10.1108/IMDS-08-2018-0368.
  • Bietz, M., K. Patrick, and C. Bloss. 2019. “Data Donation as a Model for Citizen Science Health Research.” Citizen Science: Theory and Practice 4 (1): 1–11. doi:10.5334/cstp.178.
  • Birhane, A., W. Isaac, V. Prabhakaran, M. Díaz, M.C. Elish, I. Gabriel, and S. Mohamed. 2022. “Power to the People? Opportunities and Challenges for Participatory AI.” Equity and Access in Algorithms, Mechanisms, and Optimization 1–8. doi:10.1145/3551624.3555290.
  • Bonney, R., H. Ballard, R. Jordan, E. McCallie, T. Phillips, J. Shirk, C. Wilderman. 2009. Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report.A CAISE Inquiry Group Report.
  • Bowerman, B.L., and R.T. O’Connell. 1990. Linear Statistical Models: An Applied Approach. USA: Brooks/Cole.
  • Buolamwini, J., and T. Gebru. 2018. “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.” Paper presented at the Conference on Fairness, Accountability and Transparency, April, 2020. https://proceedings.mlr.press/v81/buolamwini18a.html
  • Carlo, G., M.A. Okun, G.P. Knight, and M.R.T. de Guzman. 2005. “The Interplay of Traits and Motives on Volunteering: Agreeableness, Extraversion and Prosocial Value Motivation.” Personality and Individual Differences 38 (6): 1293–1305. doi:10.1016/j.paid.2004.08.012.
  • Centre for Data Ethics and Innovation. 2021. “BritainThinks: Trust in Data” Accessed December, 2022. https://www.gov.uk/government/publications/britainthinks-trust-in-data
  • Centre for Data Ethics and Innovation. 2022. “Public Attitudes to Data and AI: Tracker Survey.” Accessed March, 2023. https://www.gov.uk/government/publications/public-attitudes-to-data-and-ai-tracker-survey
  • Chan, A., C.T. Okolo, Z. Terner, and A. Wang. 2021. “The Limits of Global Inclusion in AI Development.” Accessed March, 2022. https://arxiv.org/abs/2102.01265
  • Chaudhry, I.S., R.Y. Paquibut, and H. Chabchoub. 2022. “Factors Influencing Employees Trust in AI; It’s Adoption at Work: Evidence from United Arab Emirates.” In 2022 International Arab Conference on Information Technology (ACIT), 1–7. IEEE. doi:10.1109/acit57182.2022.9994226.
  • Cheng, T.E., D.Y. Lam, and A.C. Yeung. 2006. “Adoption of Internet Banking: An Empirical Study in Hong Kong.” Decision Support Systems 42 (3): 1558–1572. doi:10.1016/j.dss.2006.01.002.
  • Choi, Y. 2020. “A Study of Employee Acceptance of Artificial Intelligence Technology.” European Journal of Management and Business Economics 30 (3): 318–330. doi:10.1108/EJMBE-06-2020-0158.
  • Choung, H., P. David, and A. Ross. 2022. “Trust in ai and Its Role in the Acceptance of ai Technologies.” International Journal of Human–Computer Interaction 39 (9): 1727–1739. doi:10.1080/10447318.2022.2050543.
  • Chow, A., and B. Perrigo. 2023. “The AI Arms Race is Changing Everything.” Time. Accessed February, 2023. https://time.com/6255952/ai-impact-chatgpt-microsoft-google/.
  • Cohen, J. 2013. Statistical Power Analysis for the Behavioral Sciences. USA: Academic Press.
  • Couldry, N., C. Rodriguez, G. Bolin, J. Cohen, G. Goggin, M.M. Kraidy, K. Iwabuchi, K.-S. Lee, J. Qiu, and I. Volkmer. 2018. “Inequality and Communicative Struggles in Digital Times: A Global Report on Communication for Social Progress.” Accessed January, 2023. https://repository.upenn.edu/cgi/viewcontent.cgi?article=1001&context=cargc_strategicdocuments
  • Davis, F.D. 1985. A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. USA: Massachusetts Institute of Technology.
  • Davis, F.D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13 (3): 319–340. doi:10.2307/249008.
  • Deloitte and Reform. 2018. “Citizens, Government and Business: The State of the State 2017-18.” Accessed January, 2023. https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/public-sector/deloitte-uk-the-state-of-the-state-report-2017.pdf
  • Dinev, T., and P. Hart. 2006. “An Extended Privacy Calculus Model for e-Commerce Transactions.” Information Systems Research 17 (1): 61–80. doi:10.1287/isre.1060.0080.
  • Donia, J., and J.A. Shaw. 2021. “Co-Design and Ethical Artificial Intelligence for Health: An Agenda for Critical Research and Practice.” Big Data & Society 8 (2): 205395172110652. doi:10.1177/20539517211065248.
  • European Commission. 2017. “Special Eurobarometer 460-Attitudes towards the Impact of Digitisation and Automation on Daily Life.” Accessed January, 2023. https://ec.europa.eu/info/departments/communication
  • European Commission. 2022. “The Digital Services Act Package.” Accessed March, 2023. https://digital-strategy.ec.europa.eu/en/policies/digital-services-act-package
  • Evans, R., and E. Ferguson. 2014. “Defining and Measuring Blood Donor Altruism: A Theoretical Approach from Biology, Economics and Psychology.” Vox Sanguinis 106 (2): 118–126. doi:10.1111/vox.12080.
  • Eyers, J. 2021. Banks Warned using AI in Loan Assessments could ‘Awaken a Zombie’. Australian Financial Review. https://www.afr.com/companies/financial-services/banks-warned-using-ai-in-loan-assessments-could-awaken-a-zombie-20210615-p5814i
  • Faul, F., E. Erdfelder, A. Buchner, and A.-G. Lang. 2009. “Statistical Power Analyses Using G*Power 3.1: Tests for Correlation and Regression Analyses.” Behavior Research Methods 41 (4): 1149–1160. doi:10.3758/BRM.41.4.1149.
  • Ferguson, E. 2015. “Mechanism of Altruism Approach to Blood Donor Recruitment and Retention: A Review and Future Directions.” Transfusion Medicine 25 (4): 211–226. doi:10.1111/tme.12233.
  • Ferguson, E., and C. Lawrence. 2016. “Blood Donation and Altruism: The Mechanisms of Altruism Approach.” ISBT Science Series 11 (S1): 148–157. doi:10.1111/voxs.12209.
  • Fietta, V., F. Zecchinato, B. Di Stasi, M. Polato, and M. Monaro. 2022. “Dissociation between Users’ Explicit and Implicit Attitudes toward Artificial Intelligence: An Experimental Study.” IEEE Transactions on Human-Machine Systems 52 (3): 481–489. doi:10.1109/THMS.2021.3125280.
  • Fishbein, M. 2008. “A Reasoned Action Approach to Health Promotion.” Medical Decision Making: An International Journal of the Society for Medical Decision Making 28 (6): 834–844. doi:10.1177/0272989x08326092.
  • Fishbein, M., I. Ajzen, and A. Belief. 1975. Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
  • Gado, S., R. Kempen, K. Lingelbach, and T. Bipp. 2021. “Artificial Intelligence in Psychology: How Can we Enable Psychology Students to Accept and Use Artificial Intelligence?.” Psychology Learning & Teaching 21 (1): 37–56. doi:10.1177/14757257211037149.
  • Gefen, D., Karahanna, E., & Straub, D.W. (2003). Trust and Tam in Online Shopping: An Integrated Model. MIS Quarterly, 27(1): 51–90. doi:10.2307/30036519.
  • Gibbons, F.X., M. Gerrard, H. Blanton, and D.W. Russell. 1998. “Reasoned Action and Social Reaction: Willingness and Intention as Independent Predictors of Health Risk.” Journal of Personality and Social Psychology 74 (5): 1164–1180. doi:10.1037/0022-3514.74.5.1164.
  • Gillath, O., T. Ai, M.S. Branicky, S. Keshmiri, R.B. Davison, and R. Spaulding. 2021. “Attachment and Trust in Artificial Intelligence.” Computers in Human Behavior 115: 106607. doi:10.1016/j.chb.2020.106607.
  • Gomez Ortega, A., J. Bourgeois, and G. Kortuem. 2022. “Reconstructing Intimate Contexts through Data Donation: A Case Study in Menstrual Tracking Technologies.” Paper presented at the NordiCHI '22: Nordic Human-Computer Interaction Conference, Aarhus, Denmark, October 2022. doi:10.1145/3546155.3546646.
  • Goyal, M., T. Knackstedt, S. Yan, and S. Hassanpour. 2020. “Artificial Intelligence-Based Image Classification Methods for Diagnosis of Skin Cancer: Challenges and Opportunities.” Computers in Biology and Medicine 127: 104065.doi:10.1016/j.compbiomed.2020.104065. PMC: 33246265.
  • Guo, X., X. Han, X. Zhang, Y. Dang, and C. Chen. 2015. “Investigating m-Health Acceptance from a Protection Motivation Theory Perspective: Gender and Age Differences.” Telemedicine Journal and e-Health 21 (8): 661–669. doi:10.1089/tmj.2014.0166.
  • Gursoy, D., O.H. Chi, L. Lu, and R. Nunkoo. 2019. “Consumers Acceptance of Artificially Intelligent (AI) Device Use in Service Delivery.” International Journal of Information Management 49: 157–169. doi:10.1016/j.ijinfomgt.2019.03.008.
  • Harrington, C., S. Erete, and A.M. Piper. 2019. “Deconstructing Community-Based Collaborative Design: Towards More Equitable Participatory Design Engagements.” Proceedings of the ACM on Human-Computer Interaction 3 (CSCW): 1–25. doi:10.1145/3359318.
  • Hoofnagle, C.J., J. King, S. Li, and J. Turow. 2010. “How Different Are Young Adults from Older Adults When It Comes to Information Privacy Attitudes and Policies?” SSRN Electronic Journal 1–20. doi:10.2139/ssrn.1589864.
  • Jarrahi, M.H., C. Lutz, K. Boyd, C. Oesterlund, and M. Willis. 2023. “Artificial Intelligence in the Work Context.” Journal of the Association for Information Science and Technology 74 (3): 303–310. doi:10.1002/asi.24730.
  • Kaplan, A.D., T.T. Kessler, J.C. Brill, and P. Hancock. 2021. “Trust in Artificial Intelligence: Meta-Analytic Findings.” Human Factors 65 (2): 337–359. doi:10.1177/00187208211013988.
  • Kapoor, A., and R.S. Whitt. 2021. “Nudging towards Data Equity: The Role of Stewardship and Fiduciaries in the Digital Economy.” SSRN Electronic Journal 1–18. doi:10.2139/ssrn.3791845.
  • Kaye, S.-A., I. Lewis, S. Forward, and P. Delhomme. 2020. “A Priori Acceptance of Highly Automated Cars in Australia, France, and Sweden: A Theoretically-Informed Investigation Guided by the TPB and UTAUT.” Accident; Analysis and Prevention 137: 105441. doi:10.1016/j.aap.2020.105441.
  • Kelly, S., S.-A. Kaye, and O. Oviedo-Trespalacios. 2022. “A Multi-Industry Analysis of the Future Use of AI Chatbots.” Human Behavior and Emerging Technologies 2022: 1–14. doi:10.1155/2022/2552099.
  • Kelly, S., S.-A. Kaye, and O. Oviedo-Trespalacios. 2023. “What Factors Contribute to the Acceptance of Artificial Intelligence? A Systematic Review.” Telematics and Informatics 77: 101925. doi:10.1016/j.tele.2022.101925.
  • Lashbrook, A. 2018. Ai-driven Dermatology could Leave Dark-skinned Patients Behind. The Atlantic. https://www.theatlantic.com/health/archive/2018/08/machine-learning-dermatology-skin-color/567619/
  • Lawrence, N., and N. Oh. 2021. “Enabling Data Sharing for Social Benefit through Data Trusts.” Accessed March, 2023. https://gpai.ai/projects/data-governance/data-trusts/enabling-data-sharing-for-social-benefit-through-data-trusts.pdf
  • Leslie, D., A. Mazumder, A. Peppin, M.K. Wolters, and A. Hagerty. 2021. “Does “AI” Stand for Augmenting Inequality in the Era of Covid-19 Healthcare?” BMJ (Clinical Research ed.) 372: n304. doi:10.1136/bmj.n304.
  • Lin, H.-C., T. Yun-Fang, H. Gwo-Jen, and H. Hsin. 2021. “From Precision Education to Precision Medicine: Factors Affecting Medical Staff’s Intention to Learn to Use AI Applications in Hospitals.” Journal of Educational Technology & Society 24 (1): 123–137. https://www.jstor.org/stable/26977862.
  • Liu, K., and D. Tao. 2022. “The Roles of Trust, Personalization, Loss of Privacy, and Anthropomorphism in Public Acceptance of Smart Healthcare Services.” Computers in Human Behavior 127: 107026. doi:10.1016/j.chb.2021.107026.
  • Liu, Z., J. Shan, and Y. Pigneur. 2016. “The Role of Personalized Services and Control: An Empirical Evaluation of Privacy Calculus and Technology Acceptance Model in the Mobile Context.” Journal of Information Privacy and Security 12 (3): 123–144. doi:10.1080/15536548.2016.1206757.
  • Lockey, S., N. Gillespie, and S. Curtis. 2020. Trust in Artificial Intelligence: Australian Insights. Accessed March, 2023.
  • Luo, J., and G. Gao. 2022. “Donor Recognition: A Double‐Edged Sword in Charitable Giving.” Journal of Philanthropy and Marketing 28 (1): 1–20. doi:10.1002/nvsm.1772.
  • McMahon, R., and M. Byrne. 2008. “Predicting Donation among an Irish Sample of Donors and Nondonors: Extending the Theory of Planned Behavior.” Transfusion 48 (2): 321–331. doi:10.1111/j.1537-2995.2007.01526.x.
  • Memon, A.M., and A. Memon. 2021. “Exploring Acceptance of Artificial Intelligence Amongst Healthcare Personnel: A Case in a Private Medical Centre.” International Research Journal of Modernization in Engineering Technology and Science 3 (9): 1–11.
  • Meyer-Waarden, B.L., and J. Cloarec. 2021. “Baby, You Can Drive my Car”: Psychological Antecedents That Drive Consumers’ Adoption of AI-Powered Autonomous Vehicles [Article].” Technovation 109: 102348. doi:10.1016/j.technovation.2021.102348.
  • Monteith, S., T. Glenn, J. Geddes, P.C. Whybrow, E. Achtyes, and M. Bauer. 2022. “Expectations for Artificial Intelligence (AI) in Psychiatry.” Current Psychiatry Reports 24 (11): 709–721. doi:10.1007/s11920-022-01378-5.
  • Mujcic, R., and A. Leibbrandt. 2018. “Indirect Reciprocity and Prosocial Behaviour: Evidence from a Natural Field Experiment.” The Economic Journal 128 (611): 1683–1699. doi:10.1111/ecoj.12474.
  • Mun, Y.Y., J.D. Jackson, J.S. Park, and J.C. Probst. 2006. “Understanding Information Technology Acceptance by Individual Professionals: Toward an Integrative View.” Information & Management 43 (3): 350–363. doi:10.1016/j.im.2005.08.006.
  • Na, S., S. Heo, S. Han, Y. Shin, and Y. Roh. 2022. “Acceptance Model of Artificial Intelligence (ai)-Based Technologies in Construction Firms: Applying the Technology Acceptance Model (Tam) in Combination with the Technology–Organisation–Environment (Toe) Framework.” Buildings 12 (2): 90. doi:10.3390/buildings12020090.
  • Nadkarni, S., & Gupta, R. (2007). “A Task-Based Model of Perceived Website Complexity.” MIS Quarterly 31 (3): 501–524. doi:10.2307/25148805.
  • Nazaretsky, T., M. Ariely, M. Cukurova, and G. Alexandron. 2022. “Teachers’ Trust in AI‐Powered Educational Technology and a Professional Development Program to Improve It.” British Journal of Educational Technology 53 (4): 914–931. doi:10.1111/bjet.13232.
  • Parkes, E., J. Hardinges, J. Crowe, J. Massey, and S. Moriniere. 2023. “Defining Responsible Data Stewardship.” Accessed April 2023. https://theodi.org/insights/reports/defining-responsible-data-stewardship/
  • Patel, R., A. Peppin, V. Pavel, J. Brennan, I. Parker, and C. Safak. 2021. “Participatory Data Stewardship.” Accessed March, 2023. https://www.adalovelaceinstitute.org/report/participatory-data-stewardship/
  • Peppin, A. 2022. “Who Cares What the Public Think?” https://www.adalovelaceinstitute.org/evidence-review/public-attitudes-data-regulation/
  • Piantadosi, S.T. 2023. [@spiantado]. Yes, ChatGPT Is Amazing and Impressive. No, @OpenAI Has Not Come Close to Addressing the Problem of Bias. Filters Appear to be Bypassed with Simple Tricks, and Superficially Masked. And What Is Lurking Inside Is Egregious. Twitter. Accessed March 2023.
  • Pilz, D., and H. Gewald. 2013. “Does Money Matter? Motivational Factors for Participation in Paid-and Non-Profit-Crowdsourcing Communities.” Paper presented at the 11th International Conference on Wirtschaftsinformatik, Leipzig, March 2023. https://twitter.com/spiantado/status/1599462375887114240?lang=en. https://www.researchgate.net/publication/270811012_Does_Money_Matter_Motivational_Factors_for_Participation_in_Paid-and_Non-Profit-Crowdsourcing_Communities
  • Platt, J., and S. Kardia. 2015. “Public Trust in Health Information Sharing: Implications for Biobanking and Electronic Health Record Systems.” Journal of Personalized Medicine 5 (1): 3–21. doi:10.3390/jpm5010003.
  • Pomery, E.A., F.X. Gibbons, M. Reis-Bergan, and M. Gerrard. 2009. “From Willingness to Intention: Experience Moderates the Shift from Reactive to Reasoned Behavior.” Personality & Social Psychology Bulletin 35 (7): 894–908. doi:10.1177/0146167209335166.
  • Rafique, H., A.O. Almagrabi, A. Shamim, F. Anwar, and A.K. Bashir. 2020. “Investigating the Acceptance of Mobile Library Applications with an Extended Technology Acceptance Model (Tam).” Computers & Education 145: 103732. doi:10.1016/j.compedu.2019.103732.
  • Richter, G., C. Borzikowsky, B.F. Hoyer, M. Laudes, and M. Krawczak. 2021. “Secondary Research Use of Personal Medical Data: Patient Attitudes towards Data Donation.” BMC Medical Ethics 22 (1): 164. doi:10.1186/s12910-021-00728-x.
  • Ridsdale, C., J. Rothwell, M. Smit, H. Ali-Hassan, M. Bliemel, D. Irvine, D. Kelley, S. Matwin, and B. Wuetherick. 2015. “Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report.” Dalhouse University. doi:10.13140/RG.2.1.1922.5044.
  • Robertson, A., and M. Maccarone. 2022. “AI Narratives and Unequal Conditions. Analyzing the Discourse of Liminal Expert Voices in Discursive Communicative Spaces.” Telecommunications Policy 47 (5): 102462. doi:10.1016/j.telpol.2022.102462.
  • Schmidthuber, L., D. Hilgers, and K. Randhawa. 2021. “Public Crowdsourcing: Analyzing the Role of Government Feedback on Civic Digital Platforms.” Public Administration 100 (4): 960–977. doi:10.1111/padm.12811.
  • Seger, E., A. Ovadya, B. Garfinkel, D. Siddarth, and A. Dafoe. 2023. “Democratising AI: Multiple Meanings, Goals, and Methods.” In Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 715–722. doi:10.48550/arXiv.2303.12642.
  • Selwyn, N., and B. Gallo Cordoba. 2022. “Australian Public Understandings of Artificial Intelligence.” AI & Society 37 (4): 1645–1662. doi:10.1007/s00146-021-01268-z.
  • Seo, K.H., and J.H. Lee. 2021. “The Emergence of Service Robots at Restaurants: Integrating Trust, Perceived Risk, and Satisfaction.” Sustainability, 13 (8): 4431. doi:10.3390/su13084431.
  • Septianto, F., F. Tjiptono, W. Paramita, and T.M. Chiew. 2020. “The Interactive Effects of Religiosity and Recognition in Increasing Donation.” European Journal of Marketing 55 (1): 1–26. doi:10.1108/EJM-04-2019-0326.
  • Singh, S., and N. Ramakrishnan. 2023. Is ChatGPT Biased? A Review. doi:10.31219/osf.io/9xkbu.
  • Skatova, A., and J. Goulding. 2019. “Psychology of Personal Data Donation.” PLoS One 14 (11): e0224240. doi:10.1371/journal.pone.0224240.
  • Sloane, M. 2019. “Inequality is the Name of the Game. Thoughts on the Emerging Field of Technology, Ethics and Social Justice.” Paper presented at the Weizenbaum Conference 2019 Challenges of Digital Inequity, Berlin, Germany. doi:10.34669/wi.cp.
  • Sloane, M., E. Moss, O. Awomolo, and L. Forlano. 2020. “Participation Is Not a Design Fix for Machine Learning.” In Equity and Access in Algorithms, Mechanisms, and Optimization, 1–6. Washington, DC. doi:10.1145/3551624.3555285.
  • Song, Y.W. 2019. “User Acceptance of an Artificial Intelligence (AI) Virtual Assistant: An Extension of the Technology Acceptance Model.” Thesis, DDU. https://search.ebscohost.com/login.aspx?direct=true&db=ddu&AN=194F628A9A233EB6&site=ehost-live&scope=site.
  • Sousa, S., and G. Beltrão. 2021. “Factors Influencing Trust Assessment in Technology.” Paper presented at the IFIP Conference on Human-Computer Interaction, Proceedings, Part V, August 30 – September 3, 2021, Bari, Italy. Accessed March, 2022. https://doi.org/10.1007/978-3-030-85607-6_49#Sec2
  • Spitale, G., N. Biller-Andorno, and F. Germani. 2023. “AI Model GPT-3 (Dis) Informs us Better than Humans.” arXiv preprint arXiv:2301.11924.
  • Srinivasan, A. 2021. The Right to Sex. UK: Bloomsbury Publishing.
  • Stracke, C.M. 2020. “Open Science and Radical Solutions for Diversity, Equity and Quality in Research: A Literature Review of Different Research Schools, Philosophies and Frameworks and Their Potential Impact on Science and Education.”. In 17–37. Singapore: Springer. doi:10.1007/978-981-15-4276-3_2.
  • Swisher, K. 2023. On With Kara Swisher. In Sam Altman on What Makes Him ‘Super Nervous’ About AI The OpenAI Co-founder Thinks Tools like GPT-4 Will Be Revolutionary. But He’s Wary of Downsides. https://nymag.com/intelligencer/2023/03/on-with-kara-swisher-sam-altman-on-the-ai-revolution.html
  • Thornton, B., F.X. Gibbons, and M. Gerrard. 2002. “Risk Perception and Prototype Perception: Independent Processes Predicting Risk Behavior.” Personality and Social Psychology Bulletin 28 (7): 986–999. doi:10.1177/014616720202800711.
  • van Eeuwen, M. 2017. “Mobile Conversational Commerce: Messenger Chatbots as the Next Interface between Businesses and Consumers.” University of Twente. Accessed March, 2023. http://purl.utwente.nl/essays/71706
  • van Empelen, P., and G. Kok. 2006. “Condom Use in Steady and Casual Sexual Relationships: Planning, Preparation and Willingness to Take Risks among Adolescents.” Psychology & Health 21 (2): 165–181. doi:10.1080/14768320500229898.
  • Venkatesh, V., and F.D. Davis. 2000. “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies.” Management Science 46 (2): 186–204. doi:10.1287/mnsc.46.2.186.11926.
  • Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly 27(3): 425–478. doi:10.2307/30036540.
  • Walsh, T. 2018. 2062: The World That ai Made. Australia: La Trobe University Press.
  • White, K.M., B.E. Poulsen, and M.K. Hyde. 2017. “Identity and Personality Influences on Donating Money, Time, and Blood.” Nonprofit and Voluntary Sector Quarterly 46 (2): 372–394. doi:10.1177/0899764016654280.
  • Whittlestone, J., R. Nyrup, A. Anexandrova, K. Dihal, and S. Cave. 2019. “Ethical and Societal Implications of Algorithms, Data, and Artificial Intelligence: A Roadmap for Research.” Accessed December, 2022. https://www.nuffieldfoundation.org/sites/default/files/files/Ethical-and-Societal-Implications-of-Data-and-AI-report-Nuffield-Foundat.pdf.
  • Wijnhoven, F., M. Ehrenhard, and J. Kuhn. 2015. “Open Government Objectives and Participation Motivations.” Government Information Quarterly 32 (1): 30–42. doi:10.1016/j.giq.2014.10.002.
  • Xiang, Yifan, Lanqin Zhao, Zhenzhen Liu, Xiaohang Wu, Jingjing Chen, Erping Long, Duoru Lin, Yi Zhu, Chuan Chen, Zhuoling Lin, and Haotian Lin. 2020. “Implementation of Artificial Intelligence in Medicine: Status Analysis and Development Suggestions.” Artificial Intelligence in Medicine 102: 101780. doi:10.2147/PPA.S225952.
  • Yang, K., Z. Zeng, H. Peng, and Y. Jiang. 2019. “Attitudes of Chinese Cancer Patients toward the Clinical Use of Artificial Intelligence.” Patient Preference and Adherence 13: 1867–1875. volume doi:10.2147/ppa.s225952.
  • Yigitcanlar, T., K. Degirmenci, and T. Inkinen. 2022. “Drivers behind the Public Perception of Artificial Intelligence: Insights from Major Australian Cities.” AI & Society: 1–21. doi:10.1007/s00146-022-01566-0.
  • Young, A. 2018. “About the Data Stewards Network.” Accessed March, 2023. https://medium.com/data-stewards-network/about-the-data-stewards-network-1cb9db0c0792