References
- Aw, E. N. W., J. Jiang, and J. Q. Jiang. 2019. “Rise of the Machines: Factor Investing with Artificial Neural Networks and the Cross–Section of Expected Stock Returns.” The Journal of Investing 29 (1): 6–17. doi:https://doi.org/10.3905/joi.2019.1.108.
- Bessette, D., J. Arvai, and V. Campbell-Arvai. 2014. “Decision Support Framework for Developing Regional Energy Strategies.” Environmental Science & Technology 48 (3): 1401–1408. doi:https://doi.org/10.1021/es4036286.
- Bessette, D. L., V. Campbell-Arvai, and J. Arvai. 2016. “Expanding the Reach of Participatory Risk Management: Testing an Online Decision-Aiding Framework for Informing Internally Consistent Choices.” Risk Analysis : An Official Publication of the Society for Risk Analysis 36 (5): 992–1005. doi:https://doi.org/10.1111/risa.12481.
- Caliskan, A., J. J. Bryson, and A. Narayanan. 2017. “Semantics Derived Automatically from Language Corpora Contain Human-like Biases.” Science (New York, N.Y.) 356 (6334): 183–186. doi:https://doi.org/10.1126/science.aal4230.
- Dawes, R. M., D. Faust, and P. E. Meehl. 1989. “Clinical versus Actuarial Judgment.” Science (New York, N.Y.) 243 (4899): 1668–1674. doi:https://doi.org/10.1126/science.2648573.
- de Groot, J. I. M., and L. Steg. 2008. “Value Orientations to Explain Beliefs Related to Environmental Significant Behavior: How to Measure Egoistic, Altruistic, and Biospheric Value Orientations.” Environment and Behavior 40 (3): 330–354. doi:https://doi.org/10.1177/0013916506297831.
- Dietvorst, B. J., J. P. Simmons, and C. Massey. 2015. “Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err.” Journal of Experimental Psychology. General 144 (1): 114–126. doi:https://doi.org/10.1037/xge0000033.
- Dietvorst, B. J., J. P. Simmons, and C. Massey. 2018. “Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them.” Management Science 64 (3): 1155–1170. doi:https://doi.org/10.1287/mnsc.2016.2643.
- Dounis, A. I. 2010. “Artificial Intelligence for Energy Conservation in Buildings.” Advances in Building Energy Research 4 (1): 267–299. doi:https://doi.org/10.3763/aber.2009.0408.
- Esteva, A., B. Kuprel, R. A. Novoa, J. Ko, S. M. Swetter, H. M. Blau, and S. Thrun. 2017. “ Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks .” Nature 546 (7660): 686–118. doi:https://doi.org/10.1038/nature22985.
- Evans, J. S. B. T. 2003. “In Two Minds: Dual-Process Accounts of Reasoning.” Trends in Cognitive Sciences 7 (10): 454–459. doi:https://doi.org/10.1016/j.tics.2003.08.012.
- 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:https://doi.org/10.3758/BRM.41.4.1149.
- Fishbein, M., and I. Ajzen. 1975. Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.
- Gianfrancesco, M. A., S. Tamang, J. Yazdany, and G. Schmajuk. 2018. “Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data.” JAMA Internal Medicine 178 (11): 1544–1547. doi:https://doi.org/10.1001/jamainternmed.2018.3763.
- Gino, F. 2008. “Do we Listen to Advice Just Because we Paid for It? The Impact of Advice Cost on Its Use.” Organizational Behavior and Human Decision Processes 107 (2): 234–245. doi:https://doi.org/10.1016/j.obhdp.2008.03.001.
- Gino, F., and D. A. Moore. 2007. “Effects of Task Difficulty on Use of Advice.” Journal of Behavioral Decision Making 20 (1): 21–35. doi:https://doi.org/10.1002/bdm.539.
- Gonzalez, L. F., G. A. Montes, E. Puig, S. Johnson, K. Mengersen, and K. J. Gaston. 2016. “Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.” Biochemical Pharmacology 24 (17): 1639–1641. doi:https://doi.org/10.3390/s16010097.
- Ji, L., Z. Wang, M. Chen, S. Fan, Y. Wang, and Z. Shen. 2019. “How Much Can ai Techniques Improve Surface Air Temperature Forecast? A Report from ai Challenger 2018 Global Weather Forecast Contest.” Journal of Meteorological Research 33 (5): 989–992. doi:https://doi.org/10.1007/s13351-019-9601-0.
- Jung, D., V. Dorner, C. Weinhardt, and H. Pusmaz. 2018. “Designing a Robo-Advisor for Risk-Averse, Low-Budget Consumers.” Electronic Markets 28 (3): 367–380. doi:https://doi.org/10.1007/s12525-017-0279-9.
- Kahneman, D., and G. Klein. 2009. “Conditions for Intuitive Expertise: A Failure to Disagree.” The American Psychologist 64 (6): 515–526. doi:https://doi.org/10.1037/a0016755.
- Kahneman, D., J. L. Knetsch, and R. H. Thaler. 1991. “The Endowment Effect, Loss Aversion, and Status Quo Bias.” Journal of Economic Perspectives 5 (1): 193–206. doi:https://doi.org/10.1257/jep.5.1.193.
- L’Orange Seigo, S.,. J. Arvai, S. Dohle, and M. Siegrist. 2014. “Predictors of Risk and Benefit Perception of Carbon Capture and Storage (CCS) in Regions with Different Stages of Deployment.” International Journal of Greenhouse Gas Control 25: 23–32.
- Leachman, S., and G. Merlino. 2017. “Medicine: The Final Frontier in Cancer Diagnosis.” Nature 542 (7639): 36–38. doi:https://doi.org/10.1038/nature21492.
- Lee, M. K. 2018. “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management.” Big Data & Society 5 (1): 205395171875668. doi:https://doi.org/10.1177/2053951718756684.
- Liu, P., R. Yang, and Z. Xu. 2019. “Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions.” Risk Analysis : An Official Publication of the Society for Risk Analysis 39 (2): 326–341. doi:https://doi.org/10.1111/risa.13143.
- Logg, J. M., J. A. Minson, and D. A. Moore. 2019. “Algorithm Appreciation: People Prefer Algorithmic to Human Judgment.” Organizational Behavior and Human Decision Processes 151: 90–103. doi:https://doi.org/10.1016/j.obhdp.2018.12.005.
- Longoni, C., A. Bonezzi, and C. K. Morewedge. 2019. “Resistance to Medical Artificial Intelligence.” Journal of Consumer Research 46 (4): 629–650. doi:https://doi.org/10.1093/jcr/ucz013.
- Longoni, C., and L. Cian. 2020. “Artificial Intelligence in Utilitarian vs. hedonic Contexts: The “Word-of-Machine” Effect.” Journal of Marketing. doi:https://doi.org/10.1177/0022242920957347
- Meehl, P. 1954. Clinical versus Statistical Prediction: A Theoretical Analysis and a Review of the Evidence. Minneapolis: University of Minnesota Press.
- Promberger, M., and J. Baron. 2006. “Do Patients Trust Computers?” Journal of Behavioral Decision Making 19 (5): 455–468. doi:https://doi.org/10.1002/bdm.542.
- Ratchford, M., and M. Barnhart. 2012. “Development and Validation of the Technology Adoption Propensity (TAP) Index.” Journal of Business Research 65 (8): 1209–1215. doi:https://doi.org/10.1016/j.jbusres.2011.07.001.
- Samuelson, P. A. 1938. “A Note on the Pure Theory of Consumer’s Behaviour.” Economica 5 (17): 61–71. doi:https://doi.org/10.2307/2548836.
- Segrè Cohen, A., N. G. Love, K. K. Nace, and J. Árvai. 2020. “ Consumers’ Acceptance of Agricultural Fertilizers Derived from Diverted and Recycled Human Urine.” Environmental Science & Technology 54 (8): 5297–5305. doi:https://doi.org/10.1021/acs.est.0c00576.
- Shank, D. B., A. DeSanti, and T. Maninger. 2019. “When Are Artificial Intelligence versus Human Agents Faulted for Wrongdoing? Moral Attributions after Individual and Joint Decisions.” Information, Communication & Society 22 (5): 648–663. doi:https://doi.org/10.1080/1369118X.2019.1568515.
- Siegrist, M., M.-E. Cousin, H. Kastenholz, and A. Wiek. 2007. “Public Acceptance of Nanotechnology Foods and Food Packaging: The Influence of Affect and Trust.” Appetite 49 (2): 459–466. doi:https://doi.org/10.1016/j.appet.2007.03.002.
- Sniezek, J. A., and T. Buckley. 1995. “Cueing and Cognitive Conflict in Judge-Advisor Decision Making.” Organizational Behavior and Human Decision Processes 62 (2): 159–174. doi:https://doi.org/10.1006/obhd.1995.1040.
- Wilson, R. S., and J. L. Arvai. 2006. “When Less is More: How Affect Influences Preferences When Comparing Low and High-Risk Options.” Journal of Risk Research 9 (2): 165–178. doi:https://doi.org/10.1080/13669870500419503.
- Wilson, R. S., and J. L. Arvai. 2010. “Why Less is More: Exploring Affect-Based Value Neglect.” Journal of Risk Research 13 (4): 399–409. doi:https://doi.org/10.1080/13669870902983171.
- Yaniv, I. 2004. “Receiving Other People’s Advice: Influence and Benefit.” Organizational Behavior and Human Decision Processes 93 (1): 1–13. doi:https://doi.org/10.1016/j.obhdp.2003.08.002.
- Yu, K.-H., A. L. Beam, and I. S. Kohane. 2018. “Artificial Intelligence in Healthcare.” Nature Biomedical Engineering 2 (10): 719–731. doi:https://doi.org/10.1038/s41551-018-0305-z.