• No results found

AI creates opportunities for the more traditional financial organizations by increasing their performance, being more efficient and cutting costs. Therefore, AI has become more and more useful for financial institutions to implement in their organization. The expectation is that the development of new AI systems will increase even more rapidly. Fintech organizations already adopt AI within their whole organizational structure. This could be a threat for the more traditional financial organizations. Therefore, financial organizations should follow these trends and know how they can adopt AI within the whole organization.

With this study we have aimed to provide an understanding of the effects of adopting AI within the financial industry. The existing TAM model was extended with the variable’s knowledge about AI, perceived risk and perceived trust. More in depth, we researched the effects of AI knowledge in combination with the perceived risk on the acceptance of AI-driven decision systems within the financial industry.

A fundamental assumption when starting this study, was the proven concept of the relationship between perceived usefulness and the behavioural intention to use an AI system (Davis 1989). The results of this study, also have shown that perceived usefulness has a significant positive direct effect on the behavioural intention to use an AI system. Moreover, the variable knowledge about AI was added in this research, and the results of this study show that there is significant positive direct effect between knowledge about AI and the behavioural intention to use an AI system. This is interesting for financial organizations, because by increasing the knowledge of AI by their employees, their intention to use AI systems will also increase.

Besides the variable knowledge about AI, also the perceived risk and perceived trust were added to the model. The main goal was to find out if perceived risk or perceived trust would have an effect on an existing relationship in the TAM model. The results show that perceived risk and perceived trust do have a minor influence on the relationship between knowledge about AI and perceived usefulness. This is interesting for financial organizations, because by managing these risks and eliminating the perceived risk and perceived trust levels by their employees, they can increase the employees’ level of the perceived usefulness of AI systems. We also found the effect that employees who have a lower level of perceived risk, will also have a higher level of perceived trust. This is in line with earlier studies about the perceived risk and trust in relation to the acceptance of an AI system.

In contrast, these variables do not directly influence the relationship between knowledge about AI and the behavioural intention to use an AI system. Further research about the acceptance of AI systems could conduct an experimental design to discover other insights in the employee’s factors for accepting AI systems. Also, to expand the research about the TAM model in relation to the acceptance of AI systems, future research could focus on expanding this study to other industries or countries.

There is an opportunity for financial organizations to expand their performance by starting with scaling their AI activities. They can do that by increasing the employee’s knowledge about AI in combination with informing them about the risks and eliminating uncertainty.

7. References

Ajibade, Patrick, (2018). "Technology Acceptance Model Limitations and Criticisms:

Exploring the Practical Applications and Use in Technology-related Studies, Mixed-method, and Qualitative Researches" Library Philosophy and Practice (e-journal), 2018.

Bagozzi, R. (2007). The legacy of the Technology Acceptance Model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8 (4), 244-254.

Boston Consulting Group, (2017). Most Companies Have Big Gaps Between AI Ambition and Execution. Retrieved from BCG website:

https://www.bcg.com/d/press/6september2017-gapbetween-ai-ambition-execution-169791.

Burgess, A. (2018). The Executive Guide to Artificial Intelligence: How to identify and implement applications for AI in your organization. https://doi.org/10.1007/978-3-319- 63820-1.

Canhoto, A.I & Clear, F. (2020). Artificial intelligence and machine learning as business tools: A framework for diagnosing value destruction potential, Business Horizons, Volume 63, Issue 2, 2020, Pages 183-193.

Choi, H., Kim, Y., & Kim, J. (2010). An acceptance model for an internet protocol television service in korea with prior experience as a moderator. The Service Industries Journal, 30 (11), 1883–1901.

Choo, C. W. (1991). Towards an information model of organizations. The Canadian Journal of Information Science, 16(3), 32–62.

Colson, E. (2019). What AI-driven decision making looks like. Harvard Business Review.

Cubric, Marija. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study,Technology in Society,Volume 62, 2020, 101257, ISSN 0160-791X, https://doi.org/10.1016/j.techsoc.2020.101257.

Dane, E., Rockmann, K. W., & Pratt, M. G. (2012). When should I trust my gut? Linking domain expertise to intuitive decision-making effectiveness. Organizational Behavior

and Human Decision Processes, 119(2), 187–194.

https://doi.org/10.1016/j.obhdp.2012.07.009.

Davenport, T. H., & Bean, R. (2017). How P&G and American Express are approaching AI.

Harvard Business Review. Available at https://hbr.org/2017/03/how-pgand-american-express-are-approaching-a.

Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results (Doctoral dissertation). MIT Sloan School of Management, Cambridge, MA.

Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13 (3), 319-340.

Eastwood, J., Luther, K. (2016). What You Should Want From Your Professional: The Impact of Educational Information on People’s Attitudes Toward Simple Actuarial Tools. Professional Psychology: Research and Practice, 47(6), 402-412.

Featherman M., and Fuller M., (2003). "Applying TAM to e-services adoption: the

moderating role of perceived risk," 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the, 2003, pp. 11 pp.-, doi:

10.1109/HICSS.2003.1174433.

Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. 5th Edition. London, UK:

SAGE.

Finlay, S. (2018). Artificial Intelligence and Machine Learning for Business. 3rd Edition. GB, Relativistic.

Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Researched. Reading: Addison-Wesley.

Fountaine, T., McCarthy B., Saleh, T. (2019) Building the AI-Powered Organization. Harvard Business Review, 97 (4), 62-73.

Frischmann, B., Selinger, E. (2017, September 25). Robots have already taken over our work, but they’re made of flesh and bone. The Guardian. Available at

https://www.theguardian.com/commentisfree/2017/sep/25/robots-taken-overwork-Gaines-Ross, L. (2016). What do people–not techies, not companies–think about artificial intelligence. Harvard Business Review, 24.

Gefen, D. and Straub, D. (1997), ‘‘Gender differences in the perception and use of e-mail: an extension to the technology acceptance model’’, MIS Quarterly, Vol. 21 No. 4, pp.

389-400.

Güngör, H. (2020). Creating Value with Artificial Intelligence: A Multi-stakeholder Perspective. Journal of Creating Value, 6(1), 72–85.

https://doi.org/10.1177/2394964320921071.

Gordon, M. J. (1991). A review of the validity and accuracy of self-assessments in health professions training. Academic Medicine, 66 (12), 762-9.

Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis:

A regression-based approach (2nd edition). New York: The Guilford Press.

Hayes, A. F. (2021). PROCESS v4.0.

Hoeffler, S. (2003). Measuring Preferences for Really New Products. Journal of Marketing Research, 40(4), 406–420. https://doi.org/10.1509/jmkr.40.4.406.19394.

Huck, Johnson, Kiritz and Larson (2020). "Why AI Governance Matters." The RMA Journal, vol. 102, no. 8, May 2020, p. 18. Gale General OneFile. Available at:

https://rmajournal.org/rmajournal/may_2020/MobilePagedArticle.action?articleId=15 83558#articleId1583558.

IBM, (2020). What is artificial intelligence? https://www.ibm.com/cloud/learn/what-is-artificial-intelligence.

Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586.

https://doi.org/10.1016/j.bushor.2018.03.007.

Kaplan, A., Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62, 15-25.

Kitsela, Vladyslav (2021). AI in Fintech: How to prepare for a massive shift in financial

Lee, H. J. (2004). The role of competence-based trust and organizational identification in continuous improvement. Journal of Managerial Psychology.

Logg, J. M., Minson J. A., Moore D.A., (2019). Algorithm appreciation: People prefer algorithmic to human judgment, Organizational Behavior and Human Decision Processes, Volume 151, 2019, Pages 90-103.

Lui, A., & Lamb, G. W. (2018). Artificial intelligence and augmented intelligence

collaboration: regaining trust and confidence in the financial sector. Information &

Communications Technology Law, 27(3), 267-283.

Marler, J. H., Fisher, S. L., & Ke, W. (2009). Employee self-service technology acceptance:

A comparison of pre-implementation and post-implementation relationships.

Personnel Psychology, 62 (2), 327–358.

McCarthy, John. (2004). What is Artificial Intelligence? Computer Science Department Stanford University Stanford, CA 94305 jmc@cs.stanford.edu http://www-formal.stanford.edu/jmc/ 2004 Nov 24, 7:56 p.m. Revised November 24, 2004.

McKinsey, (2018). Platform operating model for the AI bank of the future. McKinsey Analystics. Available at https://www.mckinsey.com/industries/financial-services/our-insights/platform-operating-model-for-the-ai-bank-of-the-future.

McKinsey, (2020). AI-bank of the future: Can banks meet the AI challenge? McKinsey Analytics. Available at https://www.mckinsey.com/industries/financial-services/our-insights/ai-bank-of-the-future-can-banks-meet-the-ai-challenge.

Mitchell, V.-W. (1999). Consumer perceived risk: conceptualisations and models. European Journal of marketing.

Nelson, Richard R. and Sidney G. Winter (1982), An Evolutionary Theory of Economic Change, Cambridge, MA: Belknap Press, Harvard University Press.

Nicolaou, A. I., & McKnight, D. H. (2006). Perceived Information Quality in Data Exchanges: Effects on Risk, Trust, and Intention to Use. Information Systems Research, 17(4), 332-35l.

NVB, 2020. Digitalisering, innovatie & technologie. Available at

NVB, 2021. Factsheet werkgeversschap. Available at

https://www.bankinbeeld.nl/app/uploads/2018/07/NVB-Factsheet-Werkgeverschap-januari-2021.pdf.

Ostlund, Lyman E. (1974), Perceived Innovation Attributes as Predictors of

Innovativeness, Journal of Consumer Research, Volume 1, Issue 2, September 1974, Pages 23–29, https://doi.org/10.1086/208587.

Pavlou, P.A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal Electronic Commerce, 7 (3) (2003), pp. 69-103.

Pelau, C., Dabija, D.-C., & Ene, I. (2021). What makes an AI device human-like? The role of interaction quality, empathy and perceived psychological anthropomorphic

characteristics in the acceptance of artificial intelligence in the service industry. Computers in Human Behavior, 122, 106855–.

https://doi.org/10.1016/j.chb.2021.106855.

Pennington, R., Wilcox, H. D., & Grover, V. (2003). The role of system trust in business-to-consumer transactions. Journal of management information systems, 20(3), 197-226.

Rogers, E.M. (2003) Diffusion of innovations. (5th ed.), Free Press, New York, NY.

Salas, E., Rosen, M. A., & DiazGranados, D. (2010). Expertise-based intuition and decision making in organizations. Journal of Management, 36(4), 941–973.

https://doi.org/10.1177/0149206309350084

Saade, R. and Bahli, B. (2005), ‘‘The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology

acceptance model’’, Information Management, Vol. 42, pp. 317-27.

Schwarz, A., Junglas, I. A., Krotov, V., & Chin, W. W. (2004). Exploring the role of

experience and compatibility in using mobile technologies. Information Systems and e-Business Management, 2(4), 337-356.

Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66-83.

Simon, O., Neuhofer, B., & Egger, R. (2020). Human-robot interaction: Conceptualising trust in frontline teams through LEGO® Serious Play®. Tourism management

perspectives, 35, 100692.

Sitkin, S. B., L. R. Weingart. 1995. Determinants of risky decision-making behavior: A test of the mediating role of risk perceptions and propensity. Acad. Management J. 38 1573-1592.

Slovic, P. (1987). Perception of risk. Science 236, 280-285.

Teece, D., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility:

Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13-35.

Thong, J. Y. (1999). An integrated model of information systems adoption in small businesses. Journal of management information systems, 15(4), 187-214.

Venkatesh, Viswanath & Davis, Fred. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science. 46. 186-204. 10.1287/mnsc.46.2.186.11926.

Zekos G.I. (2021) Risk Management Developments. In: Economics and Law of Artificial Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-64254-9_5.

8. Appendix: Questionnaire

The Acceptance of Artificial Intelligence

Start of Block: INTRODUCTION BLOCK

INTRODUCTION Thank you for your participation in this research.

This online survey is part of my master's thesis graduation research on the acceptance of Artificial Intelligence (AI), a case study within the financial industry. I would like to know if you have any experiences with Artificial Intelligence. Do you already use it? Do you see any risks? Do you trust it?

On average, this survey takes you 5 minutes to complete. Your responses are completely anonymous.

Chantal Donkervoort

Executive Program Management Studies

Amsterdam Business School, University of Amsterdam (UvA)

End of Block: INTRODUCTION BLOCK

Start of Block: General Questions What is your age?

o

< 25 years old (1)

o

25-34 years old (2)

o

35-44 years old (3)

o

45-54 years old (4)

o

> 55 years old (5) What is your gender?

o

Female (1)

o

Male (2)

o

I rather not say (3)

What is the highest degree or level of school you have completed? If currently enrolled, what is your highest degree received?

o

High school or the equivalent (1)

o

Secondary vocational education (2)

o

Bachelor's degree (3)

o

Master's degree (4)

o

Candidate/PhD (5)

For which organization do you work?

________________________________________________________________

What is your job function within your organization?

________________________________________________________________

End of Block: General Questions Start of Block: Knowledge about AI

Have you ever worked with an AI system before, either in your current job or before?

o

Yes (1)

o

No (2)

o

I do not know (3)

16 In your opinion, how much knowledge do you have of Artificial Intelligence? (0= don't know anything about AI, 10 = know a lot about AI)

o

0 (0)

o

1 (1)

o

2 (2)

o

3 (3)

o

4 (4)

o

5 (5)

o

6 (6)

o

7 (7)

o

8 (8)

o

9 (9)

o

10 (10)

End of Block: Knowledge about AI Start of Block: AI knowledge

When was the term “Artificial Intelligence” founded?

o

1930s (1)

o

1960s (2)

o

1990s (3)

o

2000s (4)

Which key technology is behind Artificial Intelligence?

o

Machine Learning (1)

o

Electric battery (2)

o

Robotics (3)

o

Blockchain (4)

How is Artificial Intelligence developed further and how are errors in the AI system corrected?

o

Through a faster internet conncection (1)

o

A further development is not possible with these systems, since they are ready-made programs (2)

o

Through higher storage capacities of the computers (3)

o

By learning: By the user giving feedback and making corrections to the AI (4)

What types of Artificial Intelligence are there?

o

Supervised, Unsupervised and Reinforcement Learning (1)

o

Monitored, Unsupervised and Signal Learning (2)

o

Signal Learning, Concept Learning and Rule Learning (3)

o

Reinforcement Learning, Unsupervised Learning and Signal Learning (4)

Which method is used by Reinforcement Learning in order to independently find solutions for defined problems?

o

Trial and error method to maximize punishment (1)

o

Trial and error method to maximize rewards (2)

o

Trial and error method to maximize error messages (3)

o

Trial and error method to minimize rewards (4)

In which of the following areas does the use of Artificial Intelligence result in an added value for society?

o

Traffic (1)

o

Medicine (2)

o

Finance (3)

o

All of the above (4)

Which of the following tasks could most likely be performed by Artificial Intelligence?

o

The personal implementation of consultation appointments with doctors (1)

o

The complete replacement of a doctor in the treatment of patients (2)

o

The analysis of X-ray images, for example to detect a torn meniscus or a tumor (3)

o

The implementation of psychotherapies (4)

Which of the following aspects is essential to ensure a sustainable and safe application of Artificial Intelligence?

o

The use of AI must be in line with social values and laws such as ethics and data protection (1)

o

The use of AI must be ensured by more cars for autonomous driving protection (2)

o

The use of AI must be ensured through more memory and performance capacities on smartphones and computers (3)

o

The use of AI requires a better understanding and more openness of the population towards the application of Artificial Intelligence (4)

Which of the following points is often referred to by society as a risk of Artificial Intelligence?

o

Climate Change (1)

o

New diseases (2)

o

Job losses (3)

o

Political trust (4)

Which of the following attributes can currently not be mapped by Artificial Intelligence?

o

Intuition (1)

o

Creativity (2)

o

Empathy (3)

o

All of the above (4) End of Block: AI knowledge Start of Block: Perceived usefulness

The following statements will indicate how useful Artificial Intelligent systems would be in your professional life.

Strongly disagree (1)

Somewhat disagree (2)

Neither agree nor disagree

(3)

Somewhat agree (4)

Strongly agree (5) Using (the

output of) AI systems would

enhance my effectiveness in

my job (1)

o o o o o

Using (the output of) AI systems would improve my job

performance (2)

o o o o o

Using (the output of) AI systems would

increase my

productivity (3)

o o o o o

I would find (the output of)

AI systems useful in my

work (4)

o o o o o

Assuming I have access to (the output of) AI systems I

would use it (5)

o o o o o

Given that I have access to (the output of) AI systems I predict I would

be using it (6)

o o o o o

End of Block: Perceived usefulness Start of Block: Trust

The following statements will indicate if you trust the use of Artificial Intelligent systems in your professional life.

strongly disagree (1)

Somewhat disagree (2)

Neither agree nor disagree

(3)

Somewhat agree (4)

Strongly agree (5) I trust that (the

output of) AI systems could be handled

safely (1)

o o o o o

I consider (the output of) AI

systems as

trustworthy (2)

o o o o o

I consider (the output of) AI

systems as

competent (3)

o o o o o

I consider (the output of) AI

systems as

reliable (4)

o o o o o

End of Block: Trust

Start of Block: Perceived Risk

The following statements will indicate how you perceive the risk of using Artificial Intelligent systems in your professional life.

Strongly disagree (1)

somewhat disagree (2)

neither agree nor disagree

(3)

Somewhat agree (4)

Strongly agree (5) I perceive a

considerable risk involved in

using (the output of) AI systems for my

job (1)

o o o o o

There is a high potential for loss involved if I use (the output

of) AI systems for my job (2)

o o o o o

My decision to participate in the use of (the output of) AI systems is risky

(3)

o o o o o

End of Block: Perceived Risk Start of Block: Attitude towards AI

The following statements are related to the attitude towards AI systems in your professional life.

Strongly

disagree (1) Somewhat disagree (2)

Neither agree nor disagree

(3)

Somewhat

agree (4) Strongly agree (5) I am interested

in using artificially intelligent systems in my

daily life (1)

o o o o o

There are many beneficial applications of

Artificial

Intelligence (2)

o o o o o

Artificial Intelligence is

exciting (3)

o o o o o

Artificial Intelligence can

provide new economic opportunities for this country

(4)

o o o o o

I would like to use Artificial Intelligence in

my own job (5)

o o o o o

An artificially intelligent agent would be better

than an employee in many routine

jobs (6)

o o o o o

I am impressed by what Artificial Intelligence can

do (7)

o o o o o

Artificial Intelligence can

have positive impacts on

people’s wellbeing (8)

o o o o o

Artificially intelligent systems can help people feel

happier (9)

o o o o o

Artificially intelligent systems can perform better

than humans (10)

o o o o o

Much of society will benefit from a future full of Artificial

Intelligence (11)

o o o o o

For routine transactions, I

would rather interact with an

artificially intelligent system than with a human

(12)

o o o o o

The following statements are related to the attitude towards AI systems in your professional life.

Strongly disagree (1)

Somewhat disagree (2)

Neither agree nor disagree

(3)

Somewhat agree (4)

Strongly agree (5) I think Artificial

Intelligence is

dangerous (1)

o o o o o

Organizations use Artificial Intelligence

unethically (2)

o o o o o

I find Artificial Intelligence

sinister (3)

o o o o o

Artificial Intelligence is used to spy on

people (4)

o o o o o

I shiver with discomfort when I think about future

uses of Artificial Intelligence (5)

o o o o o

Artificial Intelligence

might take control of

people (6)

o o o o o

I think artificially intelligent systems make

many errors (7)

o o o o o

People like me will suffer if

Artificial Intelligence is used more and more (8)

o o o o o

End of Block: Attitude towards AI Start of Block: Behaviour Use

GERELATEERDE DOCUMENTEN