Perception of Artificial Intelligence in Spain

doi:10.1016/j.tele.2021.101672

Telematics and Informatics

Volume 63, October 2021, 101672

https://doi.org/10.1016/j.tele.2021.101672 Get rights and content

Highlights

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Attitude forward Scientific discoveries and technological development.
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Perception of Artificial Intelligence and robots.
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A binary logit regression model.

Abstract

This paper analyses the perception of Artificial Intelligence (AI) by individuals in Spain and the factors associated with it. It uses data from 6308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results are that a gender gap is detected, and that people have a negative attitude if they are not interested in scientific discoveries and technological developments and if AI and robots are not useful at work.

Section snippets

Introduction.

In April 2018, the first European strategy for Artificial Intelligence (AI) was presented addressing opportunities and challenges of AI advances in the European Union (European Commission, 2018). The general idea is to promote the development and deployment of AI in the European Union countries but taking into account human and ethical implications of AI (von der Leyen, 2019).

The Commission’s White Paper (European Commission, 2020) expresses the many opportunities that AI can bring to Europe’s

Literature review

This section will cover previous literature related to what Artificial Intelligence is, the impact it has, as well as the perception of technological change linked to it.

Research methodology

This section contains the data that will be used for this study, as well as the methodology employed in this study. In the first part, the focus is on the data used, the data source and the description of the database. In the second part, the methodology used is explained.

Empirical results

This section presents the results of the binary logit and probit models of perception of Artificial Intelligence that have been developed. The estimated models explain the attitude (positive or negative) towards AI and robots of the respondents. Both binary regression models use as reference category that people have a positive attitude. Thus, the dependent variable was generated as a dummy variable that takes the value 1 if the attitude is positive or highly positive, and 0 otherwise.

Do not

Discussion

This paper analyses individuals' perception of AI in Spain and the factors associated with it. This is not the first time this topic has been analysed. Fast and Horvitz (2017) found that New Yorkers' perception of AI increased until 2009, but then changed. The main reason is that people are concerned about the negative impact of AI at work, and the loss of ethics and control of AI. In addition, they found that the perception of AI in healthcare and education for 30 years keeps growing. We

Conclusions

This paper analyses perception of AI of individuals in Spain and the factors associated with it. In short, to have the best attitude towards AI and robots, the individual must think that they are good for society (they help do jobs). The second point is to have a strong interest in scientific discoveries and technological developments. And finally, thinking that robots are really necessary for hard and dangerous jobs.

Conversely, a negative attitude will come from respondents who think that many

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

Funding: This work was supported by the private research project of Company MasMovil; the public research project of the Spanish Ministry of Economy, Universidad Carlos III de Madrid, and Competitiveness (MINECO), reference TEC2017-88048-C2-2-R; and Santander Financial Institute (SANFI) - UCEIF Foundation.

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View full text

Perception of Artificial Intelligence in Spain

Highlights

Abstract

Section snippets

Introduction.

Literature review

Research methodology

Empirical results

Discussion

Conclusions

Declaration of Competing Interest

Acknowledgements

J. High Technol. Manage. Res.

Lancet Digital Health

Telecommun. Policy

Struct. Change Econ. Dynam.

Int. J. Inf. Manage.

Telecommun. Policy

Comput. Law Sec. Rev.

Futures

Telematics Inform.

Telecommun. Policy

Qualitative response models: a survey

J. Econ. Literat.

Smart technology, artificial intelligence, robotics, and algorithms (STARA): Employees’ perceptions of our future workplace

J. Manage. Organ.