Beliefs and attitudes on automation and AI

Last registered on November 15, 2024

Pre-Trial

Trial Information

General Information

Title
Beliefs and attitudes on automation and AI
RCT ID
AEARCTR-0014322
Initial registration date
September 16, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 17, 2024, 1:56 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Last updated
November 15, 2024, 4:16 AM EST

Last updated is the most recent time when changes to the trial's registration were published.

Locations

Region
Region
Region

Primary Investigator

Affiliation
Link Campus University

Other Primary Investigator(s)

PI Affiliation
Free University of Bozen-Bolzano
PI Affiliation
Free University of Bozen-Bolzano
PI Affiliation
Rockwool Foundation
PI Affiliation
London School of Economics

Additional Trial Information

Status
Completed
Start date
2024-10-10
End date
2024-11-05
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Technological change has always been a very debated topic in economics. How Keynes described a future with less work in his letter to his grandchildren has been the object of many controversies over time. We are now experiencing a new wave of technological change, the so-called Robotization and Artificial Intelligence (AI) revolution, with likely stark consequences on productivity and the labour market.

Several studies have delved into the effects of automation and, more recently, artificial intelligence (AI) on the labor market, with findings suggesting a decrease in jobs, especially for low-skilled individuals due to automation, and a wider spectrum of job displacement potential with AI. However, the impact of these changes on attitudes towards technological advancements and political behaviors remains an open question.

Polling data from sources like the Pew Research Center and the Eurobarometer indicate that people generally support technological progress in principle. However, there is a prevalent fear that automation and AI will lead to widespread job loss in the near future, despite many individuals underestimating their own vulnerability to these changes. On the policy front, a partisan divide emerges, with Republicans often opposing increased welfare and taxation, while Democrats tend to advocate for such measures. Meanwhile, within the realm of political science, scholars such as Gallego and Kurer (2022) highlight an anticipated backlash from those negatively affected by technological advancements, even though the aggregate benefits may outweigh the costs. However, the extent of misperceptions surrounding recent technological changes remains poorly understood and warrants further investigation.

Preliminary evidence from political economy studies, such as those by Anelli, Colantone, and Stanig (2021), suggests that exposure to automation could lead to increased support for far-right populist parties, possibly fueled by nostalgia for a perceived golden age. However, more research is needed to elucidate the underlying mechanisms. Additionally, studies by Thewissen and Rueda (2017), Jeffrey (2021), and Van Hoon (2022) shed light on the relationship between automation exposure and preferences for redistribution policies, with mixed findings suggesting a nuanced dynamic, with preferences for redistribution higher for people with higher education, and in situations with a starker rhetoric on unfairness.

Our survey experiment aims to delve deeper into the extent of public misperceptions regarding automation and AI, exploring how different perceptions may shape policy preferences and potentially mobilize voters across three countries—the US, Germany, and Italy. These countries exhibit varying degrees of automation adoption and distinct labor market characteristics, providing a rich context for comparative analysis.
External Link(s)

Registration Citation

Citation
Battiston, Giacomo et al. 2024. "Beliefs and attitudes on automation and AI." AEA RCT Registry. November 15. https://doi.org/10.1257/rct.14322-1.3
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Each individuals will see a political statement encompassing a specific vision on automation and AI, except the pure control group.
Intervention (Hidden)
Each individuals will see a political statement encompassing a specific vision on automation and AI except the pure control group.
Here are the messages:

Techno-optimist

Ladies and Gentlemen, Fellow Citizens,
The advancement of automation and artificial intelligence will lead to a better future. Productivity will increase and new jobs will be created. The automation of routine tasks will allow workers to focus on what truly matters—on the meaningful, creative, innovative part of their jobs. The economy will expand increasing opportunities for everyone.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to ensure that the march of technology is not stopped because of misplaced fears. We will implement policies that promote automation and artificial intelligence and ensure we are at the cutting edge of technological progress.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.

Techno-pessimist

Ladies and Gentlemen, Fellow Citizens,
The advancement of automation and artificial intelligence will lead to a worse future. Certain occupations will become outdated, leading to a worrying decline in available employment opportunities, worse working conditions and lower wages. Benefits will be increasingly concentrated in the hands of tech tycoons.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to ensure that the march of technology does not trample on the livelihoods of our citizens. We will implement policies that protect workers from the advancement of automation and artificial intelligence and foster a fair and just transition.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.

Balanced

Ladies and Gentlemen, Fellow Citizens,
The impact of automation and artificial intelligence is uncertain. On one hand, advancements promise to enhance productivity, create new jobs and free workers from the repetitive tasks. On the other hand, these changes will potentially lead to job loss and a lower quality of remaining jobs, with most benefits concentrated in the hands of tech tycoons.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to navigate this uncertain terrain with thoughtful interventions. We will implement balanced policies that, on one hand, promote automation and artificial intelligence, but, on the other hand, protect workers from these advancements and foster a fair and just transition.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.
Intervention Start Date
2024-10-10
Intervention End Date
2024-11-05

Primary Outcomes

Primary Outcomes (end points)
In part 1, several beliefs related to automation and AI:

a) the number of robots in their country, the country that has or has recently installed more robots, the industrial sector where these robots were mostly installed both worldwide and in their country, how AI works (incentivized);
b) number of jobs robots have taken out or created;
c) number of jobs that will be lost or created because of AI, both in the aggregate and by skill requirements of the jobs;
d) opinions on how robots and AI may influence the job market.

In part 2, several policy preferences and the willingness to politically mobilize on the topic:

a) if policy-makers should intervene on automation and AI, and why;
b) several policy preferences, like minimum wage, stronger regulations, universal income, breaking up big tech monopolies, education policies, lower taxes on labour, tax credits for innovation, taxing robots, unemployment benefits;
c) willingness to publicly support a statement on automation and AI, either balanced, optimistic or pessimistic

From Change.org, we will record the number of signatures per petition.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
In part 2, we will also consider:

a) chances of losing one's job in the next 5 years because of automation or AI;
b) trust in several institutions, as the government, political parties, trade unions and tech tycoons.

From Change.org, we will try to link each signature to a questionnaire by looking at the timing of the signature and the completion time of the questionnaires.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Part 1: misperceptions on automation and AI

After having collected basic information on demographics and voting intentions, we will acquire two crucial pieces of information: the occupation of the respondent and the industry were he works in. In this way we will be able to assess the exposure of his current or past job to automation. Furthermore, in our empirical analysis, by combining this information with other demographic and social characteristics, we will be able to instrument the current exposure with the expected one by using the approach in Anelli, Colantone and Stanig (2021).

Another relevant part of the introductory questionnaire will collect information on cultural worldviews, so to be able to classify individuals in terms of cultural types between individualist/collectivist and authoritative/liberal using the cultural cognition questionnaire (Kahan et al., 2013).

After having acquired this background information, we will elicit several beliefs related to automation and AI (outcomes a)-c)). Questions a) will be incentivized, as participants will get a bonus fee of $0.50 if they are able to correctly guess the answer to a randomly picked question among those in a). The correct answers will be based on the Institute for Robots statistics for 2022. At the end of this part, we will have open question d) on the respondent’s opinion on the impact of automation and AI on the labour market.

Part 2:

In this part, we explore the influence that visions on technology have on policy preferences and the willingness to mobilize in support of these preferences.

We introduce at the beginning of this part the political statement encompassing a specific vision on automation and AI. The facts within the articles will not change, but the predicted outcomes of automation and AI and the suggested policies will differ between a “techno-optimist”, “techno-pessimist” and a “balanced” spin. Each participant will only see one statement, except for the baseline where no statement is shown. The statements will be followed by control questions to ensure the participants have read and understood the statement.

Later, we will elicit policy preferences. They will be elicited with a) a question on if policy-makers should intervene on automation and AI together with an open question asking for arguments to justify the previous choice, b) radio buttons on the preferred policies among a list of policies from Johnson and Acemoglu (2023). The subsequent part will be on political mobilization, as respondents will be asked to sign an online petition on Change.org. They can choose one out of three petitions based on the statements or not to publicly support any petition.

At the end, we will have a final questionnaire where we will elicit the chances of losing one's own job, additional demographic and socio-economic information, trust in several institutions, risk attitudes, feelings towards technology, information on the personal use of technology. After the survey is over, respondents will be shown a link to the petition on Change.org that they declared they were willing to sign.
Experimental Design Details
We introduce at the beginning of this part the political statement encompassing a specific vision on automation and AI. The role of technological visions in fostering innovation policies has been widely discussed (Gordon, 2016, Johnson and Acemoglu, 2023). The so-called “techno-optimist” visions try to induce people in believing that technological change is always good for jobs. Computer inventors/entrepreneurs like Bill Gates, Steve Jobs and Mark Zuckenberg may all be counted within this group of people together with high tech businessmen like Elon Musk. “Techno-pessimists” visions argue that automation and AI will in the short-run always take out jobs and that adjustment will be painful, partly because of the low productivity-enhancing effect of these technologies. An intermediate stream of thought claims that there are trade-offs related to the impact of automation and AI on the labour market and that the final outcome will ultimately depend on government policies, if they will lead to better applied technologies complementary to human work or crappy ones that only marginally increase productivity compared to human work and mostly substitute for it. Among these “balanced” economists, we can today count Daron Acemoglu and David Autor. Our manipulation will consist in presenting three political statements to our participants. The facts within the articles will not change, but the predicted outcomes of automation and AI and the suggested policies will differ between a “techno-optimist”, “techno-pessimist” and a “balanced” spin.

Here are the messages:

Techno-optimist

Ladies and Gentlemen, Fellow Citizens,
The advancement of automation and artificial intelligence will lead to a better future. Productivity will increase and new jobs will be created. The automation of routine tasks will allow workers to focus on what truly matters—on the meaningful, creative, innovative part of their jobs. The economy will expand increasing opportunities for everyone.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to ensure that the march of technology is not stopped because of misplaced fears. We will implement policies that promote automation and artificial intelligence and ensure we are at the cutting edge of technological progress.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.

Techno-pessimist

Ladies and Gentlemen, Fellow Citizens,
The advancement of automation and artificial intelligence will lead to a worse future. Certain occupations will become outdated, leading to a worrying decline in available employment opportunities, worse working conditions and lower wages. Benefits will be increasingly concentrated in the hands of tech tycoons.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to ensure that the march of technology does not trample on the livelihoods of our citizens. We will implement policies that protect workers from the advancement of automation and artificial intelligence and foster a fair and just transition.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.

Balanced

Ladies and Gentlemen, Fellow Citizens,
The impact of automation and artificial intelligence is uncertain. On one hand, advancements promise to enhance productivity, create new jobs and free workers from the repetitive tasks. On the other hand, these changes will potentially lead to job loss and a lower quality of remaining jobs, with most benefits concentrated in the hands of tech tycoons.

Our response to this challenge will define the character of our nation for generations to come. My commitment to you is to navigate this uncertain terrain with thoughtful interventions. We will implement balanced policies that, on one hand, promote automation and artificial intelligence, but, on the other hand, protect workers from these advancements and foster a fair and just transition.

Our goal is clear: a future where every American can thrive in an economy that is as humane as it is advanced.
Randomization Method
Randomization is implemented with a double-blind procedure. In our oTree code, each row of the dataset corresponds to a different treatment in sequential and repeated order (baseline, balanced, optimistic, pessimistic) without the recruiting company Cint being allowed to see the dataset. Respondents are recruited and re-directed to the website by Cint to fill a row of the dataset without any control by us.
Randomization Unit
Respondent
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
11,600 individuals across the three countries (US, Germany and Italy) recruited through Cint, representing a representative sample of these countries in terms of age, education and gender
Sample size: planned number of observations
11,600 individuals
Sample size (or number of clusters) by treatment arms
2,900 individuals by treatment arm: 2,900 baseline, 2,900 balanced, 2,900 pessimistic, 2,900 optimistic
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Ethical Commission of the Free University of Bozen-Bolzano
IRB Approval Date
2024-03-13
IRB Approval Number
N/A
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials