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<!DOCTYPE html>
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<title>5 Trend across time: attitudes toward workplace automation | Artificial Intelligence: American Attitudes and Trends</title>
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<meta name="twitter:title" content="5 Trend across time: attitudes toward workplace automation | Artificial Intelligence: American Attitudes and Trends" />
<meta name="author" content="Baobao Zhang and Allan Dafoe" />
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<li><img src="images/small_logo.png" alt="Report small logo" width="272px" hspace="12" vspace="12"/></li>
<li><a href="index.html"><b>Table of Contents</b></a></li>
<li class="divider"></li>
<li class="chapter" data-level="1" data-path="executive-summary.html"><a href="executive-summary.html"><i class="fa fa-check"></i><b>1</b> Executive summary</a><ul>
<li class="chapter" data-level="1.1" data-path="executive-summary.html"><a href="executive-summary.html#select-results"><i class="fa fa-check"></i><b>1.1</b> Select results</a></li>
<li class="chapter" data-level="1.2" data-path="executive-summary.html"><a href="executive-summary.html#reading-notes"><i class="fa fa-check"></i><b>1.2</b> Reading notes</a></li>
<li class="chapter" data-level="1.3" data-path="executive-summary.html"><a href="executive-summary.html#press-coverage"><i class="fa fa-check"></i><b>1.3</b> Press coverage</a></li>
</ul></li>
<li class="chapter" data-level="2" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html"><i class="fa fa-check"></i><b>2</b> General attitudes toward AI</a><ul>
<li class="chapter" data-level="2.1" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html#subsecsupportai"><i class="fa fa-check"></i><b>2.1</b> More Americans support than oppose developing AI</a></li>
<li class="chapter" data-level="2.2" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html#subsecdemosupportai"><i class="fa fa-check"></i><b>2.2</b> Support for developing AI is greater among those who are wealthy, educated, male, or have experience with technology</a></li>
<li class="chapter" data-level="2.3" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html#subsecsupportmanageai"><i class="fa fa-check"></i><b>2.3</b> An overwhelming majority of Americans think that AI and robots should be carefully managed</a></li>
<li class="chapter" data-level="2.4" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html#harmful-consequences-of-ai-in-the-context-of-other-global-risks"><i class="fa fa-check"></i><b>2.4</b> Harmful consequences of AI in the context of other global risks</a></li>
<li class="chapter" data-level="2.5" data-path="general-attitudes-toward-ai.html"><a href="general-attitudes-toward-ai.html#americans-understanding-of-key-technology-terms"><i class="fa fa-check"></i><b>2.5</b> Americans’ understanding of key technology terms</a></li>
</ul></li>
<li class="chapter" data-level="3" data-path="public-opinion-on-ai-governance.html"><a href="public-opinion-on-ai-governance.html"><i class="fa fa-check"></i><b>3</b> Public opinion on AI governance</a><ul>
<li class="chapter" data-level="3.1" data-path="public-opinion-on-ai-governance.html"><a href="public-opinion-on-ai-governance.html#subsecgovchallenges13"><i class="fa fa-check"></i><b>3.1</b> Americans consider many AI governance challenges to be important; prioritize data privacy and preventing AI-enhanced cyber attacks, surveillance, and digital manipulation</a></li>
<li class="chapter" data-level="3.2" data-path="public-opinion-on-ai-governance.html"><a href="public-opinion-on-ai-governance.html#americans-who-are-younger-who-have-cs-or-engineering-degrees-express-less-concern-about-ai-governance-challenges"><i class="fa fa-check"></i><b>3.2</b> Americans who are younger, who have CS or engineering degrees express less concern about AI governance challenges</a></li>
<li class="chapter" data-level="3.3" data-path="public-opinion-on-ai-governance.html"><a href="public-opinion-on-ai-governance.html#americans-place-the-most-trust-in-the-u.s.-military-and-universities-to-build-ai-trust-tech-companies-and-non-governmental-organizations-more-than-the-government-to-manage-the-technology"><i class="fa fa-check"></i><b>3.3</b> Americans place the most trust in the U.S. military and universities to build AI; trust tech companies and non-governmental organizations more than the government to manage the technology</a></li>
</ul></li>
<li class="chapter" data-level="4" data-path="ai-policy-and-u-s-china-relations.html"><a href="ai-policy-and-u-s-china-relations.html"><i class="fa fa-check"></i><b>4</b> AI policy and U.S.-China relations</a><ul>
<li class="chapter" data-level="4.1" data-path="ai-policy-and-u-s-china-relations.html"><a href="ai-policy-and-u-s-china-relations.html#americans-underestimate-the-u.s.-and-chinas-ai-research-and-development"><i class="fa fa-check"></i><b>4.1</b> Americans underestimate the U.S. and China’s AI research and development</a></li>
<li class="chapter" data-level="4.2" data-path="ai-policy-and-u-s-china-relations.html"><a href="ai-policy-and-u-s-china-relations.html#subsecexperimentchina"><i class="fa fa-check"></i><b>4.2</b> Communicating the dangers of a U.S.-China arms race requires explaining policy trade-offs</a></li>
<li class="chapter" data-level="4.3" data-path="ai-policy-and-u-s-china-relations.html"><a href="ai-policy-and-u-s-china-relations.html#americans-see-the-potential-for-u.s.-china-cooperation-on-some-ai-governance-challenges"><i class="fa fa-check"></i><b>4.3</b> Americans see the potential for U.S.-China cooperation on some AI governance challenges</a></li>
</ul></li>
<li class="chapter" data-level="5" data-path="trend-across-time-attitudes-toward-workplace-automation.html"><a href="trend-across-time-attitudes-toward-workplace-automation.html"><i class="fa fa-check"></i><b>5</b> Trend across time: attitudes toward workplace automation</a><ul>
<li class="chapter" data-level="5.1" data-path="trend-across-time-attitudes-toward-workplace-automation.html"><a href="trend-across-time-attitudes-toward-workplace-automation.html#americans-do-not-think-that-labor-market-disruptions-will-increase-with-time"><i class="fa fa-check"></i><b>5.1</b> Americans do not think that labor market disruptions will increase with time</a></li>
<li class="chapter" data-level="5.2" data-path="trend-across-time-attitudes-toward-workplace-automation.html"><a href="trend-across-time-attitudes-toward-workplace-automation.html#extending-the-historical-time-trend"><i class="fa fa-check"></i><b>5.2</b> Extending the historical time trend</a></li>
</ul></li>
<li class="chapter" data-level="6" data-path="high-level-machine-intelligence.html"><a href="high-level-machine-intelligence.html"><i class="fa fa-check"></i><b>6</b> High-level machine intelligence</a><ul>
<li class="chapter" data-level="6.1" data-path="high-level-machine-intelligence.html"><a href="high-level-machine-intelligence.html#arrivesooner"><i class="fa fa-check"></i><b>6.1</b> The public predicts a 54% likelihood of high-level machine intelligence within 10 years</a></li>
<li class="chapter" data-level="6.2" data-path="high-level-machine-intelligence.html"><a href="high-level-machine-intelligence.html#subsecsupporthlmi"><i class="fa fa-check"></i><b>6.2</b> Americans express mixed support for developing high-level machine intelligence</a></li>
<li class="chapter" data-level="6.3" data-path="high-level-machine-intelligence.html"><a href="high-level-machine-intelligence.html#subsecdemohlmi"><i class="fa fa-check"></i><b>6.3</b> High-income Americans, men, and those with tech experience express greater support for high-level machine intelligence</a></li>
<li class="chapter" data-level="6.4" data-path="high-level-machine-intelligence.html"><a href="high-level-machine-intelligence.html#subsecharmgood"><i class="fa fa-check"></i><b>6.4</b> The public expects high-level machine intelligence to be more harmful than good</a></li>
</ul></li>
<li class="appendix"><span><b>Appendices</b></span></li>
<li class="chapter" data-level="A" data-path="appmethod.html"><a href="appmethod.html"><i class="fa fa-check"></i><b>A</b> Appendix A: Methodology</a><ul>
<li class="chapter" data-level="A.1" data-path="appmethod.html"><a href="appmethod.html#yougovsampling"><i class="fa fa-check"></i><b>A.1</b> YouGov sampling and weights</a></li>
<li class="chapter" data-level="A.2" data-path="appmethod.html"><a href="appmethod.html#appdemosubgroups"><i class="fa fa-check"></i><b>A.2</b> Demographic subgroups</a></li>
<li class="chapter" data-level="A.3" data-path="appmethod.html"><a href="appmethod.html#appanalysis"><i class="fa fa-check"></i><b>A.3</b> Analysis</a></li>
<li class="chapter" data-level="A.4" data-path="appmethod.html"><a href="appmethod.html#datasharing"><i class="fa fa-check"></i><b>A.4</b> Data sharing</a></li>
</ul></li>
<li class="chapter" data-level="B" data-path="apptopline.html"><a href="apptopline.html"><i class="fa fa-check"></i><b>B</b> Appendix B: Topline questionnaire</a><ul>
<li class="chapter" data-level="B.1" data-path="apptopline.html"><a href="apptopline.html#global_risks"><i class="fa fa-check"></i><b>B.1</b> Global risks</a></li>
<li class="chapter" data-level="B.2" data-path="apptopline.html"><a href="apptopline.html#considersai"><i class="fa fa-check"></i><b>B.2</b> Survey experiment: what the public considers AI, automation, machine learning, and robotics</a></li>
<li class="chapter" data-level="B.3" data-path="apptopline.html"><a href="apptopline.html#knowledge-of-computer-science-cstechnology"><i class="fa fa-check"></i><b>B.3</b> Knowledge of computer science (CS)/technology</a></li>
<li class="chapter" data-level="B.4" data-path="apptopline.html"><a href="apptopline.html#supportdevai"><i class="fa fa-check"></i><b>B.4</b> Support for developing AI</a></li>
<li class="chapter" data-level="B.5" data-path="apptopline.html"><a href="apptopline.html#manageexp"><i class="fa fa-check"></i><b>B.5</b> Survey experiment: AI and/or robots should be carefully managed</a></li>
<li class="chapter" data-level="B.6" data-path="apptopline.html"><a href="apptopline.html#trustdevai"><i class="fa fa-check"></i><b>B.6</b> Trust of actors to develop AI</a></li>
<li class="chapter" data-level="B.7" data-path="apptopline.html"><a href="apptopline.html#trustmanageai"><i class="fa fa-check"></i><b>B.7</b> Trust of actors to manage AI</a></li>
<li class="chapter" data-level="B.8" data-path="apptopline.html"><a href="apptopline.html#govchallenges"><i class="fa fa-check"></i><b>B.8</b> AI governance challenges</a></li>
<li class="chapter" data-level="B.9" data-path="apptopline.html"><a href="apptopline.html#airesearchcompare"><i class="fa fa-check"></i><b>B.9</b> Survey experiment: comparing perceptions of U.S. vs. China AI research and development</a></li>
<li class="chapter" data-level="B.10" data-path="apptopline.html"><a href="apptopline.html#armsraceexp"><i class="fa fa-check"></i><b>B.10</b> Survey experiment: U.S.-China arms race</a><ul>
<li class="chapter" data-level="B.10.1" data-path="apptopline.html"><a href="apptopline.html#control"><i class="fa fa-check"></i><b>B.10.1</b> Control</a></li>
<li class="chapter" data-level="B.10.2" data-path="apptopline.html"><a href="apptopline.html#nationalism-treatment"><i class="fa fa-check"></i><b>B.10.2</b> Nationalism treatment</a></li>
<li class="chapter" data-level="B.10.3" data-path="apptopline.html"><a href="apptopline.html#war-risks-treatment"><i class="fa fa-check"></i><b>B.10.3</b> War risks treatment</a></li>
<li class="chapter" data-level="B.10.4" data-path="apptopline.html"><a href="apptopline.html#common-humanity-treatment"><i class="fa fa-check"></i><b>B.10.4</b> Common humanity treatment</a></li>
</ul></li>
<li class="chapter" data-level="B.11" data-path="apptopline.html"><a href="apptopline.html#uschinacoop"><i class="fa fa-check"></i><b>B.11</b> Issue areas for possible U.S.-China cooperation</a></li>
<li class="chapter" data-level="B.12" data-path="apptopline.html"><a href="apptopline.html#jobtime"><i class="fa fa-check"></i><b>B.12</b> Trend across time: job creation or job loss</a></li>
<li class="chapter" data-level="B.13" data-path="apptopline.html"><a href="apptopline.html#forecasthlmi"><i class="fa fa-check"></i><b>B.13</b> High-level machine intelligence: forecasting timeline</a></li>
<li class="chapter" data-level="B.14" data-path="apptopline.html"><a href="apptopline.html#supporthlmi"><i class="fa fa-check"></i><b>B.14</b> Support for developing high-level machine intelligence</a></li>
<li class="chapter" data-level="B.15" data-path="apptopline.html"><a href="apptopline.html#expectedoutcome"><i class="fa fa-check"></i><b>B.15</b> Expected outcome of high-level machine intelligence</a></li>
</ul></li>
<li class="chapter" data-level="C" data-path="addresults.html"><a href="addresults.html"><i class="fa fa-check"></i><b>C</b> Appendix C: Additional data analysis results</a><ul>
<li class="chapter" data-level="C.1" data-path="addresults.html"><a href="addresults.html#addsupportdevai"><i class="fa fa-check"></i><b>C.1</b> Support for developing AI</a></li>
<li class="chapter" data-level="C.2" data-path="addresults.html"><a href="addresults.html#addcarefullym"><i class="fa fa-check"></i><b>C.2</b> Survey experiment and cross-national comparison: AI and/or robots should be carefully managed</a></li>
<li class="chapter" data-level="C.3" data-path="addresults.html"><a href="addresults.html#appglobalrisks"><i class="fa fa-check"></i><b>C.3</b> Harmful consequences of AI in the context of other global risks</a></li>
<li class="chapter" data-level="C.4" data-path="addresults.html"><a href="addresults.html#aawhatsai"><i class="fa fa-check"></i><b>C.4</b> Survey experiment: what the public considers AI, automation, machine learning, and robotics</a></li>
<li class="chapter" data-level="C.5" data-path="addresults.html"><a href="addresults.html#appgovchallenges"><i class="fa fa-check"></i><b>C.5</b> AI governance challenges: prioritizing governance challenges</a></li>
<li class="chapter" data-level="C.6" data-path="addresults.html"><a href="addresults.html#trust-in-various-actors-to-develop-and-manage-ai-in-the-interest-of-the-public"><i class="fa fa-check"></i><b>C.6</b> Trust in various actors to develop and manage AI in the interest of the public</a></li>
<li class="chapter" data-level="C.7" data-path="addresults.html"><a href="addresults.html#appuschinacomp"><i class="fa fa-check"></i><b>C.7</b> Survey experiment: comparing perceptions of U.S. vs. China AI research and development</a></li>
<li class="chapter" data-level="C.8" data-path="addresults.html"><a href="addresults.html#appuschinaarmsrace"><i class="fa fa-check"></i><b>C.8</b> Survey experiment: U.S.-China arms race</a></li>
<li class="chapter" data-level="C.9" data-path="addresults.html"><a href="addresults.html#appjobloss"><i class="fa fa-check"></i><b>C.9</b> Trend across time: job creation or job loss</a></li>
<li class="chapter" data-level="C.10" data-path="addresults.html"><a href="addresults.html#apphlmi"><i class="fa fa-check"></i><b>C.10</b> High-level machine intelligence: forecasting timeline</a></li>
<li class="chapter" data-level="C.11" data-path="addresults.html"><a href="addresults.html#appsupporthlmi"><i class="fa fa-check"></i><b>C.11</b> Support for developing high-level machine intelligence</a></li>
<li class="chapter" data-level="C.12" data-path="addresults.html"><a href="addresults.html#appexpectedoutcome"><i class="fa fa-check"></i><b>C.12</b> Expected outcome of high-level machine intelligence</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html"><i class="fa fa-check"></i>Acknowledgements</a><ul>
<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html#primary-researchers"><i class="fa fa-check"></i>Primary researchers</a></li>
<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html#editing-and-design"><i class="fa fa-check"></i>Editing and design</a></li>
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<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html#for-media-or-other-inquiries"><i class="fa fa-check"></i>For media or other inquiries</a></li>
<li class="chapter" data-level="" data-path="acknowledgements.html"><a href="acknowledgements.html#recommended-citation"><i class="fa fa-check"></i>Recommended citation</a></li>
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<li class="chapter" data-level="" data-path="about-us.html"><a href="about-us.html"><i class="fa fa-check"></i>About us</a><ul>
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<li class="chapter" data-level="" data-path="about-us.html"><a href="about-us.html#about-the-future-of-humanity-institute"><i class="fa fa-check"></i>About the Future of Humanity Institute</a></li>
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<li class="chapter" data-level="" data-path="references.html"><a href="references.html"><i class="fa fa-check"></i>References</a></li>
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<li><a href="https://governance.ai">Center for the Governance of AI</a></li>
<li><a href="https://www.fhi.ox.ac.uk/">Future of Humanity Institute</a></li>
<li><a href="http://www.ox.ac.uk/">University of Oxford</a></li>
<li><img src="images/FHI-Logo-Print.png" alt="FHI logo" width="77px" hspace="12"/><img src="images/oxford-university-logo.png" alt="Oxford logo" width="74px" hspace="12"/></li>
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<h1><span class="header-section-number">5</span> Trend across time: attitudes toward workplace automation</h1>
<!--
BZ: I think this section is pretty solid -- about 95% there.
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<p>Survey questions measuring Americans’ perceptions of workplace automation have existed since the 1950s. Our research seeks to track changes in these attitudes across time by connecting past survey data with original, contemporary survey data.</p>
<div id="americans-do-not-think-that-labor-market-disruptions-will-increase-with-time" class="section level2">
<h2><span class="header-section-number">5.1</span> Americans do not think that labor market disruptions will increase with time</h2>
<p>American government agencies, think tanks, and media organizations began conducting surveys to study public opinion about technological unemployment during the 1980s when unemployment was relatively high. Between 1983 and 2003, the U.S. National Science Foundation (NSF) conducted eight surveys that asked respondents the following:</p>
<blockquote>
<p>In general, computers and factory automation will create more jobs than they will eliminate. Do you strongly agree, agree, disagree, or strongly disagree?</p>
</blockquote>
<p>Our survey continued this time trend study by posing a similar – but updated – question (see <a href="apptopline.html#jobtime">Appendix B</a>):</p>
<blockquote>
<p>Do you strongly agree, agree, disagree, or strongly disagree with the statement below?</p>
</blockquote>
<blockquote>
<p>In general, automation and AI will create more jobs than they will eliminate.</p>
</blockquote>
<p>Our survey question also addressed the chief ambiguity of the original question: lack of a future time frame. We used a survey experiment to help resolve this ambiguity by randomly assigning respondents to one of four conditions. We created three treatment conditions with the future time frames of 10 years, 20 years, and 50 years, as well as a control condition that did not specify a future time frame.</p>
<p>On average, Americans disagree with the statement more than they agree with it, although about a quarter of respondents in each experimental group give “don’t know” responses. Respondents’ agreement with the statement seems to increase slightly with the future time frame, but formal tests in <a href="addresults.html#appjobloss">Apppendix C</a> reveal that there exist no significant differences between the responses to the differing future time frames. This result is puzzling from the perspective that AI and robotics will increasingly automate tasks currently done by humans. Such a view would expect more <em>disagreement</em> with the statement as one looks further into the future. One hypothesis to explain our results is that respondents believe the disruption from automation is destabilizing in the upcoming 10 years but eventually institutions will adapt and the labor market will stabilize. This hypothesis is consistent with our other finding that the median American predicts a 54% chance of high-level machine intelligence being developed within the next 10 years.</p>
<div class="figure"><span id="fig:jobsloss"></span>
<img src="ai_public_opinion_us_2018_report-190107_web_files/figure-html/jobsloss-1.png" alt="Agreement with the statement that automation and AI will create more jobs than it will eliminate" width="2100" />
<p class="caption">
Figure 5.1: Agreement with the statement that automation and AI will create more jobs than it will eliminate
</p>
</div>
</div>
<div id="extending-the-historical-time-trend" class="section level2">
<h2><span class="header-section-number">5.2</span> Extending the historical time trend</h2>
<p>The percentage of Americans that disagrees with the statement that automation and AI will create more jobs than they destroy is similar to the historical rate of disagreement with the same statement about computers and factory automation. Nevertheless, the percentage who agree with the statement has decreased by 12 percentage points since 2003 while the percentage who responded “don’t know” has increased by 18 percentage points since 2003, according to Figure <a href="trend-across-time-attitudes-toward-workplace-automation.html#fig:jobscompare">5.2</a>.</p>
<p>There are three possible reasons for these observed changes. First, we have updated the question to ask about “automation and AI” instead of “computers and factory automation.” The technologies we asked about could impact a wider swath of the economy; therefore, respondents may be more uncertain about AI’s impact on the labor market. Second, there is a difference in survey mode between the historical data and our data. The NSF surveys were conducted via telephone while our survey is conducted online. Some previous research has shown that online surveys, compared with telephone surveys, produce a greater percentage of “don’t know” responses <span class="citation">(Nagelhout et al. <a href="#ref-nagelhout2010web">2010</a>; Bronner and Kuijlen <a href="#ref-bronner2007live">2007</a>)</span>. But, other studies have shown that online surveys cause no such effect <span class="citation">(Shin, Johnson, and Rao <a href="#ref-shin2012survey">2012</a>; Bech and Kristensen <a href="#ref-bech2009differential">2009</a>)</span>. Third, the changes in the responses could be due to the actual changes in respondents’ perceptions of workplace automation over time.</p>
<div class="figure"><span id="fig:jobscompare"></span>
<img src="ai_public_opinion_us_2018_report-190107_web_files/figure-html/jobscompare-1.png" alt="Response to statement that automation will create more jobs than it will eliminate[^jobsqfn] (data from before 2018 from National Science Foundation surveys)" width="2100" />
<p class="caption">
Figure 5.2: Response to statement that automation will create more jobs than it will eliminate<a href="#fn11" class="footnote-ref" id="fnref11"><sup>11</sup></a> (data from before 2018 from National Science Foundation surveys)
</p>
</div>
</div>
</div>
<h3>References</h3>
<div id="refs" class="references">
<div id="ref-bech2009differential">
<p>Bech, Mickael, and Morten Bo Kristensen. 2009. “Differential Response Rates in Postal and Web-Based Surveys in Older Respondents.” <em>Survey Research Methods</em> 3 (1): 1–6.</p>
</div>
<div id="ref-bronner2007live">
<p>Bronner, Fred, and Ton Kuijlen. 2007. “The Live or Digital Interviewer - a Comparison Between CASI, CAPI and CATI with Respect to Differences in Response Behaviour.” <em>International Journal of Market Research</em> 49 (2): 167–90.</p>
</div>
<div id="ref-nagelhout2010web">
<p>Nagelhout, Gera E, Marc C Willemsen, Mary E Thompson, Geoffrey T Fong, Bas Van den Putte, and Hein de Vries. 2010. “Is Web Interviewing a Good Alternative to Telephone Interviewing? Findings from the International Tobacco Control (Itc) Netherlands Survey.” <em>BMC Public Health</em> 10 (1): 351.</p>
</div>
<div id="ref-shin2012survey">
<p>Shin, Eunjung, Timothy P Johnson, and Kumar Rao. 2012. “Survey Mode Effects on Data Quality: Comparison of Web and Mail Modes in a Us National Panel Survey.” <em>Social Science Computer Review</em> 30 (2): 212–28.</p>
</div>
</div>
<div class="footnotes">
<hr />
<ol start="11">
<li id="fn11"><p>Note that our survey asked respondents this question with the time frames 10, 20 and 50 years, whereas the NSF surveys provided no time frame.<a href="trend-across-time-attitudes-toward-workplace-automation.html#fnref11" class="footnote-back">↩</a></p></li>
</ol>
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