B Appendix B: Topline questionnaire

Below, we present the survey text as shown to respondents. The numerical codings are shown in parentheses following each answer choice.

In addition, we report the topline results: percentages weighted to be representative of the U.S. adult population, the unweighted raw percentages, and the raw frequencies. Note that in all survey experiments, respondents were randomly assigned to each experimental group with equal probability.

B.1 Global risks

[All respondents were presented with the following prompt.]

We want to get your opinion about global risks. A “global risk” is an uncertain event or condition that, if it happens, could cause a significant negative impact for at least 10 percent of the world’s population. That is at least 1 in 10 people around the world could experience a significant negative impact.

You will be asked to consider 5 potential global risks.

[Respondents were presented with five items randomly selected from the list below. One item was shown at a time.]

  • Failure to address climate change: Continued failure of governments and businesses to pass effective measures to reduce climate change, protect people, and help those impacted by climate change to adapt.
  • Failure of regional or global governance: Regional organizations (e.g., the European Union) or global organizations (e.g., the United Nations) are unable to resolve issues of economic, political, or environmental importance.
  • Conflict between major countries: Disputes between major countries that lead to economic, military, cyber, or societal conflicts.
  • Weapons of mass destruction: Use of nuclear, chemical, biological or radiological weapons, creating international crises and killing large numbers of people.
  • Large-scale involuntary migration: Large-scale involuntary movement of people, such as refugees, caused by conflict, disasters, environmental or economic reasons.
  • Rapid and massive spread of infectious diseases: The uncontrolled spread of infectious diseases, for instance as a result of resistance to antibiotics, that leads to widespread deaths and economic disruptions.
  • Water crises: A large decline in the available quality and quantity of fresh water that harms human health and economic activity.
  • Food crises: Large numbers of people are unable to buy or access food. Harmful consequences of artificial intelligence (AI): Intended or unintended consequences of artificial intelligence that causes widespread harm to humans, the economy, and the environment.
  • Harmful consequences of synthetic biology: Intended or unintended consequences of synthetic biology, such as genetic engineering, that causes widespread harm to humans, the economy, and the environment.
  • Large-scale cyber attacks: Large-scale cyber attacks that cause large economic damages, tensions between countries, and widespread loss of trust in the internet.
  • Large-scale terrorist attacks: Individuals or non-government groups with political or religious goals that cause large numbers of deaths and major material damage.
  • Global recession: Economic decline in several major countries that leads to a decrease in income and high unemployment.
  • Extreme weather events: Extreme weather events that cause large numbers of deaths as well as damage to property, infrastructure, and the environment.
  • Major natural disasters: Earthquakes, volcanic activity, landslides, tsunamis, or geomagnetic storms that cause large numbers of deaths as well as damage to property, infrastructure, and the environment.

QUESTION:

What is the likelihood of [INSERT GLOBAL RISK] happening globally within the next 10 years? Please use the slider to indicate your answer. 0% chance means it will certainly not happen and 100% chance means it will certainly happen.

ANSWER CHOICES:17

  • Very unlikely: less than 5% chance (2.5%)
  • Unlikely: 5-20% chance (12.5%)
  • Somewhat unlikely: 20-40% chance (30%)
  • Equally likely as unlikely: 40-60% chance (50%)
  • Somewhat likely: 60-80% chance (70%)
  • Likely: 80-95% chance (87.5%)
  • Very likely: more than 95% chance (97.5%)
  • I don’t know

QUESTION:

If [INSERT GLOBAL RISK] were to happen, what would be the size of the negative impact for several countries or industries within the next 10 years?

ANSWER CHOICES:

  • Minimal (0)
  • Minor (1)
  • Moderate (2)
  • Severe (3)
  • Catastrophic (4)
  • I don’t know
Table B.1: Likelihood - Failure to address climate change; N = 666
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 10.53 10.21 68
Unlikely 5-20% 6.87 6.46 43
Somewhat unlikely 20-40% 11.61 11.41 76
Equally likely as unlikely 40-60% 18.44 18.62 124
Somewhat likely 60-80% 15.81 15.77 105
Likely 80-95% 13.47 13.81 92
Very likely > 95% 16.00 16.37 109
I don’t know 7.17 7.21 48
Skipped 0.10 0.15 1
Table B.2: Likelihood - Failure of regional/global governance; N = 652
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 5.40 5.52 36
Unlikely 5-20% 7.99 7.98 52
Somewhat unlikely 20-40% 12.14 12.42 81
Equally likely as unlikely 40-60% 24.71 24.39 159
Somewhat likely 60-80% 17.80 18.10 118
Likely 80-95% 11.54 11.96 78
Very likely > 95% 8.86 9.51 62
I don’t know 10.96 9.66 63
Skipped 0.58 0.46 3
Table B.3: Likelihood - Conflict between major countries; N = 625
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.47 3.36 21
Unlikely 5-20% 6.45 7.04 44
Somewhat unlikely 20-40% 10.68 10.40 65
Equally likely as unlikely 40-60% 22.16 20.64 129
Somewhat likely 60-80% 22.46 23.36 146
Likely 80-95% 13.92 14.24 89
Very likely > 95% 12.21 12.80 80
I don’t know 8.49 8.00 50
Skipped 0.16 0.16 1
Table B.4: Likelihood - Weapons of mass destruction; N = 645
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 7.05 6.67 43
Unlikely 5-20% 13.71 13.80 89
Somewhat unlikely 20-40% 15.19 15.04 97
Equally likely as unlikely 40-60% 24.33 24.19 156
Somewhat likely 60-80% 17.15 17.36 112
Likely 80-95% 9.26 9.15 59
Very likely > 95% 6.44 6.98 45
I don’t know 6.87 6.82 44
Skipped 0 0 0
Table B.5: Likelihood - Large-scale involuntary migration; N = 628
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 6.70 6.53 41
Unlikely 5-20% 7.83 7.32 46
Somewhat unlikely 20-40% 11.57 11.62 73
Equally likely as unlikely 40-60% 18.65 18.31 115
Somewhat likely 60-80% 20.91 21.34 134
Likely 80-95% 13.63 14.01 88
Very likely > 95% 12.31 13.06 82
I don’t know 8.27 7.64 48
Skipped 0.12 0.16 1
Table B.6: Likelihood - Spread of infectious diseases; N = 620
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 4.76 4.03 25
Unlikely 5-20% 13.12 13.06 81
Somewhat unlikely 20-40% 17.24 17.58 109
Equally likely as unlikely 40-60% 22.76 23.39 145
Somewhat likely 60-80% 17.55 17.58 109
Likely 80-95% 10.07 10.00 62
Very likely > 95% 6.94 6.94 43
I don’t know 7.46 7.26 45
Skipped 0.12 0.16 1
Table B.7: Likelihood - Water crises; N = 623
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 6.37 6.10 38
Unlikely 5-20% 9.71 10.43 65
Somewhat unlikely 20-40% 13.22 13.64 85
Equally likely as unlikely 40-60% 21.23 21.03 131
Somewhat likely 60-80% 20.26 19.26 120
Likely 80-95% 11.04 10.91 68
Very likely > 95% 10.83 11.72 73
I don’t know 7.33 6.90 43
Skipped 0 0 0
Table B.8: Likelihood - Food crises; N = 1073
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 6.29 5.96 64
Unlikely 5-20% 12.53 11.65 125
Somewhat unlikely 20-40% 14.49 14.82 159
Equally likely as unlikely 40-60% 22.53 22.55 242
Somewhat likely 60-80% 16.90 17.24 185
Likely 80-95% 10.46 10.90 117
Very likely > 95% 9.38 10.07 108
I don’t know 7.36 6.71 72
Skipped 0.08 0.09 1
Table B.9: Likelihood - Harmful consequences of AI; N = 573
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 11.26 11.34 65
Unlikely 5-20% 16.43 16.06 92
Somewhat unlikely 20-40% 15.95 15.53 89
Equally likely as unlikely 40-60% 19.36 20.07 115
Somewhat likely 60-80% 11.56 11.34 65
Likely 80-95% 8.30 8.03 46
Very likely > 95% 7.71 7.85 45
I don’t know 9.43 9.77 56
Skipped 0 0 0
Table B.10: Likelihood - Harmful consequences of synthetic biology; N = 630
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 9.92 9.68 61
Unlikely 5-20% 15.66 15.08 95
Somewhat unlikely 20-40% 15.06 15.24 96
Equally likely as unlikely 40-60% 23.48 22.86 144
Somewhat likely 60-80% 12.32 12.86 81
Likely 80-95% 7.47 7.62 48
Very likely > 95% 6.04 6.19 39
I don’t know 10.06 10.48 66
Skipped 0 0 0
Table B.11: Likelihood - Cyber attacks; N = 650
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.04 2.15 14
Unlikely 5-20% 4.28 3.69 24
Somewhat unlikely 20-40% 7.74 7.85 51
Equally likely as unlikely 40-60% 15.78 16.15 105
Somewhat likely 60-80% 22.66 21.85 142
Likely 80-95% 16.44 16.62 108
Very likely > 95% 22.40 23.54 153
I don’t know 8.53 8.00 52
Skipped 0.12 0.15 1
Table B.12: Likelihood - Terrorist attacks; N = 635
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 5.21 4.88 31
Unlikely 5-20% 4.53 4.88 31
Somewhat unlikely 20-40% 12.43 11.81 75
Equally likely as unlikely 40-60% 19.47 19.21 122
Somewhat likely 60-80% 22.28 22.52 143
Likely 80-95% 15.74 15.43 98
Very likely > 95% 12.45 12.91 82
I don’t know 7.89 8.35 53
Skipped 0 0 0
Table B.13: Likelihood - Global recession; N = 599
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 4.17 3.67 22
Unlikely 5-20% 7.34 7.18 43
Somewhat unlikely 20-40% 12.68 12.85 77
Equally likely as unlikely 40-60% 23.43 24.21 145
Somewhat likely 60-80% 23.83 23.04 138
Likely 80-95% 10.80 10.85 65
Very likely > 95% 8.34 8.68 52
I don’t know 9.41 9.52 57
Skipped 0 0 0
Table B.14: Likelihood - Extreme weather events; N = 613
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.52 3.10 19
Unlikely 5-20% 5.64 5.22 32
Somewhat unlikely 20-40% 8.77 8.81 54
Equally likely as unlikely 40-60% 20.12 18.76 115
Somewhat likely 60-80% 18.09 18.27 112
Likely 80-95% 13.02 14.03 86
Very likely > 95% 24.95 25.45 156
I don’t know 5.89 6.36 39
Skipped 0 0 0
Table B.15: Likelihood - Natural disasters; N = 637
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.47 2.51 16
Unlikely 5-20% 4.10 4.08 26
Somewhat unlikely 20-40% 7.32 7.06 45
Equally likely as unlikely 40-60% 17.63 17.74 113
Somewhat likely 60-80% 19.43 19.15 122
Likely 80-95% 18.12 18.05 115
Very likely > 95% 25.73 26.37 168
I don’t know 5.21 5.02 32
Skipped 0 0 0
Table B.16: Size of negative impact - Failure to address climate change; N = 666
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 13.46 13.96 93
Minor 11.26 10.96 73
Moderate 23.37 23.27 155
Severe 28.41 28.08 187
Catastrophic 14.26 14.56 97
I don’t know 9.13 9.01 60
Skipped 0.10 0.15 1
Table B.17: Size of negative impact - Failure of regional/global governance; N = 652
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 6.04 5.98 39
Minor 6.09 5.67 37
Moderate 28.68 28.99 189
Severe 33.21 34.05 222
Catastrophic 10.76 10.89 71
I don’t know 15.12 14.26 93
Skipped 0.10 0.15 1
Table B.18: Size of negative impact - Conflict between major countries; N = 625
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 1.18 0.96 6
Minor 4.94 4.80 30
Moderate 28.81 28.16 176
Severe 38.23 38.56 241
Catastrophic 14.80 16.00 100
I don’t know 11.89 11.36 71
Skipped 0.14 0.16 1
Table B.19: Size of negative impact - Weapons of mass destruction; N = 645
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.28 2.17 14
Minor 4.99 4.19 27
Moderate 13.57 13.49 87
Severe 31.05 31.01 200
Catastrophic 38.06 39.38 254
I don’t know 10.05 9.77 63
Skipped 0 0 0
Table B.20: Size of negative impact - Large-scale involuntary migration; N = 628
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.07 2.07 13
Minor 8.67 8.28 52
Moderate 25.63 25.96 163
Severe 35.31 36.15 227
Catastrophic 18.14 17.83 112
I don’t know 9.99 9.55 60
Skipped 0.19 0.16 1
Table B.21: Size of negative impact - Spread of infectious diseases; N = 620
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.72 2.58 16
Minor 6.03 5.65 35
Moderate 26.86 28.06 174
Severe 32.00 32.58 202
Catastrophic 20.50 20.48 127
I don’t know 11.88 10.65 66
Skipped 0 0 0
Table B.22: Size of negative impact - Water crises; N = 623
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 1.72 1.93 12
Minor 4.42 4.65 29
Moderate 19.92 19.42 121
Severe 36.71 36.44 227
Catastrophic 27.24 28.25 176
I don’t know 10.00 9.31 58
Skipped 0 0 0
Table B.23: Size of negative impact - Food crises; N = 1073
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.55 2.61 28
Minor 7.22 6.99 75
Moderate 22.81 22.37 240
Severe 33.93 34.67 372
Catastrophic 24.04 24.88 267
I don’t know 9.38 8.39 90
Skipped 0.08 0.09 1
Table B.24: Size of negative impact - Harmful consequences of AI; N = 573
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 7.54 7.50 43
Minor 14.82 13.79 79
Moderate 27.77 27.92 160
Severe 20.46 21.82 125
Catastrophic 14.62 14.31 82
I don’t know 14.79 14.66 84
Skipped 0 0 0
Table B.25: Size of negative impact - Harmful consequences of synthetic biology; N = 630
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 6.77 6.67 42
Minor 11.95 11.59 73
Moderate 28.40 27.94 176
Severe 26.03 26.03 164
Catastrophic 11.15 11.90 75
I don’t know 15.70 15.87 100
Skipped 0 0 0
Table B.26: Size of negative impact - Cyber attacks; N = 650
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 1.19 1.23 8
Minor 4.46 4.46 29
Moderate 21.43 21.23 138
Severe 38.26 37.69 245
Catastrophic 23.01 24.46 159
I don’t know 11.66 10.92 71
Skipped 0 0 0
Table B.27: Size of negative impact - Terrorist attacks; N = 635
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.61 2.68 17
Minor 6.11 6.14 39
Moderate 29.29 29.45 187
Severe 33.69 33.70 214
Catastrophic 15.97 15.91 101
I don’t know 12.32 12.13 77
Skipped 0 0 0
Table B.28: Size of negative impact - Global recession; N = 599
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.71 2.67 16
Minor 5.94 5.68 34
Moderate 29.89 29.72 178
Severe 35.49 36.23 217
Catastrophic 14.63 14.52 87
I don’t know 11.35 11.19 67
Skipped 0 0 0
Table B.29: Size of negative impact - Extreme weather events; N = 613
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 2.54 2.45 15
Minor 6.69 6.53 40
Moderate 25.94 26.43 162
Severe 32.50 31.97 196
Catastrophic 22.79 23.00 141
I don’t know 9.56 9.62 59
Skipped 0 0 0
Table B.30: Size of negative impact - Natural disasters; N = 637
Responses Percentages (weighted) Percentages (unweighted) Raw frequencies
Minimal 1.29 1.26 8
Minor 5.86 5.81 37
Moderate 22.26 23.08 147
Severe 36.41 36.11 230
Catastrophic 27.47 27.32 174
I don’t know 6.72 6.44 41
Skipped 0 0 0

B.2 Survey experiment: what the public considers AI, automation, machine learning, and robotics

[Respondents were randomly assigned to one of the four questions. The order of answer choices was randomized, except that “None of the above” was always shown last.]

QUESTIONS:

  • In your opinion, which of the following technologies, if any, uses artificial intelligence (AI)? Select all the apply.
  • In your opinion, which of the following technologies, if any, uses automation? Select all that apply.
  • In your opinion, which of the following technologies, if any, uses machine learning? Select all that apply.
  • In your opinion, which of the following technologies, if any, uses robotics? Select all that apply.

ANSWER CHOICES:

  • Virtual assistants (e.g., Siri, Google Assistant, Amazon Alexa)
  • Smart speakers (e.g., Amazon Echo, Google Home, Apple Homepod)
  • Facebook photo tagging
  • Google Search
  • Recommendations for Netflix movies or Amazon ebooks
  • Google Translate
  • Driverless cars and trucks
  • Social robots that can interact with humans
  • Industrial robots used in manufacturing
  • Drones that do not require a human controller
  • None of the above
Table B.31: Artificial intelligence (AI); N = 493
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Virtual assistants (e.g., Siri, Google Assistant, Amazon Alexa) 62.87 64.30 317
Smart speakers (e.g., Amazon Echo, Google Home, Apple Homepod) 55.46 56.19 277
Facebook photo tagging 36.16 36.51 180
Google Search 35.59 36.51 180
Recommendations for Netflix movies or Amazon ebooks 27.73 29.01 143
Google Translate 29.49 30.02 148
Driverless cars and trucks 56.38 57.20 282
Social robots that can interact with humans 63.63 64.10 316
Industrial robots used in manufacturing 40.11 40.16 198
Drones that do not require a human controller 53.48 52.74 260
Table B.32: Automation; N = 513
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Virtual assistants (e.g., Siri, Google Assistant, Amazon Alexa) 66.75 67.06 344
Smart speakers (e.g., Amazon Echo, Google Home, Apple Homepod) 60.81 61.01 313
Facebook photo tagging 43.74 45.42 233
Google Search 52.12 53.80 276
Recommendations for Netflix movies or Amazon ebooks 45.13 46.39 238
Google Translate 45.06 46.39 238
Driverless cars and trucks 68.16 68.62 352
Social robots that can interact with humans 64.00 64.72 332
Industrial robots used in manufacturing 64.70 65.11 334
Drones that do not require a human controller 65.04 65.69 337
Table B.33: Machine learning; N = 508
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Virtual assistants (e.g., Siri, Google Assistant, Amazon Alexa) 59.10 60.43 307
Smart speakers (e.g., Amazon Echo, Google Home, Apple Homepod) 46.70 46.65 237
Facebook photo tagging 35.37 36.81 187
Google Search 45.42 46.26 235
Recommendations for Netflix movies or Amazon ebooks 37.97 38.19 194
Google Translate 33.40 34.06 173
Driverless cars and trucks 52.96 54.33 276
Social robots that can interact with humans 59.19 59.45 302
Industrial robots used in manufacturing 37.41 37.80 192
Drones that do not require a human controller 49.03 49.41 251
Table B.34: Robotics; N = 486
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Virtual assistants (e.g., Siri, Google Assistant, Amazon Alexa) 45.27 46.30 225
Smart speakers (e.g., Amazon Echo, Google Home, Apple Homepod) 35.59 36.83 179
Facebook photo tagging 21.00 21.40 104
Google Search 22.07 23.25 113
Recommendations for Netflix movies or Amazon ebooks 17.84 18.31 89
Google Translate 20.30 21.19 103
Driverless cars and trucks 60.26 61.93 301
Social robots that can interact with humans 61.89 63.17 307
Industrial robots used in manufacturing 67.99 69.75 339
Drones that do not require a human controller 57.55 59.05 287

B.3 Knowledge of computer science (CS)/technology

QUESTION:

What is your knowledge of computer science/technology? (Select all that apply.)

ANSWER CHOICES:

  • I have taken at least one college-level course in computer science.
  • I have a computer science or engineering undergraduate degree.
  • I have a graduate degree in computer science or engineering.
  • I have programming experience.
  • I don’t have any of the educational or work experiences described above.
Table B.35: Computer science/technology background; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Took at least one college-level course in CS 24.73 25.05 501
CS or engineering undergraduate degree 7.12 7.30 146
CS or engineering graduate degree 3.85 3.75 75
Have programming experience 10.88 11.10 222
None of the above 63.68 63.20 1264

B.4 Support for developing AI

[All respondents were presented with the following prompt.]

Next, we would like to ask you questions about your attitudes toward artificial intelligence.

Artificial Intelligence (AI) refers to computer systems that perform tasks or make decisions that usually require human intelligence. AI can perform these tasks or make these decisions without explicit human instructions. Today, AI has been used in the following applications:

[Respondents were shown five items randomly selected from the list below.]

  • Translate over 100 different languages
  • Predict one’s Google searches
  • Identify people from their photos
  • Diagnose diseases like skin cancer and common illnesses
  • Predict who are at risk of various diseases
  • Help run factories and warehouses
  • Block spam email
  • Play computer games
  • Help conduct legal case research
  • Categorize photos and videos
  • Detect plagiarism in essays
  • Spot abusive messages on social media
  • Predict what one is likely to buy online
  • Predict what movies or TV shows one is likely to watch online

QUESTION:

How much do you support or oppose the development of AI?

ANSWER CHOICES:

  • Strongly support (2)
  • Somewhat support (1)
  • Neither support nor oppose (0)
  • Somewhat oppose (-1)
  • Strongly oppose (-2)
  • I don’t know
Table B.36: Support for developing AI; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly support 12.58 12.65 253
Somewhat support 28.36 28.65 573
Neither support nor oppose 27.84 27.60 552
Somewhat oppose 12.79 12.75 255
Strongly oppose 8.90 9.05 181
I don’t know 9.54 9.30 186
Skipped 0 0 0

B.5 Survey experiment: AI and/or robots should be carefully managed

QUESTION:

Please tell me to what extent you agree or disagree with the following statement.

[Respondents were presented with one statement randomly selected from the list below.]

  • AI and robots are technologies that require careful management.
  • AI is a technology that requires careful management.
  • Robots are technologies that require careful management.

ANSWER CHOICES:

  • Totally agree (2)
  • Tend to agree (1)
  • Tend to disagree (-1)
  • Totally disagree (-2)
  • I don’t know
Table B.37: Responses to statement - AI and robots; N = 656
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Totally agree 51.41 53.20 349
Tend to agree 30.09 28.96 190
Tend to disagree 4.79 3.81 25
Totally disagree 0.59 0.76 5
I don’t know 13.12 13.26 87
Skipped 0 0 0
Table B.38: Responses to statement - AI; N = 667
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Totally agree 53.54 53.67 358
Tend to agree 30.85 30.13 201
Tend to disagree 3.67 3.90 26
Totally disagree 0.80 0.90 6
I don’t know 11.14 11.39 76
Skipped 0 0 0
Table B.39: Responses to statement - Robots; N = 677
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Totally agree 51.66 52.44 355
Tend to agree 30.31 31.31 212
Tend to disagree 5.76 5.17 35
Totally disagree 1.81 1.48 10
I don’t know 10.46 9.60 65
Skipped 0 0 0

B.6 Trust of actors to develop AI

QUESTION:

How much confidence, if any, do you have in each of the following to develop AI in the best interests of the public?

[Respondents were shown five items randomly selected from the list below. We included explainer text for actors not well known to the public; respondents could view the explainer text by hovering their mouse over the actor’s name. The items and the answer choices were shown in a matrix format.]

  • The U.S. military
  • The U.S. civilian government
  • National Security Agency (NSA)
  • Federal Bureau of Investigation (FBI)
  • Central Intelligence Agency (CIA)
  • North Atlantic Treaty Organization (NATO)
  • Explainer text for NATO: NATO is a military alliance that includes 28 countries including most of Europe, as well as the U.S. and Canada.
  • An international research organization (e.g., CERN)
  • Explainer text for CERN: The European Organization for Nuclear Research, known as CERN, is a European research organization that operates the largest particle physics laboratory in the world.
  • Tech companies
  • Google
  • Facebook
  • Apple
  • Microsoft
  • Amazon
  • A non-profit AI research organization (e.g., OpenAI)
  • Explainer text for OpenAI: Open AI is an AI non-profit organization with backing from tech investors that seeks to develop safe AI. University researchers

ANSWER CHOICES:

  • A great deal of confidence (3)
  • A fair amount of confidence (2)
  • Not too much confidence (1)
  • No confidence (0)
  • I don’t know
Table B.40: U.S. military; N = 638
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 17.16 17.08 109
A fair amount of confidence 32.19 30.88 197
Not too much confidence 23.92 24.14 154
No confidence 14.40 14.89 95
I don’t know 12.33 13.01 83
Skipped 0 0 0
Table B.41: U.S. civilian government; N = 671
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 5.59 5.66 38
A fair amount of confidence 24.04 24.29 163
Not too much confidence 32.77 33.23 223
No confidence 23.80 23.40 157
I don’t know 13.79 13.41 90
Skipped 0 0 0
Table B.42: NSA; N = 710
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 9.63 9.30 66
A fair amount of confidence 28.04 26.90 191
Not too much confidence 26.65 26.76 190
No confidence 22.82 24.37 173
I don’t know 12.87 12.68 90
Skipped 0 0 0
Table B.43: FBI; N = 656
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 9.26 9.60 63
A fair amount of confidence 26.20 25.46 167
Not too much confidence 25.07 25.15 165
No confidence 27.10 27.44 180
I don’t know 12.25 12.20 80
Skipped 0.14 0.15 1
Table B.44: CIA; N = 730
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 8.43 8.77 64
A fair amount of confidence 26.10 25.07 183
Not too much confidence 26.80 26.99 197
No confidence 25.61 26.30 192
I don’t know 12.93 12.74 93
Skipped 0.13 0.14 1
Table B.45: NATO; N = 695
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 4.40 4.17 29
A fair amount of confidence 25.41 24.75 172
Not too much confidence 25.98 26.62 185
No confidence 23.13 24.03 167
I don’t know 21.08 20.43 142
Skipped 0 0 0
Table B.46: Intergovernmental research organizations (e.g., CERN); N = 645
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 11.97 12.25 79
A fair amount of confidence 28.87 28.84 186
Not too much confidence 22.94 22.64 146
No confidence 16.85 16.59 107
I don’t know 19.37 19.69 127
Skipped 0 0 0
Table B.47: Tech companies; N = 674
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.28 10.83 73
A fair amount of confidence 34.15 34.57 233
Not too much confidence 28.40 27.15 183
No confidence 14.91 15.13 102
I don’t know 12.15 12.17 82
Skipped 0.12 0.15 1
Table B.48: Google; N = 645
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 11.91 11.47 74
A fair amount of confidence 27.35 26.82 173
Not too much confidence 25.92 26.67 172
No confidence 21.56 21.40 138
I don’t know 13.00 13.33 86
Skipped 0.26 0.31 2
Table B.49: Facebook; N = 632
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 4.29 3.96 25
A fair amount of confidence 14.35 13.45 85
Not too much confidence 26.40 27.22 172
No confidence 41.27 42.88 271
I don’t know 13.44 12.18 77
Skipped 0.25 0.32 2
Table B.50: Apple; N = 697
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.41 10.76 75
A fair amount of confidence 26.29 26.26 183
Not too much confidence 27.00 27.98 195
No confidence 22.20 21.81 152
I don’t know 13.84 12.91 90
Skipped 0.26 0.29 2
Table B.51: Microsoft; N = 597
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.85 10.89 65
A fair amount of confidence 33.08 32.66 195
Not too much confidence 26.89 27.14 162
No confidence 17.99 17.76 106
I don’t know 11.05 11.39 68
Skipped 0.14 0.17 1
Table B.52: Amazon; N = 685
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.60 10.95 75
A fair amount of confidence 29.53 29.34 201
Not too much confidence 25.51 25.40 174
No confidence 22.02 22.19 152
I don’t know 12.34 12.12 83
Skipped 0 0 0
Table B.53: Non-profit (e.g., OpenAI); N = 659
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.19 10.17 67
A fair amount of confidence 29.40 30.35 200
Not too much confidence 23.57 23.98 158
No confidence 13.65 13.66 90
I don’t know 23.04 21.70 143
Skipped 0.13 0.15 1
Table B.54: University researchers; N = 666
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 13.86 14.11 94
A fair amount of confidence 36.29 36.04 240
Not too much confidence 22.27 22.82 152
No confidence 12.75 12.31 82
I don’t know 14.70 14.56 97
Skipped 0.14 0.15 1

B.7 Trust of actors to manage AI

QUESTION:

How much confidence, if any, do you have in each of the following to manage the development and use of AI in the best interests of the public?

[Respondents were shown five items randomly selected from the list below. We included explainer text for actors not well known to the public; respondents could view the explainer text by hovering their mouse over the actor’s name. The items and the answer choices were shown in a matrix format.]

  • U.S. federal government
  • U.S. state governments
  • International organizations (e.g., United Nations, European Union)
  • The United Nations (UN)
  • An intergovernmental research organization (e.g., CERN)
  • Explainer text for CERN: The European Organization for Nuclear Research, known as CERN, is a European research organization that operates the largest particle physics laboratory in the world.
  • Tech companies
  • Google
  • Facebook
  • Apple
  • Microsoft
  • Amazon
  • Non-government scientific organizations (e.g., AAAI)
  • Explainer text for AAAI: Association for the Advancement of Artificial Intelligence (AAAI) is a non-government scientific organization that promotes research in, and responsible use of AI.
  • Partnership on AI, an association of tech companies, academics, and civil society groups

ANSWER CHOICES:

  • A great deal of confidence (3)
  • A fair amount of confidence (2)
  • Not too much confidence (1)
  • No confidence (0)
  • I don’t know
Table B.55: U.S. federal government; N = 743
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 6.86 6.59 49
A fair amount of confidence 20.26 20.19 150
Not too much confidence 28.44 28.67 213
No confidence 31.50 32.44 241
I don’t know 12.68 11.84 88
Skipped 0.25 0.27 2
Table B.56: U.S. state governments; N = 713
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 6.25 6.45 46
A fair amount of confidence 20.39 19.21 137
Not too much confidence 31.57 32.12 229
No confidence 29.65 30.72 219
I don’t know 11.69 11.22 80
Skipped 0.45 0.28 2
Table B.57: International organizations; N = 827
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 5.94 5.80 48
A fair amount of confidence 22.48 21.77 180
Not too much confidence 29.58 29.87 247
No confidence 26.81 27.45 227
I don’t know 14.81 14.87 123
Skipped 0.38 0.24 2
Table B.58: UN; N = 802
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 6.23 6.61 53
A fair amount of confidence 22.49 21.57 173
Not too much confidence 26.14 26.18 210
No confidence 31.90 31.55 253
I don’t know 12.64 13.59 109
Skipped 0.60 0.50 4
Table B.59: Intergovernmental research organizations (e.g., CERN); N = 747
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 6.69 7.10 53
A fair amount of confidence 30.51 29.72 222
Not too much confidence 23.89 24.10 180
No confidence 20.32 20.21 151
I don’t know 18.36 18.61 139
Skipped 0.22 0.27 2
Table B.60: Tech companies; N = 758
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 8.33 8.44 64
A fair amount of confidence 33.50 32.98 250
Not too much confidence 25.07 26.12 198
No confidence 19.88 20.45 155
I don’t know 12.81 11.74 89
Skipped 0.41 0.26 2
Table B.61: Google; N = 767
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 9.61 9.13 70
A fair amount of confidence 23.60 23.86 183
Not too much confidence 27.44 27.77 213
No confidence 25.13 25.03 192
I don’t know 13.75 13.95 107
Skipped 0.47 0.26 2
Table B.62: Facebook; N = 741
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 4.99 4.45 33
A fair amount of confidence 16.18 16.19 120
Not too much confidence 28.50 28.21 209
No confidence 36.95 38.46 285
I don’t know 13.14 12.42 92
Skipped 0.24 0.27 2
Table B.63: Apple; N = 775
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 8.25 8.39 65
A fair amount of confidence 25.10 24.90 193
Not too much confidence 29.08 28.65 222
No confidence 23.91 24.52 190
I don’t know 13.55 13.42 104
Skipped 0.12 0.13 1
Table B.64: Microsoft; N = 771
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 7.79 7.78 60
A fair amount of confidence 30.11 29.83 230
Not too much confidence 22.98 23.48 181
No confidence 24.10 24.38 188
I don’t know 14.68 14.14 109
Skipped 0.35 0.39 3
Table B.65: Amazon; N = 784
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 10.19 10.33 81
A fair amount of confidence 25.22 24.87 195
Not too much confidence 25.20 25.38 199
No confidence 24.53 24.87 195
I don’t know 14.87 14.54 114
Skipped 0 0 0
Table B.66: Non-government scientific organization (e.g., AAAI); N = 792
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 7.64 7.83 62
A fair amount of confidence 30.32 30.05 238
Not too much confidence 25.37 26.39 209
No confidence 15.03 14.65 116
I don’t know 21.46 20.83 165
Skipped 0.19 0.25 2
Table B.67: Partnership on AI; N = 780
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
A great deal of confidence 8.89 9.23 72
A fair amount of confidence 30.12 29.49 230
Not too much confidence 25.89 26.79 209
No confidence 16.33 15.77 123
I don’t know 18.64 18.59 145
Skipped 0.12 0.13 1

B.8 AI governance challenges

We would like you to consider some potential policy issues related to AI. Please consider the following:

[Respondents were shown five randomly-selected items from the list below, one item at a time. For ease of comprehension, we include the shorten labels used in the figures in square brackets.]

  • [Hiring bias] Fairness and transparency in AI used in hiring: Increasingly, employers are using AI to make hiring decisions. AI has the potential to make less biased hiring decisions than humans. But algorithms trained on biased data can lead to lead to hiring practices that discriminate against certain groups. Also, AI used in this application may lack transparency, such that human users do not understand what the algorithm is doing, or why it reaches certain decisions in specific cases.
  • [Criminal justice bias] Fairness and transparency in AI used in criminal justice: Increasingly, the criminal justice system is using AI to make sentencing and parole decisions. AI has the potential to make less biased hiring decisions than humans. But algorithms trained on biased data could lead to discrimination against certain groups. Also, AI used in this application may lack transparency such that human users do not understand what the algorithm is doing, or why it reaches certain decisions in specific cases.
  • [Disease diagnosis] Accuracy and transparency in AI used for disease diagnosis: Increasingly, AI software has been used to diagnose diseases, such as heart disease and cancer. One challenge is to make sure the AI can correctly diagnose those who have the disease and not mistakenly diagnose those who do not have the disease. Another challenge is that AI used in this application may lack transparency such that human users do not understand what the algorithm is doing, or why it reaches certain decisions in specific cases.
  • [Data privacy] Protect data privacy: Algorithms used in AI applications are often trained on vast amounts of personal data, including medical records, social media content, and financial transactions. Some worry that data used to train algorithms are not collected, used, and stored in ways that protect personal privacy.
  • [Autonomous vehicles] Make sure autonomous vehicles are safe: Companies are developing self-driving cars and trucks that require little or no input from humans. Some worry about the safety of autonomous vehicles for those riding in them as well as for other vehicles, cyclists, and pedestrians.
  • [Ditigal manipulation] Prevent AI from being used to spread fake and harmful content online: AI has been used by governments, private groups, and individuals to harm or manipulate internet users. For instance, automated bots have been used to generate and spread false and/or harmful news stories, audios, and videos.
  • [Cyber attacks] Prevent AI cyber attacks against governments, companies, organizations, and individuals: Computer scientists have shown that AI can be used to launch effective cyber attacks. AI could be used to hack into servers to steal sensitive information, shut down critical infrastructures like power grids or hospital networks, or scale up targeted phishing attacks.
  • [Surveillance] Prevent AI-assisted surveillance from violating privacy and civil liberties: AI can be used to process and analyze large amounts of text, photo, audio, and video data from social media, mobile communications, and CCTV cameras. Some worry that governments, companies, and employers could use AI to increase their surveillance capabilities.
  • [U.S.-China arms race] Prevent escalation of a U.S.-China AI arms race: Leading analysts believe that an AI arms race is beginning, in which the U.S. and China are investing billions of dollars to develop powerful AI systems for surveillance, autonomous weapons, cyber operations, propaganda, and command and control systems. Some worry that a U.S.-China arms race could lead to extreme dangers. To stay ahead, the U.S. and China may race to deploy advanced military AI systems that they do not fully understand or can control. We could see catastrophic accidents, such as a rapid, automated escalation involving cyber and nuclear weapons.
  • [Value alignment] Make sure AI systems are safe, trustworthy, and aligned with human values: As AI systems become more advanced, they will increasingly make decisions without human input. One potential fear is that AI systems, while performing jobs they are programmed to do, could unintentionally make decisions that go against the values of its human users, such as physically harming people.
  • [Autonomous weapons] Ban the use of lethal autonomous weapons (LAWs): Lethal autonomous weapons (LAWs) are military robots that can attack targets without control by humans. LAWs could reduce the use of human combatants on the battlefield. But some worry that the adoption of LAWs could lead to mass violence. Because they are cheap and easy to produce in bulk, national militaries, terrorists, and other groups could readily deploy LAWs.
  • [Technological unemployment] Guarantee a good standard of living for those who lose their jobs to automation: Some forecast that AI will increasingly be able to do jobs done by humans today. AI could potentially do the jobs of blue-collar workers, like truckers and factory workers, as well as the jobs of white-collar workers, like financial analysts or lawyers. Some worry that in the future, robots and computers can do most of the jobs that are done by humans today.
  • [Critical AI systems failure] Prevent critical AI systems failures: As AI systems become more advanced, they could be used by the military or in critical infrastructure, like power grids, highways, or hospital networks. Some worry that the failure of AI systems or unintentional accidents in these applications could cause 10 percent or more of all humans to die.

QUESTION:

In the next 10 years, how likely do you think it is that this AI governance challenge will impact large numbers of people in the U.S.?

ANSWER CHOICES:

  • Very unlikely: less than 5% chance (2.5%)
  • Unlikely: 5-20% chance (12.5%)
  • Somewhat unlikely: 20-40% chance (30%)
  • Equally likely as unlikely: 40-60% chance (50%)
  • Somewhat likely: 60-80% chance (70%)
  • Likely: 80-95% chance (87.5%)
  • Very likely: more than 95% chance (97.5%)
  • I don’t know

QUESTION:

In the next 10 years, how likely do you think it is that this AI governance challenge will impact large numbers of people around the world?

ANSWER CHOICES:

  • Very unlikely: less than 5% chance (2.5%)
  • Unlikely: 5-20% chance (12.5%)
  • Somewhat unlikely: 20-40% chance (30%)
  • Equally likely as unlikely: 40-60% chance (50%)
  • Somewhat likely: 60-80% chance (70%)
  • Likely: 80-95% chance (87.5%)
  • Very likely: more than 95% chance (97.5%)
  • I don’t know

QUESTION:

In the next 10 years, how important is it for tech companies and governments to carefully manage the following challenge?

ANSWER CHOICES:

  • Very important (3)
  • Somewhat important (2)
  • Not too important (1)
  • Not at all important (0)
  • I don’t know
Table B.68: Likelihood in the U.S. - Hiring bias; N = 760
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.57 2.63 20
Unlikely 5-20% 6.07 6.18 47
Somewhat unlikely 20-40% 10.86 10.92 83
Equally likely as unlikely 40-60% 22.27 22.50 171
Somewhat likely 60-80% 23.34 22.89 174
Likely 80-95% 12.39 12.76 97
Very likely > 95% 9.86 9.61 73
I don’t know 12.35 12.37 94
Skipped 0.29 0.13 1
Table B.69: Likelihood in the U.S. - Criminal justice bias; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 4.94 4.50 35
Unlikely 5-20% 8.76 8.61 67
Somewhat unlikely 20-40% 13.25 12.85 100
Equally likely as unlikely 40-60% 21.23 21.08 164
Somewhat likely 60-80% 17.13 17.22 134
Likely 80-95% 12.28 12.60 98
Very likely > 95% 9.05 9.64 75
I don’t know 12.90 12.98 101
Skipped 0.45 0.51 4
Table B.70: Likelihood in the U.S. - Disease diagnosis; N = 767
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.79 2.61 20
Unlikely 5-20% 4.73 4.95 38
Somewhat unlikely 20-40% 10.18 9.52 73
Equally likely as unlikely 40-60% 23.12 23.21 178
Somewhat likely 60-80% 20.50 19.95 153
Likely 80-95% 13.43 13.95 107
Very likely > 95% 9.72 10.17 78
I don’t know 13.62 13.69 105
Skipped 1.91 1.96 15
Table B.71: Likelihood in the U.S. - Data privacy; N = 807
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.75 2.11 17
Unlikely 5-20% 4.53 4.58 37
Somewhat unlikely 20-40% 7.52 7.19 58
Equally likely as unlikely 40-60% 16.10 15.86 128
Somewhat likely 60-80% 18.81 19.33 156
Likely 80-95% 17.00 16.36 132
Very likely > 95% 20.59 21.69 175
I don’t know 10.87 10.78 87
Skipped 1.84 2.11 17
Table B.72: Likelihood in the U.S. - Autonomous vehicles; N = 796
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.65 3.64 29
Unlikely 5-20% 5.80 5.90 47
Somewhat unlikely 20-40% 10.93 10.43 83
Equally likely as unlikely 40-60% 16.17 16.33 130
Somewhat likely 60-80% 23.62 23.62 188
Likely 80-95% 15.78 15.45 123
Very likely > 95% 12.29 12.94 103
I don’t know 10.89 10.68 85
Skipped 0.87 1.01 8
Table B.73: Likelihood in the U.S. - Digital manipulation; N = 741
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.79 2.83 21
Unlikely 5-20% 3.24 3.10 23
Somewhat unlikely 20-40% 8.12 7.69 57
Equally likely as unlikely 40-60% 13.81 14.30 106
Somewhat likely 60-80% 16.58 16.33 121
Likely 80-95% 17.74 18.08 134
Very likely > 95% 23.45 23.62 175
I don’t know 12.49 12.15 90
Skipped 1.77 1.89 14
Table B.74: Likelihood in the U.S. - Cyber attacks; N = 745
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.36 2.42 18
Unlikely 5-20% 4.28 3.89 29
Somewhat unlikely 20-40% 8.44 8.59 64
Equally likely as unlikely 40-60% 15.45 15.84 118
Somewhat likely 60-80% 19.22 19.46 145
Likely 80-95% 15.96 15.30 114
Very likely > 95% 20.52 21.21 158
I don’t know 9.70 10.47 78
Skipped 3.07 2.82 21
Table B.75: Likelihood in the U.S. - Surveillance; N = 784
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.70 2.42 19
Unlikely 5-20% 2.92 2.81 22
Somewhat unlikely 20-40% 6.19 6.38 50
Equally likely as unlikely 40-60% 15.23 15.05 118
Somewhat likely 60-80% 18.95 18.75 147
Likely 80-95% 16.03 15.69 123
Very likely > 95% 23.52 24.23 190
I don’t know 12.15 12.12 95
Skipped 2.32 2.55 20
Table B.76: Likelihood in the U.S. - U.S.-China arms race; N = 766
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.24 3.26 25
Unlikely 5-20% 5.98 6.01 46
Somewhat unlikely 20-40% 10.01 10.84 83
Equally likely as unlikely 40-60% 18.74 18.41 141
Somewhat likely 60-80% 20.08 19.71 151
Likely 80-95% 13.17 12.79 98
Very likely > 95% 10.62 11.36 87
I don’t know 15.17 14.62 112
Skipped 3.00 3.00 23
Table B.77: Likelihood in the U.S. - Value alignment; N = 783
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.78 4.21 33
Unlikely 5-20% 7.30 6.90 54
Somewhat unlikely 20-40% 9.01 9.07 71
Equally likely as unlikely 40-60% 20.34 19.54 153
Somewhat likely 60-80% 19.26 19.28 151
Likely 80-95% 13.66 13.79 108
Very likely > 95% 12.96 13.67 107
I don’t know 12.43 12.26 96
Skipped 1.26 1.28 10
Table B.78: Likelihood in the U.S. - Autonomous weapons; N = 757
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 6.22 5.94 45
Unlikely 5-20% 10.36 9.38 71
Somewhat unlikely 20-40% 12.75 12.68 96
Equally likely as unlikely 40-60% 18.91 19.02 144
Somewhat likely 60-80% 15.72 15.72 119
Likely 80-95% 11.44 11.76 89
Very likely > 95% 10.72 11.23 85
I don’t know 11.99 12.29 93
Skipped 1.89 1.98 15
Table B.79: Likelihood in the U.S. - Technological unemployment; N = 738
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.08 2.98 22
Unlikely 5-20% 5.80 5.69 42
Somewhat unlikely 20-40% 11.00 11.11 82
Equally likely as unlikely 40-60% 17.74 17.62 130
Somewhat likely 60-80% 17.16 17.75 131
Likely 80-95% 14.86 14.91 110
Very likely > 95% 15.75 15.99 118
I don’t know 12.84 12.20 90
Skipped 1.75 1.76 13
Table B.80: Likelihood in the U.S. - Critical AI systems failure; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 6.98 6.43 50
Unlikely 5-20% 7.94 7.58 59
Somewhat unlikely 20-40% 12.26 12.98 101
Equally likely as unlikely 40-60% 20.36 20.31 158
Somewhat likely 60-80% 15.59 15.42 120
Likely 80-95% 12.25 11.83 92
Very likely > 95% 9.36 10.15 79
I don’t know 14.85 14.78 115
Skipped 0.41 0.51 4
Table B.81: Likelihood around the world - Hiring bias; N = 760
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.95 3.03 23
Unlikely 5-20% 5.47 5.00 38
Somewhat unlikely 20-40% 8.54 8.55 65
Equally likely as unlikely 40-60% 20.23 21.45 163
Somewhat likely 60-80% 21.55 21.32 162
Likely 80-95% 13.68 13.55 103
Very likely > 95% 12.20 12.11 92
I don’t know 15.04 14.61 111
Skipped 0.35 0.39 3
Table B.82: Likelihood around the world - Criminal justice bias; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 4.44 4.24 33
Unlikely 5-20% 8.06 7.71 60
Somewhat unlikely 20-40% 10.96 10.80 84
Equally likely as unlikely 40-60% 19.17 19.41 151
Somewhat likely 60-80% 18.29 18.25 142
Likely 80-95% 13.09 13.62 106
Very likely > 95% 9.38 9.90 77
I don’t know 16.38 15.94 124
Skipped 0.23 0.13 1
Table B.83: Likelihood around the world - Disease diagnosis; N = 767
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.31 2.35 18
Unlikely 5-20% 4.18 4.17 32
Somewhat unlikely 20-40% 9.93 9.13 70
Equally likely as unlikely 40-60% 21.28 20.99 161
Somewhat likely 60-80% 20.47 20.47 157
Likely 80-95% 15.00 15.38 118
Very likely > 95% 10.94 11.47 88
I don’t know 15.80 15.91 122
Skipped 0.09 0.13 1
Table B.84: Likelihood around the world - Data privacy; N = 807
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.86 2.23 18
Unlikely 5-20% 2.92 2.60 21
Somewhat unlikely 20-40% 8.32 8.30 67
Equally likely as unlikely 40-60% 13.79 14.75 119
Somewhat likely 60-80% 19.07 18.84 152
Likely 80-95% 18.43 18.22 147
Very likely > 95% 21.09 21.81 176
I don’t know 13.34 13.01 105
Skipped 0.19 0.25 2
Table B.85: Likelihood around the world - Autonomous vehicles; N = 796
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.77 3.52 28
Unlikely 5-20% 5.25 5.65 45
Somewhat unlikely 20-40% 12.37 11.68 93
Equally likely as unlikely 40-60% 16.74 17.21 137
Somewhat likely 60-80% 21.09 21.11 168
Likely 80-95% 14.13 14.45 115
Very likely > 95% 12.04 12.19 97
I don’t know 13.99 13.57 108
Skipped 0.63 0.63 5
Table B.86: Likelihood around the world - Digital manipulation; N = 741
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 1.98 2.16 16
Unlikely 5-20% 1.67 1.48 11
Somewhat unlikely 20-40% 7.34 7.29 54
Equally likely as unlikely 40-60% 12.68 12.96 96
Somewhat likely 60-80% 17.18 17.00 126
Likely 80-95% 21.22 21.73 161
Very likely > 95% 22.31 22.00 163
I don’t know 15.24 14.98 111
Skipped 0.39 0.40 3
Table B.87: Likelihood around the world - Cyber attacks; N = 745
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 1.08 1.21 9
Unlikely 5-20% 4.95 4.03 30
Somewhat unlikely 20-40% 4.76 5.10 38
Equally likely as unlikely 40-60% 16.95 16.64 124
Somewhat likely 60-80% 18.94 19.73 147
Likely 80-95% 19.13 19.06 142
Very likely > 95% 20.57 20.40 152
I don’t know 13.20 13.42 100
Skipped 0.42 0.40 3
Table B.88: Likelihood around the world - Surveillance; N = 784
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 1.26 1.40 11
Unlikely 5-20% 3.55 3.19 25
Somewhat unlikely 20-40% 5.12 5.36 42
Equally likely as unlikely 40-60% 14.26 14.41 113
Somewhat likely 60-80% 18.90 19.13 150
Likely 80-95% 20.30 19.77 155
Very likely > 95% 22.62 22.70 178
I don’t know 13.93 13.90 109
Skipped 0.07 0.13 1
Table B.89: Likelihood around the world - U.S.-China arms race; N = 766
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.21 3.13 24
Unlikely 5-20% 4.61 4.83 37
Somewhat unlikely 20-40% 7.70 7.83 60
Equally likely as unlikely 40-60% 19.50 19.19 147
Somewhat likely 60-80% 20.71 20.76 159
Likely 80-95% 14.99 14.75 113
Very likely > 95% 12.46 12.92 99
I don’t know 16.61 16.32 125
Skipped 0.22 0.26 2
Table B.90: Likelihood around the world - Value alignment; N = 783
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.70 2.94 23
Unlikely 5-20% 4.66 4.60 36
Somewhat unlikely 20-40% 8.80 8.81 69
Equally likely as unlikely 40-60% 19.92 19.41 152
Somewhat likely 60-80% 18.97 18.77 147
Likely 80-95% 15.57 15.33 120
Very likely > 95% 14.93 15.71 123
I don’t know 14.44 14.43 113
Skipped 0 0 0
Table B.91: Likelihood around the world - Autonomous weapons; N = 757
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 3.72 3.70 28
Unlikely 5-20% 7.04 5.42 41
Somewhat unlikely 20-40% 9.42 9.64 73
Equally likely as unlikely 40-60% 17.23 17.44 132
Somewhat likely 60-80% 16.08 15.85 120
Likely 80-95% 16.35 17.04 129
Very likely > 95% 14.87 15.19 115
I don’t know 15.20 15.59 118
Skipped 0.09 0.13 1
Table B.92: Likelihood around the world - Technological unemployment; N = 738
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.76 2.57 19
Unlikely 5-20% 4.92 4.47 33
Somewhat unlikely 20-40% 8.31 8.81 65
Equally likely as unlikely 40-60% 18.36 18.16 134
Somewhat likely 60-80% 19.90 21.00 155
Likely 80-95% 14.78 14.50 107
Very likely > 95% 16.71 16.67 123
I don’t know 13.77 13.41 99
Skipped 0.51 0.41 3
Table B.93: Likelihood around the world - Critical AI systems failure; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 5.36 5.27 41
Unlikely 5-20% 8.07 7.97 62
Somewhat unlikely 20-40% 10.75 10.41 81
Equally likely as unlikely 40-60% 18.03 17.87 139
Somewhat likely 60-80% 16.71 16.84 131
Likely 80-95% 13.09 13.11 102
Very likely > 95% 11.23 11.83 92
I don’t know 16.76 16.71 130
Skipped 0 0 0
Table B.94: Issue importance - Hiring bias; N = 760
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 56.86 57.11 434
Somewhat important 22.11 22.76 173
Not too important 6.56 6.05 46
Not at all important 1.50 1.58 12
I don’t know 12.98 12.50 95
Skipped 0 0 0
Table B.95: Issue importance - Criminal justice bias; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 56.08 56.68 441
Somewhat important 21.78 22.49 175
Not too important 6.65 5.91 46
Not at all important 1.83 1.67 13
I don’t know 13.66 13.24 103
Skipped 0 0 0
Table B.96: Issue importance - Disease diagnosis; N = 767
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 55.60 56.98 437
Somewhat important 22.37 21.25 163
Not too important 6.68 6.91 53
Not at all important 1.98 1.83 14
I don’t know 13.26 12.91 99
Skipped 0.11 0.13 1
Table B.97: Issue importance - Data privacy; N = 807
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 63.65 64.93 524
Somewhat important 17.65 17.10 138
Not too important 4.76 4.71 38
Not at all important 1.71 1.36 11
I don’t know 12.05 11.65 94
Skipped 0.19 0.25 2
Table B.98: Issue importance - Autonomous vehicles; N = 796
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 58.70 59.55 474
Somewhat important 22.36 21.73 173
Not too important 6.13 6.28 50
Not at all important 1.44 1.63 13
I don’t know 11.15 10.55 84
Skipped 0.22 0.25 2
Table B.99: Issue importance - Digital manipulation; N = 741
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 57.66 58.30 432
Somewhat important 18.75 18.08 134
Not too important 6.25 6.48 48
Not at all important 3.11 2.97 22
I don’t know 14.16 14.04 104
Skipped 0.08 0.13 1
Table B.100: Issue importance - Cyber attacks; N = 745
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 62.12 61.21 456
Somewhat important 17.80 18.39 137
Not too important 7.07 7.38 55
Not at all important 1.14 1.07 8
I don’t know 11.88 11.95 89
Skipped 0 0 0
Table B.101: Issue importance - Surveillance; N = 784
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 58.54 58.80 461
Somewhat important 19.33 19.26 151
Not too important 6.40 6.63 52
Not at all important 1.73 1.66 13
I don’t know 13.93 13.52 106
Skipped 0.07 0.13 1
Table B.102: Issue importance - U.S.-China arms race; N = 766
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 55.88 55.74 427
Somewhat important 19.44 19.71 151
Not too important 7.07 7.57 58
Not at all important 2.38 2.35 18
I don’t know 15.13 14.49 111
Skipped 0.10 0.13 1
Table B.103: Issue importance - Value alignment; N = 783
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 56.46 56.45 442
Somewhat important 20.49 20.95 164
Not too important 6.69 6.64 52
Not at all important 1.56 1.66 13
I don’t know 14.80 14.30 112
Skipped 0 0 0
Table B.104: Issue importance - Autonomous weapons; N = 757
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 58.32 57.73 437
Somewhat important 20.00 19.55 148
Not too important 5.52 5.94 45
Not at all important 1.23 1.45 11
I don’t know 14.94 15.32 116
Skipped 0 0 0
Table B.105: Issue importance - Technological unemployment; N = 738
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 54.12 54.34 401
Somewhat important 22.07 22.49 166
Not too important 6.50 6.91 51
Not at all important 2.83 2.44 18
I don’t know 14.39 13.69 101
Skipped 0.09 0.14 1
Table B.106: Issue importance - Critical AI systems failure; N = 778
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very important 52.63 53.86 419
Somewhat important 21.10 20.44 159
Not too important 7.98 8.10 63
Not at all important 2.93 2.44 19
I don’t know 15.36 15.17 118
Skipped 0 0 0

B.9 Survey experiment: comparing perceptions of U.S. vs. China AI research and development

[Respondents were presented with one randomly-selected question from the two below.]

QUESTIONS:

  • Compared with other industrialized countries, how would you rate the U.S. in AI research and development?
  • Compared with other industrialized countries, how would you rate China in AI research and development?

ANSWER CHOICES:

  • Best in the world (3)
  • Above average (2)
  • Average (1)
  • Below average (0)
  • I don’t know
Table B.107: Perceptions of research and development - U.S.; N = 988
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Best in the world 9.73 10.02 99
Above average 36.16 37.55 371
Average 26.09 24.70 244
Below average 4.99 4.96 49
I don’t know 23.03 22.77 225
Skipped 0 0 0
Table B.108: Perceptions of research and development - China; N = 1012
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Best in the world 7.33 7.41 75
Above average 45.40 46.64 472
Average 16.66 15.81 160
Below average 3.93 3.66 37
I don’t know 26.68 26.48 268
Skipped 0 0 0

B.10 Survey experiment: U.S.-China arms race

[All respondents were presented with the following prompt.]

We want to understand your thoughts on some important issues in the news today. Please read the short news article below.

Leading analysts believe that an “AI arms race” is beginning, in which the U.S. and China are investing billions of dollars to develop powerful AI systems for surveillance, autonomous weapons, cyber operations, propaganda, and command and control systems.

[Respondents were randomly assigned to one of the four experimental groups listed below.]

B.10.1 Control

[No additional text.]

B.10.2 Nationalism treatment

Some leaders in the U.S. military and tech industry argue that the U.S. government should invest much more resources in AI research to ensure that the U.S.’s AI capabilities stay ahead of China’s. Furthermore, they argue that the U.S. government should partner with American tech companies to develop advanced AI systems, particularly for military use.

According to a leaked memo produced by a senior National Security Council official, China has “assembled the basic components required for winning the Al arms race…Much like America’s success in the competition for nuclear weapons, China’s 21st Century Manhattan Project sets them on a path to getting there first.”

B.10.3 War risks treatment

Some prominent thinkers are concerned that a U.S.-China arms race could lead to extreme dangers. To stay ahead, the U.S. and China may race to deploy advanced military AI systems that they do not fully understand or can control. We could see catastrophic accidents, such as a rapid, automated escalation involving cyber and nuclear weapons.

“Competition for AI superiority at [the] national level [is the] most likely cause of World War Three,” warned Elon Musk, the CEO of Tesla and SpaceX.

B.10.4 Common humanity treatment

Some prominent thinkers are concerned that a U.S.-China arms race could lead to extreme dangers. To stay ahead, the U.S. and China may race to deploy advanced military AI systems that they do not fully understand or can control. We could see catastrophic accidents, such as a rapid, automated escalation involving cyber and nuclear weapons.

“Unless we learn how to prepare for, and avoid, the potential risks, AI could be the worst event in the history of our civilization. It brings dangers, like powerful autonomous weapons,” warned the late Stephen Hawking, one of the world’s most prominent physicists. At the same time, he said that with proper management of the technology, researchers “can create AI for the good of the world.”

[The order of the next two questions is randomized.]

QUESTION:

How much do you agree or disagree with the following statement?

The U.S. should invest more in AI military capabilities to make sure it doesn’t fall behind China’s, even if doing so may exacerbate the arms race. For instance, the U.S. could increase AI research funding for the military and universities. It could also collaborate with American tech companies to develop AI for military use.

ANSWER CHOICES:

  • Strongly agree (2)
  • Somewhat agree (1)
  • Neither agree nor disagree (0)
  • Somewhat disagree (-1)
  • Strongly disagree (-2)
  • I don’t know

QUESTION:

How much do you agree or disagree with the following statement?

The U.S. should work hard to cooperate with China to avoid the dangers of an AI arms race, even if doing so requires giving up some of the U.S.’s advantages. Cooperation could include collaborations between American and Chinese AI research labs, or the U.S. and China creating and committing to common safety standards.

ANSWER CHOICES:

  • Strongly agree (2)
  • Somewhat agree (1)
  • Neither agree nor disagree (0)
  • Somewhat disagree (-1)
  • Strongly disagree (-2)
  • I don’t know
Table B.109: Responses to statement that U.S. should invest more in AI military capabilities - Control; N = 510
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 23.38 24.31 124
Somewhat agree 25.99 25.88 132
Neither agree nor disagree 23.48 22.75 116
Somewhat disagree 8.88 8.82 45
Strongly disagree 4.93 4.71 24
I don’t know 13.34 13.53 69
Skipped 0 0 0
Table B.110: Responses to statement that U.S. should invest more in AI military capabilities - Treatment 1: Pro-nationalist; N = 505
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 20.88 20.40 103
Somewhat agree 26.89 27.52 139
Neither agree nor disagree 21.79 22.18 112
Somewhat disagree 11.69 12.28 62
Strongly disagree 5.30 5.35 27
I don’t know 13.45 12.28 62
Skipped 0 0 0
Table B.111: Responses to statement that U.S. should invest more in AI military capabilities - Treatment 2: Risks of arms race; N = 493
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 18.26 19.07 94
Somewhat agree 27.85 27.38 135
Neither agree nor disagree 21.69 20.28 100
Somewhat disagree 12.87 13.79 68
Strongly disagree 6.88 6.90 34
I don’t know 12.45 12.58 62
Skipped 0 0 0
Table B.112: Responses to statement that U.S. should invest more in AI military capabilities - Treatment 3: One common humanity; N = 492
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 22.38 20.53 101
Somewhat agree 27.29 27.85 137
Neither agree nor disagree 24.37 23.98 118
Somewhat disagree 6.73 7.11 35
Strongly disagree 6.17 6.91 34
I don’t know 13.07 13.62 67
Skipped 0 0 0
Table B.113: Responses to statement that U.S. should work hard to cooperate with China to avoid dangers of AI arms race - Control; N = 510
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 22.34 22.55 115
Somewhat agree 26.16 26.27 134
Neither agree nor disagree 22.02 20.59 105
Somewhat disagree 8.29 9.02 46
Strongly disagree 7.38 7.45 38
I don’t know 13.59 13.92 71
Skipped 0.21 0.20 1
Table B.114: Responses to statement that U.S. should work hard to cooperate with China to avoid dangers of AI arms race - Treatment 1: Pro-nationalist; N = 505
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 18.51 18.81 95
Somewhat agree 27.35 28.12 142
Neither agree nor disagree 20.08 20.99 106
Somewhat disagree 10.09 9.90 50
Strongly disagree 8.45 7.92 40
I don’t know 15.51 14.26 72
Skipped 0 0 0
Table B.115: Responses to statement that U.S. should work hard to cooperate with China to avoid dangers of AI arms race - Treatment 2: Risks of arms race; N = 493
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 24.97 25.96 128
Somewhat agree 25.32 25.15 124
Neither agree nor disagree 21.53 20.49 101
Somewhat disagree 9.83 9.94 49
Strongly disagree 5.84 5.68 28
I don’t know 12.51 12.78 63
Skipped 0 0 0
Table B.116: Responses to statement that U.S. should work hard to cooperate with China to avoid dangers of AI arms race - Treatment 3: One common humanity; N = 492
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 23.63 24.19 119
Somewhat agree 27.52 28.46 140
Neither agree nor disagree 21.31 20.33 100
Somewhat disagree 8.50 7.32 36
Strongly disagree 6.72 6.91 34
I don’t know 12.31 12.80 63
Skipped 0 0 0

B.11 Issue areas for possible U.S.-China cooperation

QUESTION:

For the following issues, how likely is it that the U.S. and China can cooperate?

[Respondents were presented with three issues from the list below. All three issues were presented on the same page; the order that they appeared was randomized.]

  • Prevent AI cyber attacks against governments, companies, organizations, and individuals.
  • Prevent AI-assisted surveillance from violating privacy and civil liberties.
  • Make sure AI systems are safe, trustworthy, and aligned with human values.
  • Ban the use of lethal autonomous weapons.
  • Guarantee a good standard of living for those who lose their jobs to automation.

ANSWER CHOICES:

  • Very unlikely: less than 5% chance (2.5%)
  • Unlikely: 5-20% chance (12.5%)
  • Somewhat unlikely: 20-40% chance (30%)
  • Equally likely as unlikely: 40-60% chance (50%)
  • Somewhat likely: 60-80% chance (70%)
  • Likely: 80-95% chance (87.5%)
  • Very likely: more than 95% chance (97.5%)
  • I don’t know
Table B.117: Likelihood of cooperation with China - Prevent AI cyber attacks against governments, companies, organizations, and individuals; N = 1173
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely 5% 9.20 8.95 105
Unlikely 5-20% 10.26 10.49 123
Somewhat unlikely 20-40% 17.56 17.22 202
Equally likely as unlikely 40-60% 23.55 23.36 274
Somewhat likely 60-80% 13.77 13.73 161
Likely 80-95% 6.98 7.25 85
Very likely > 95% 4.14 4.18 49
I don’t know 14.45 14.75 173
Skipped 0.08 0.09 1
Table B.118: Likelihood of cooperation with China - Prevent AI-assisted surveillance from violating privacy and civil liberties; N = 1140
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely 5% 12.43 12.37 141
Unlikely 5-20% 12.78 13.33 152
Somewhat unlikely 20-40% 19.48 19.74 225
Equally likely as unlikely 40-60% 21.93 20.70 236
Somewhat likely 60-80% 10.59 10.79 123
Likely 80-95% 4.02 4.12 47
Very likely > 95% 3.82 4.12 47
I don’t know 14.87 14.74 168
Skipped 0.08 0.09 1
Table B.119: Likelihood of cooperation with China - Make sure AI systems are safe, trustworthy, and aligned with human values; N = 1226
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely 5% 6.34 6.53 80
Unlikely 5-20% 9.07 8.97 110
Somewhat unlikely 20-40% 16.79 16.88 207
Equally likely as unlikely 40-60% 26.32 25.53 313
Somewhat likely 60-80% 14.84 14.85 182
Likely 80-95% 7.35 7.26 89
Very likely > 95% 5.77 5.87 72
I don’t know 13.38 13.95 171
Skipped 0.14 0.16 2
Table B.120: Likelihood of cooperation with China - Ban the use of lethal autonomous weapons; N = 1226
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely 5% 12.28 12.32 151
Unlikely 5-20% 11.14 10.85 133
Somewhat unlikely 20-40% 14.03 14.03 172
Equally likely as unlikely 40-60% 23.98 23.65 290
Somewhat likely 60-80% 10.15 10.60 130
Likely 80-95% 6.67 6.93 85
Very likely > 95% 5.69 5.46 67
I don’t know 15.91 15.99 196
Skipped 0.14 0.16 2
Table B.121: Likelihood of cooperation with China - Guarantee a good standard of living for those who lose their jobs to automation; N = 1235
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely 5% 13.19 13.36 165
Unlikely 5-20% 13.01 13.28 164
Somewhat unlikely 20-40% 18.26 18.46 228
Equally likely as unlikely 40-60% 22.81 22.19 274
Somewhat likely 60-80% 9.46 9.39 116
Likely 80-95% 5.08 5.18 64
Very likely > 95% 4.27 4.53 56
I don’t know 13.78 13.44 166
Skipped 0.14 0.16 2

B.12 Trend across time: job creation or job loss

QUESTION:

How much do you agree or disagree with the following statement?

[Respondents were presented with one statement randomly selected from the list below.]

  • In general, automation and AI will create more jobs than they will eliminate.
  • In general, automation and AI will create more jobs than they will eliminate in 10 years.
  • In general, automation and AI will create more jobs than they will eliminate in 20 years.
  • In general, automation and AI will create more jobs than they will eliminate in 50 years.

ANSWER CHOICES:

  • Strongly agree (2)
  • Agree (1)
  • Disagree (-1)
  • Strongly disagree (-2)
  • I don’t know
Table B.122: Responses to statement that automation and AI will create more jobs than they will eliminate - No time frame; N = 484
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 6.37 6.82 33
Agree 20.19 18.18 88
Disagree 27.39 28.10 136
Strongly disagree 21.43 22.31 108
Don’t know 24.45 24.38 118
Skipped 0.17 0.21 1
Table B.123: Responses to statement that automation and AI will create more jobs than they will eliminate - 10 years; N = 510
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 3.40 3.53 18
Agree 17.67 18.04 92
Disagree 30.03 29.02 148
Strongly disagree 22.85 23.92 122
Don’t know 26.04 25.49 130
Skipped 0 0 0
Table B.124: Responses to statement that automation and AI will create more jobs than they will eliminate - 20 years; N = 497
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 3.69 4.02 20
Agree 17.82 17.10 85
Disagree 31.02 30.99 154
Strongly disagree 21.31 21.73 108
Don’t know 25.98 25.96 129
Skipped 0.18 0.20 1
Table B.125: Responses to statement that automation and AI will create more jobs than they will eliminate - 50 years; N = 509
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly agree 6.77 6.48 33
Agree 15.37 15.52 79
Disagree 35.35 35.56 181
Strongly disagree 18.82 18.27 93
Don’t know 23.69 24.17 123
Skipped 0 0 0

B.13 High-level machine intelligence: forecasting timeline

QUESTION:

The following questions ask about high-level machine intelligence. We have high-level machine intelligence when machines are able to perform almost all tasks that are economically relevant today better than the median human (today) at each task. These tasks include asking subtle common-sense questions such as those that travel agents would ask. For the following questions, you should ignore tasks that are legally or culturally restricted to humans, such as serving on a jury.

In your opinion, how likely is it that high-level machine intelligence will exist in 10 years? 20 years? 50 years? For each prediction, please use the slider to indicate the percent chance that you think high-level machine intelligence will exist. 0% chance means it will certainly not exist. 100% chance means it will certainly exist.

______ In 10 years?

______ In 20 years?

______ In 50 years?

ANSWER CHOICES:

  • Very unlikely: less than 5% chance (2.5%)
  • Unlikely: 5-20% chance (12.5%)
  • Somewhat unlikely: 20-40% chance (30%)
  • Equally likely as unlikely: 40-60% chance (50%)
  • Somewhat likely: 60-80% chance (70%)
  • Likely: 80-95% chance (87.5%)
  • Very likely: more than 95% chance (97.5%)
  • I don’t know
Table B.126: Forecasting high-level machine intelligence - 10 years; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 4.46 4.50 90
Unlikely 5-20% 8.19 8.20 164
Somewhat unlikely 20-40% 14.84 14.75 295
Equally likely as unlikely 40-60% 20.34 19.95 399
Somewhat likely 60-80% 21.08 21.25 425
Likely 80-95% 10.69 10.65 213
Very likely > 95% 7.40 7.85 157
I don’t know 12.91 12.75 255
Skipped 0.09 0.10 2
Table B.127: Forecasting high-level machine intelligence - 20 years; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 1.52 1.45 29
Unlikely 5-20% 2.73 2.95 59
Somewhat unlikely 20-40% 6.26 5.85 117
Equally likely as unlikely 40-60% 16.83 16.40 328
Somewhat likely 60-80% 18.17 18.65 373
Likely 80-95% 22.25 22.25 445
Very likely > 95% 17.91 18.30 366
I don’t know 14.18 14.00 280
Skipped 0.15 0.15 3
Table B.128: Forecasting high-level machine intelligence - 50 years; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Very unlikely < 5% 2.28 2.30 46
Unlikely 5-20% 1.66 1.55 31
Somewhat unlikely 20-40% 2.75 2.75 55
Equally likely as unlikely 40-60% 10.08 9.90 198
Somewhat likely 60-80% 12.33 12.20 244
Likely 80-95% 14.43 14.50 290
Very likely > 95% 40.86 41.15 823
I don’t know 15.52 15.55 311
Skipped 0.09 0.10 2

B.14 Support for developing high-level machine intelligence

QUESTION:

How much do you support or oppose the development of high-level machine intelligence?

ANSWER CHOICES:

  • Strongly support
  • Somewhat support
  • Neither support nor oppose
  • Somewhat oppose
  • Strongly oppose
  • I don’t know
Table B.129: Support for developing high-level machine intelligence; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Strongly support 7.78 8.10 162
Somewhat support 23.58 23.30 466
Neither support nor oppose 29.40 28.75 575
Somewhat oppose 16.19 16.60 332
Strongly oppose 11.02 11.10 222
I don’t know 11.94 12.05 241
Skipped 0.09 0.10 2

B.15 Expected outcome of high-level machine intelligence

QUESTION:

Suppose that high-level machine intelligence could be developed one day. How positive or negative do you expect the overall impact of high-level machine intelligence to be on humanity in the long run?

ANSWER CHOICES:

  • Extremely good
  • On balance good
  • More or less neutral
  • On balance bad
  • Extremely bad, possibly human extinction
  • I don’t know
Table B.130: Expected outcome of high-level machine intelligence; N = 2000
Answer choices Percentages (weighted) Percentages (unweighted) Raw frequencies
Extremely good 5.35 5.45 109
On balance good 21.28 21.25 425
More or less neutral 21.00 21.10 422
On balance bad 22.38 23.10 462
Extremely bad, possibly human extinction 11.66 11.55 231
Don’t know 18.25 17.45 349
Skipped 0.09 0.10 2

  1. For this and other questions that ask respondents about likelihoods, each multiple-choice answer was coded to the mean value across the probabilities in the answer’s range.