Most Americans don’t have strong feelings about the impact of technology on their family life, but they worry about the effects of online pornography and social media on young people.
In the midst of debates about the ways technology is affecting families and relationships, we asked Americans to evaluate how smartphones, social media, or artificial intelligence have affected their family life. Perhaps the most striking finding is that many Americans do not lean in either a positive or negative direction. Half or more say social media and AI are neither positive nor negative, and just over one-third say the same for smartphones. This could indicate ambivalence or uncertainty, but because a large percentage of Americans choose this middle ground, none of the three forms of technology is seen as mostly positive or mostly negative by a majority of Americans.
Among those who take a position, opinions of AI are balanced — 22% evaluate it as positive and 21% evaluate it as negative. For social media, however, negative views outweigh positive by more than 2 to 1 (34% vs. 15%). The only form of technology judged as a net plus for family life is the smartphone, where 37% considered its influence to be positive compared with 28% seeing it as a negative for families.
Americans with and without children under 18 at home feel very negatively about social media, but those with children at home are also more likely to say it is a positive (19%). Parents of minor children are also much more positive about the role of AI. These parents are, however, evenly divided about smartphones, while those without young children in the home tend to be slightly more positive than negative about the role smartphones can play for families. One possible interpretation of the difference in positivity toward smartphones is that they facilitate communication with adult children and extended families, while for families with younger children at home, they could be a source of contention.
All age groups judge smartphones to be a more positive influence than the other technologies. In contrast, opinions about social media and AI vary significantly by age. Young people evaluate AI far more positively than older respondents — the difference between the youngest and oldest age groups is 22 percentage points. Respondents under 30 also evaluate social media much more positively than other age groups, though it is seen as the least positive type of technology by young respondents, with less than one-quarter judging it to be positive. Those over 65 evaluate social media as a slightly more positive force than artificial intelligence, though the percentage reporting positive sentiments about either technology was low.
Evaluations of smartphones and social media also vary by partisanship. Democrats report more positive views than Republicans of both smartphones and social media. Independents are the least enthusiastic group about both forms of technology. By contrast, one point of partisan agreement is evaluations of AI, with only around 20% of Democrats, independents, and Republicans reporting positive views. Given how new this technology is, however, it may be that Americans’ views of its role in family life will change as more gain experience with it.
In addition to asking about the effects of technology on family life generally, we also focused on public views of how various forms of technology affect young people in particular.
Americans have relatively straightforward views of how two types of technology affect children: They are extremely concerned about online pornography and are at least somewhat concerned about social media. The number of Americans who say pornography has a “very” negative effect is at a supermajority level. Combining the “very” and “somewhat” negative responses, 81% see pornography’s impact in negative terms. A majority also view social media this way, with 73% saying its impact is either “very” or “somewhat” negative. But the pattern of responses is different. Only a third of the country is “very” negative on social media, with four in 10 in the “somewhat” negative category. People may see some redeeming qualities in social media that prevent the most negative responses.
For both of these forms of technology, people have crystallized ideas about how they affect young people: very few have neutral (neither positive nor negative) evaluations. For social media, this pattern is notable in comparison to the half of Americans who said that social media’s effects on family life were neither positive nor negative. Americans may be ambivalent about social media’s role when asked to consider the family as a whole, but they believe it is a negative force when asked to think about young people specifically.
By comparison, artificial intelligence (AI) and video games are in a different category with around four in 10 Americans simply neutral on the technology’s impact on young people. True, 50% of the country sees AI in negative terms and more than 40% see video games as a negative, but the model response for those two forms of technology is still neutrality on this scale.
Overall, the public is clearly concerned about each of these technologies, broadly seeing all of them as more negative than positive influences in the lives of young people. But the unambiguous major concern is pornography; the secondary concern is social media; and there is trailing concern for artificial intelligence and video games. People put them in different categories, and so should policymakers if they want to follow public opinion.
This overall pattern changes very little by demographic. It is consistent across partisanship and other factors like income or race. One might think age would play a role in defining how people think about these issues, with younger cohorts less worried about the impact of technology, yet that is broadly not true. Consider AI: regardless of age, the neutral category is the most prominent for all partisan groups — Democrats, Republicans and pure independents.
The one group where the modal response is higher for “very negative” than for “neutral” is among young Democrats when considering AI. Thirty-one percent of them are very negative, with just 27% neutral. In all other cases the basic pattern holds. Similar results hold across other demographic groups as well.
Americans also do not distinguish between the impact of these technologies on young men vs. young women. In both the media and, to some degree, the literature on family policy, there is generally more concern about young men relative to pornography and young women relative to social media. To test this among the American public, we performed an experiment that altered the stem of the question to ask about “young people,” “young men,” or “young women.”
The numbers move lightly in the expected directions, but not at levels that suggest deep differences in how people see the impact on young men and young women. Sixty percent of people are very worried about pornography for young men, but 55% say the same thing about young women. The difference when it comes to the impact of social media on young men vs. young women is not even statistically significant at just two percentage points, and the difference in concern about AI is only three percentage points. Americans do seem slightly more concerned about the effects of video games on young men than young women, though the overall percentages who have very negative views about this form of technology are low.
Given the high level of concern about the effects of online pornography on young people, what do Americans want done about this issue?
We explore a broader set of policy options and parental actions to regulate children’s access to technology elsewhere and find considerable support for guardrails to help manage the impact of technology on children in a digital world. But here we focus on the specific question of age verification for online pornography.
Overall, 77% of Americans strongly support age verification, though there are some age differences that are also tied to partisanship. Younger Democrats are the group most likely to be leery of insisting on age verification for pornography. Among the oldest generation, about three-quarters “strongly support” this type of regulation, and support clearly does fall off some among younger groups. However, even among young Democrats, the modal answer is still to favor age verification: 37% strongly favor it, and a majority (56%) favor it overall. While it is possible to find age differences, the overwhelming preference is to age-gate pornography.
It is common to look for areas where the parties disagree in American public life — and, of course, there are numerous examples. However, the impact of technology on young people is an area where agreement is fairly clear: Americans speak with a loud and consistent voice about the harm online pornography can do to minors, and they strongly favor government regulation to enforce age limits. Most Americans also worry about the harms of social media, though their concern is somewhat less emphatic compared to pornography.
When asked to consider the effects of technologies like AI, social media, or smartphones on family life generally — not just on young people — we tend to see far higher levels of ambivalence or uncertainty. Our data suggest that more Americans believe smartphones benefit their families than harm them, a result that is especially striking, given that other technologies like social media or AI are also accessible via smartphones. Nonetheless, it is clear that many Americans are still in the process of coming to grips with the role of technology in their family lives.
METHODOLOGY NOTE
Between August 6-18, 2025, YouGov interviewed 3317 nationally representative respondents who were then matched down to a sample of 3000 to produce the final dataset. The respondents were matched to a sampling frame on gender, age, race, and education. The frame was constructed by stratified sampling from the full 2023 American Community Survey (ACS) one-year sample with selection within strata by weighted sampling with replacements (using the person weights on the public use file).
The matched cases were weighted to the sampling frame using propensity scores. The matched cases and the frame were combined and a logistic regression was estimated for inclusion in the frame. The propensity score function included age, gender, race/ethnicity, years of education, region, and home ownership. The propensity scores were grouped into deciles of the estimated propensity score in the frame and post-stratified according to these deciles.
The weights were then post-stratified on 2020 and 2024 presidential vote choice as well as a four-way stratification of gender, age (four categories), race (four categories), and education (four categories) to produce the final weight. The overall margin of error is +/- 2.1%.