Digital Trust in Everyday Online Life 2025

This page summarises findings from the Human Clarity Institute’s Digital Life 2025 dataset, based on 1,003 responses across six English-speaking countries. The analysis focuses on the signals people rely on when deciding whether information is trustworthy, and how those signals shape everyday belief decisions in digital environments.

The findings capture how trust operates in modern digital environments, where people must decide what to believe across multiple sources, formats, and contexts. Rather than focusing on uncertainty or behaviour, this page examines the core signals people use to filter information.

View the Digital Life 2025 Dataset

What the data shows

Three signals stand out in this dataset: clear evidence remains the most important factor when deciding what to believe, trusted sources such as experts continue to play a key role, and belief decisions are shaped by identifiable signals rather than automatic trust. Together, these findings suggest that everyday digital trust is guided by filtering rules rather than passive acceptance.

Overall, the data show that trust in everyday digital life is not based on blind belief. Instead, people rely on identifiable signals such as evidence and trusted expertise when deciding what to accept as true.

By the numbers (from HCI data)

Patterns observed in the data

Evidence acts as the primary decision filter

The most consistent signal across respondents is reliance on clear facts and evidence. This suggests that despite uncertainty in digital environments, people still anchor belief decisions to tangible information rather than source alone.

Trust is guided by recognised expertise

Experts remain the most trusted group, indicating that credibility is still linked to perceived knowledge and authority. However, this trust is not universal and competes with other signals.

Trust decisions rely on multiple signals rather than a single source

The absence of a universally trusted source suggests that people combine signals — such as evidence, expertise, and context — when deciding what to believe.

Confidence in judging content is present but not absolute

Moderate confidence in identifying AI-generated content suggests that people feel capable of judging information, but not with complete certainty.

No single source dominates trust decisions

While experts are the most trusted group, no single source is relied on universally. This suggests that people combine multiple signals when deciding what to believe online.

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Methodology

This dataset forms part of the Human Clarity Institute’s Human–AI Experience research programme, examining how people experience life in digitally mediated environments shaped by AI, online systems, and modern information conditions. The study uses a cross-sectional online survey design and focuses on descriptive patterns in the attitudes, behaviours, and experiences captured on this summary page.

Data were collected on 10 September 2025 via the Prolific research platform from adults across six English-speaking countries. Participants provided explicit informed consent for anonymised data publication as part of HCI’s open research programme.

Sampling & participants

• Clean dataset: 1,003 valid responses
• Countries: United Kingdom, United States, Canada, Australia, Ireland, New Zealand
• Eligibility: Adults (18+) fluent in English
• Recruitment platform: Prolific

Participants were recruited using platform screening filters. The resulting dataset should be interpreted as a non-probability convenience sample and is not intended to represent national populations.

The cleaned dataset, variable dictionary, and reuse terms are publicly available through the HCI dataset repository: Digital Life 2025 Dataset →

Data integrity

All percentages reported on this page are calculated from valid responses in the cleaned dataset (n = 1,003). Percentages are rounded to the nearest whole number for readability.

Where multiple response options are possible, percentages represent the share of participants selecting each option. Totals may exceed 100% because respondents could select more than one response.

Counts and percentages shown in hero statistics, numerical highlights, question-and-answer sections, and thematic summaries are based directly on the cleaned Digital Life 2025 dataset. Minor differences between totals may occur due to rounding.

This dataset is exploratory and descriptive in nature. It does not support causal inference and results should be interpreted as observed patterns within the survey sample.

This dataset is released as open research to support transparent analysis of human experience in the digital and AI era.

Suggested citation:
Human Clarity Institute. (2025). Digital Life 2025 (Dataset). Human Clarity Institute.
DOI: https://doi.org/10.5281/zenodo.17393880

Data use and reuse terms are outlined in our Data Use & Disclaimer.