Software Developers on Climate Change, AI, and Sustainable Software: A survey of GitHub users, Summer 2026


Appendix II. Survey Method

Sample

The survey was administered online in English to a sample of GitHub users in the 50 U.S. states and the District of Columbia. Invitations were sent by email to a random sample of GitHub monthly active users who had previously opted in to receive marketing communications from GitHub. Fielding dates: June 30 – August 9, 2026.

A total of 1,217 people submitted the survey. Two exclusions were applied before analysis: 1) Respondents who completed less than 75% of the questionnaire (fewer than 8 out of 29 questions) were removed; 2) Respondents who finished in less than one-third of the median completion time — a median of 4 minutes, giving a threshold of 1:20 — were also removed as likely inattentive. After these exclusions, 1,039 respondents remained, and all results in this report are based on that analytic sample. 

As a thank-you for participation, four respondents were selected at random to receive a $100 reward (deliverable as a gift card, prepaid cash card, or charity donation via BHN Rewards).

Sampling frame and interpretation

Because the sample was drawn from GitHub monthly active users who had opted in to marketing emails, this is a non-probability sample of an already self-selected population. Estimates in this report describe respondents to this survey and should not be interpreted as unbiased estimates of the U.S. software developer population or of GitHub users more broadly. Respondents who opted in to marketing communications may differ systematically from GitHub users who did not, and respondents who chose to complete the survey may differ from those who did not, including on the topics measured here.

Comparisons to the U.S. general population

Where estimates from this survey are compared to Climate Change in the American Mind (CCAM), the CCAM estimates are drawn from a nationally representative online sample of U.S. adults recruited via Ipsos’ KnowledgePanel using a combination of random-digit-dial and address-based sampling, weighted to U.S. Census Bureau parameters for age, gender, race, income, education, and region. The most recent CCAM wave was fielded April 17-26, 2026 (n = 1,068). Because the GitHub survey is not a probability sample and is not weighted to any external benchmark, differences between the two samples reflect a combination of population differences and design differences.

 

Questionnaire and measures

Items on global warming happening, human cause, worry, perceived personal harm, perceived harm to future generations, and personal importance are drawn from Climate Change in the American Mind (CCAM) survey, including the Six Americas Super Short Survey (SASSY). Item wording matches the CCAM wave described above to allow direct comparison. The survey instrument was designed by Paull Young and Grace Vorreuter of GitHub and Anthony Leiserowitz, Marija Verner, and Jennifer Marlon of Yale University, and was programmed by Grace Vorreuter of GitHub. The figures and tables were constructed by Emily Goddard of Yale University. Jennifer Carman and Seth Rosenthal of Yale University contributed to the report through editorial and quality review.

Rounding

Percentage points are rounded to the nearest whole number for tabulation purposes, and summed categories (e.g., “very worried” + “somewhat worried”) are rounded after the sums are calculated (e.g., 41.4% + 37.2% = 78.6%, which appears in this report as 79%). As a result, a combined percentage reported in the text may differ by one point from the sum of the rounded category percentages shown in a figure, and percentages in a given figure may total slightly higher or lower than 100%.

Ethics

Participation was voluntary and respondents provided informed consent. Contact information collected for the sweepstakes drawing was stored separately from survey responses and was not linked to individual response data for analysis.

Data availability

Aggregated topline results are provided in the current report. Individual-level microdata are not publicly available in order to protect respondent confidentiality. Requests for additional analyses should be directed to the authors.