A new study examining gender differences in AI literacy workshop outcomes reveals distinct patterns in how male and female secondary students engage with artificial intelligence and deepfakes. The research, conducted among Australian students in Years 7, 8, and 10 from two co-educational government schools, highlights the need for gender-responsive curriculum design to address equity in AI education and safety awareness.
Study Design and Key Findings
The study, titled "Gender Differences in AI Literacy Workshop Outcomes and Deepfake Engagement" (arXiv:2606.14718), analyzed data from 199 students pre-workshop and 136 post-workshop who participated in a one-day AI literacy workshop. Using statistical regression methods controlling for year level and school, the researchers uncovered several significant gender-differentiated patterns.
Before the workshop, male students reported significantly higher STEM career interest across all three domains: AI, computer science, and engineering. In contrast, female students were significantly more likely to use AI for schoolwork and to seek advice from AI tools. Notably, males were significantly more likely to have created or shared deepfake content.
After the workshop, both genders improved in AI knowledge. However, female students showed a richer profile of gains: wider conceptual understanding, greater confidence, and meaningful increases in AI and computer science career interest that partially narrowed the gender STEM gap.
| Metric | Male Students (Pre-Workshop) | Female Students (Pre-Workshop) | Post-Workshop Change |
|---|---|---|---|
| STEM career interest (AI, CS, Engineering) | Significantly higher | Lower | Females increased, narrowing gap |
| AI use for schoolwork | Lower | Significantly higher | Not reported |
| Deepfake creation/sharing | Significantly higher | Lower | Not reported |
| AI knowledge gain | Improved | Improved | Females: broader conceptual gains |
| Confidence in AI | Not specified | Greater post-workshop gains | Females: meaningful increases |
Implications for AI Literacy and Safety
The study's authors argue that these findings highlight the need for gender-responsive AI curricula, particularly deepfake safety education for male students. The results also demonstrate that even single-day workshops can narrow gender gaps in STEM aspirations and AI confidence.
"These findings highlight the need for gender-responsive AI curricula, particularly deepfake safety education for male students," the researchers stated. They added that the one-day intervention showed meaningful improvements for female students, including "greater confidence" and "increases in AI and CS career interest."
Broader Context for Enterprise Leaders
While the study focused on secondary education, the implications extend to the technology workforce of tomorrow. Enterprise leaders responsible for AI adoption and talent development should note that gender differences emerge early in AI engagement. Female students' higher propensity to use AI for schoolwork and seek AI advice suggests a natural affinity that could be nurtured into future technical roles. Meanwhile, male students' higher rate of deepfake creation underscores the need for ethics and safety training in any AI literacy program, whether in schools or corporate training.
The findings also reinforce the value of structured, short-duration interventions—such as workshops—in building AI literacy and broadening STEM participation. For companies investing in internal AI upskilling, these insights could inform more inclusive program design.
Methodology and Source
The study was conducted by researchers Renzella, Jake, Bergh, Christian, Banks, Natasha, and Vassar, Alexandra, and posted on arXiv under the identifier 2606.14718. The paper is published under a Creative Commons Attribution 4.0 International license. All statistics cited here come directly from the abstract and full text of the paper.
