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This characterization shows that AI introduces pressures beyond learning and using new tools, affecting how software professionals perform and remain accountable for technical work and how they prepare for the future of their careers.
Access to code generation via AI may rise, but control over software development is likely to become more exclusive, favoring those with deep expertise.
Software engineers are increasingly dependent on LLMs, risking overreliance that could undermine traditional practices like peer consultation and documentation.
AI-generated responses can subtly distort qualitative survey findings, challenging the reliability of participant insights in software engineering research.
Many software engineering studies rely on fewer than 12 interviews, raising questions about the rigor of qualitative research in the field.
Forget standalone ethics modules – embedding empathy directly into core software engineering tasks is key to building responsible AI.
