Featured In

Jane Phillips

From the sales floor to the academic podium, through the fast-paced world of AI and tech startups, my journey is fueled by a love for understanding how people and technology intersect in the modern workplace.

  • “Although the LLM's had varied results, GPT-4 outperformed most of the student population, faking on average better than 99.6 % of the student population on Likert-type measures, and 91.78 % better than the student population on the forced-choice measures.”

    Phillips, J., & Robie, C. (2024a). Can a computer outfake a human? Personality and Individual Differences, 217, 112434. https://doi.org/10.1016/j. paid.2023.112434

  • Putting the wrong person in a job is a huge risk for organizations: the increased turnover training that they’re investing in hiring decisions can cost an organization a lot of money and time and resources, so inaccurate measures would increase the likelihood of hiring the wrong person and candidates might think, ‘i can use an llm to make my score on this assessment better,’ but that doesn’t really help the individual or the organization.” Canadian HR Reporter. (2023, November 15). Do hiring managers have to worry about faked personality tests?

    Phillips, J., & Robie, C. (2024a). Can a computer outfake a human? Personality and Individual Differences, 217, 112434. https://doi.org/10.1016/j. paid.2023.112434

  • “LLMs, particularly ChatGPT models, demonstrated the ability to produce high scores on personality assessments, often outperforming human participants. Since LLMs are increasingly easily accessed and provide responses to text prompts within seconds, these findings underscore the potential for LLMs to manipulate out- comes in high-stakes scenarios such as job selection processes.”

    Phillips, J., & Robie, C. (2024b). Hacking the perfect score on high-stakes personality assessments with generative AI. Personality and Individual Differences, 231, 112840. https://doi.org/10.1016/j.paid.2024.112840