whistleblowing in AI
Whistleblowing in AI refers to the act of reporting or exposing unethical or illegal practices related to artificial intelligence technologies. It involves individuals within an organization or industry coming forward with information about wrongdoing, but can also include highlighting unintended consequences of design or policy choices.
The related discussion of critical big data literacy highlights the importance of being aware of and critically analyzing the ethical implications and potential harm associated with big data and AI technologies. To be appropriate, whistleblowing must be neither inaccurate/alarmist nor complacent, and this requires that individuals have a comprehensive understanding of how these technologies work, their potential biases and limitations, and their impact on society.
A commitment to prospective, forward-looking responsibility arguably entails encouraging discussions about whistleblowing in AI as part of critical big data literacy, to encourage a deeper understanding of the potential risks and ethical concerns associated with AI systems. This knowledge can help them identify situations where whistleblowing may be necessary to address these issues and advocate for responsible and ethical use of AI technologies.
But it also requires institutional designs that foster accountability and transparency.
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