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What is the role of ethics in a machine learning engineer's job?
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AI ethics are the set of guiding principles that stakeholders (from engineers to government officials) use to ensure artificial intelligence technology is developed and used responsibly. This means taking a safe, secure, humane, and environmentally friendly approach to AI. 

A strong AI code of ethics can include avoiding bias, ensuring the privacy of users and their data, and mitigating environmental risks. Codes of ethics in companies and government-led regulatory frameworks are two main ways that AI ethics can be implemented. By covering global and national ethical AI issues, and laying the policy groundwork for ethical AI in companies, both approaches help regulate AI technology.

More broadly, the discussion around AI ethics has progressed from being centered around academic research and non-profit organizations. Today, big tech companies like IBM, Google, and Meta have assembled teams to tackle ethical issues that arise from collecting massive amounts of data. At the same time, government and intergovernmental entities have begun to devise regulations and ethics policies based on academic research.