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This bias often stems from training data that reflects historical and systemic inequalities. For example, AI systems used in hiring, law enforcement, or healthcare may disproportionately disadvantage certain racial groups by reinforcing existing stereotypes or underrepresenting them in key areas.
It is difficult for people to determine if such decisions are fair and trustworthy, leading potentially to bias in AI systems going undetected, or people rejecting the use of such systems. This has led to advocacy and in some jurisdictions legal requirements for explainable artificial intelligence. [69]
Therefore, we call on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4. This pause should be public and verifiable, and include all key actors. If such a pause cannot be enacted quickly, governments should step in and institute a moratorium.
Biases in AI algorithms and methods that lead to discrimination are causes for concern among many activist organizations and academic institutions. Recommendations include increasing diversity among creators of AI algorithms and addressing existing systemic bias in current legislation and AI development practices. [40] [42]
"Right now, AI is like a steam engine, which was quite disruptive when introduced to society," he said in a recent video. He then used a different metaphor, saying it will evolve in a few years to ...
AI and AI ethics researchers Timnit Gebru, Emily M. Bender, Margaret Mitchell, and Angelina McMillan-Major have argued that discussion of existential risk distracts from the immediate, ongoing harms from AI taking place today, such as data theft, worker exploitation, bias, and concentration of power. [139]
Potential agent gotchas include use of copyrighted data in AI models, bias, and hallucinations. So, project leaders must be attentive to safeguards, governance, regulations and best practices in ...
Automation bias can be a crucial factor in the use of intelligent decision support systems for military command-and-control operations. One 2004 study found that automation bias effects have contributed to a number of fatal military decisions, including friendly-fire killings during the Iraq War. Researchers have sought to determine the proper ...