Focusing on Tackling Algorithmic Bias is Key to Ethical AI … – Fagen wasanni

AI ethicist Alice Xiang argues that while killer robots and superintelligence may be concerns for the future, the immediate and insidious harms being caused by artificial intelligence (AI) lie in algorithmic biases and inequalities. Xiang emphasizes the need to address existing biases in AI systems that entrench societal biases and perpetuate inequalities. Biased algorithms have been found to discriminate against marginalized groups such as women and people of color, often due to skewed training data. Xiang warns that as AI becomes more pervasive in high-stakes domains like healthcare, employment, and law enforcement, these biases can compound and create a more unequal society.

Xiang suggests that it is crucial to prioritize addressing these algorithmic biases over speculative long-term threats. She believes that preventing existential threats is achieved by identifying and mitigating the concrete harms that currently exist. Despite efforts by industry players to establish ethical practices for AI development, algorithmic bias remains a persistent problem that has not been systematically fixed. Xiang highlights incidents like Googles mislabelling of photos and biased recruitment algorithms as examples of ongoing bias in AI systems.

Xiang also raises concern about the representational biases found in generative AIs, which reproduce stereotypes present in the training data. She points out that if image generators are biased, it can influence creators who use them for inspiration in creative fields. Efforts to prevent these harms are still in the early stages, with companies relying on varying levels of self-governance due to the lack of comprehensive government oversight.

To address these issues, Xiang emphasizes the need for companies to prioritize AI ethics from the early stages of development. She calls for increased investment in the underfunded field of AI ethics to ensure that developers have the necessary knowledge and tools to address biases and make ethical decisions. By focusing on tackling algorithmic bias, the industry can work towards developing more ethical AI systems that serve all members of society.

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Focusing on Tackling Algorithmic Bias is Key to Ethical AI ... - Fagen wasanni