Unveiling the Dangers of Common AI Technology: A Must-Read Guide
Published on: March 10, 2024
The recent turmoil at OpenAI, including the firing and rehiring of CEO Sam Altman, has intensified discussions around AI safety, particularly in the context of Artificial General Intelligence (AGI). However, Anjana Susarla from Michigan State University points out that the focus on AGI overlooks the more immediate and pervasive impact of AI in everyday life.
While AI is widely recognized in its roles in digital assistants and social media algorithms, it also significantly influences more discreet areas such as job hiring processes, loan approvals, medical diagnostics, and criminal justice. These instances of AI, often unnoticed, can have profound impacts on individuals' lives.
The risks associated with AI are not just speculative but real, particularly regarding biases. AI systems can inherit biases from training data, as seen in resume screening tools biased against women. Similarly, predictive methods in healthcare and child welfare could exhibit biases leading to unequal assessments across different social groups.
Proxy discrimination in AI poses another significant risk, where characteristics correlated with legally protected attributes like race influence algorithmic decisions, resulting in unequal outcomes. Misinterpretation or misuse of AI outputs can also lead to harmful decisions, such as the erroneous association of asthma with lower pneumonia mortality risk in a neural network model.
The Biden administration's executive order and the Federal Trade Commission's enforcement efforts mark initial steps toward recognizing and safeguarding against these algorithmic harms. However, as AI technologies like large language models become more integrated into daily activities, there is a pressing need to scrutinize these systems for biases and ensure conformity with transparency and accuracy standards.
In conclusion, the challenges posed by AI are not confined to futuristic scenarios of superintelligence but are present in the widespread use of AI in current societal systems. Understanding and mitigating the vulnerabilities in algorithmic decision-making is crucial for ensuring equitable outcomes and safeguarding those most at risk from these technologies.