These are three of the biggest problems facing today's AI

10/23/2016

This article discusses the limitations and drawbacks of artificial intelligence (AI) and deep learning technology. It highlights the challenges faced by AI systems in areas such as language understanding, contextual comprehension, and inference-making. The article also points out the risks associated with over-reliance on machine learning algorithms and the potential biases that can be ingrained in AI systems. It emphasizes the importance of human supervision and intervention to ensure the ethical use and decision-making of AI. Overall, the article provides a critical examination of the current state and potential pitfalls of AI and deep learning.

artificial intelligence ꞏ deep learning ꞏ limitations ꞏ drawbacks ꞏ machine learning ꞏ neural networks ꞏ algorithm ꞏ data bias ꞏ interpretability ꞏ black box ꞏ automation ꞏ decision-making ꞏ ethics ꞏ bias in ai ꞏ fairness ꞏ transparency ꞏ accountability ꞏ technology ꞏ future of ai ꞏ machine intelligence ꞏ ai limitations ꞏ ai challenges ꞏ computational limitations ꞏ ethical concerns ꞏ algorithmic bias ꞏ ai ethics ꞏ ai governance ꞏ ai impact ꞏ ai risks ꞏ ai accountability ꞏ ai transparency ꞏ ai decision-making ꞏ ai bias ꞏ ai interpretability ꞏ ai explainability ꞏ ai fairness ꞏ ai regulation ꞏ ai oversight