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One example is coding of workers' compensation claims, which are submitted in a prose narrative form and must manually be assigned standardized codes. AI is being investigated to perform this task faster, more cheaply, and with fewer errors. [16] [17] AI‐enabled virtual reality systems may be useful for safety training for hazard recognition ...
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. [133]
Multiple essayists state that artificial general intelligence is still two to four decades away. Most of the essayists advice proceeding with caution. Hypothetical dangers discussed include societal fragmentation, loss of human jobs, dominance of multinational corporations with powerful AI, or existential risk if superintelligent machines develop a drive for self-preservation. [1]
The dangers of AI algorithms can manifest themselves in algorithmic bias and dangerous feedback loops, and they can expand to all sectors of daily life, from the economy to social interactions, to ...
The Tesla CEO said AI is a “significant existential threat.” Elon Musk says there’s a 10% to 20% chance that AI ‘goes bad,’ even while he raises billions for his own startup xAI
For example, the use of generative AI for armed conflict and the potential for multiple generative AI models to be fused together into larger single-layer systems that could autonomously ...
The letter highlights both the positive and negative effects of artificial intelligence. [7] According to Bloomberg Business, Professor Max Tegmark of MIT circulated the letter in order to find common ground between signatories who consider super intelligent AI a significant existential risk, and signatories such as Professor Oren Etzioni, who believe the AI field was being "impugned" by a one ...
AI safety is an interdisciplinary field focused on preventing accidents, misuse, or other harmful consequences arising from artificial intelligence (AI) systems. It encompasses machine ethics and AI alignment, which aim to ensure AI systems are moral and beneficial, as well as monitoring AI systems for risks and enhancing their reliability.