Amid the quick rise and implementation of AI across industries, some investors worry that the potential ESG downsides haven't been adequately considered and safeguarded against.
Researchers have also sought to quantify fairness and bias in AI models through various socio-ethnic parameters. For example, Stanford's artificial intelligence index report score for bias across AI models. It found "For my clients, that rubbed a lot of people the wrong way. Because this is a social issue," he said. "I mean, if the [Federal Reserve] wants unemployment to go up and a weakening economy, generative AI is going to do it for them."While there is no standardized methodology to quantify the exact ESG impacts of a given AI-related investment, there are certain considerations investors can take.
The firm characterizes the first two as likely requiring a low- to high- level of effort from investors. It notes that the final step likely requires a high level of engagement.
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