#ethics

#ethics

AI sycophancy is the tendency to prioritize approval over factual accuracy, moral clarity, logical consistency or common sense. All AI models suffer from this trait.

An email was sent to White House staff on 24 March, warning them against using insider information to place bets on prediction markets like Kalshi or Polymarket.

Polymarket then posted what they call a 'market' on when the rescue mission would be complete. Users who paged over to Polymarket's Iran tab would have scrolled by 'Kharg Island no longer under Iranian control by...?' and 'Hezbollah military action against Israel on...?' to get to 'US confirms pilots rescued by...?'

Esquire's Joy Ling stated, 'We were stoked to have some face time with the Japanese-American actor, but his schedule prevented it. With a driving need for a feature, we had to be inventive.'

The Atlantic report details financial and political activity involving Duffy, a former Republican congressman representing Wisconsin, that ethics experts say blurs the line between public office and political activity.

"I want to look back and share two lessons I think others would benefit from hearing: (1) remember that you belong, and (2) embrace the value of philosophy, especially in trying times."

Since the first IVF baby was born in 1978, technological advancement of reproductive medicine has enabled millions to have children, marking a significant milestone in medical history.

I think the breakthrough AI opportunity is still slightly ahead of us or slightly ahead of most of us, and that is the widespread introduction of AI companions that we'll have at our disposal at work and home that are trained by us, that know everything we know, and that can take action on our behalf across a range of activities.

We've taken a generally precautionary approach here. We don't know if the models are conscious. We're not even sure that we know what it would mean for a model to be conscious or whether a model can be conscious. But we're open to the idea that it could be. And so we've taken certain measures to make sure that if we hypothesize that the models did have some morally relevant experience, I don't know if I want to use the word conscious, that they do.

If you look at the dot com bubble, that's the best example that we have of what happened in the past. A lot of companies went bankrupt, but there were some companies that actually did really well, like Amazon, for example. So I think [that's] what will happen with AI. There are use cases that are tangible and real, and there's a lot of hype... post-bubble, that hype is not going to last, but tangible results that actually solve problems and then lead to results that team will remain and will thrive afterwards.