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17 results for “equity”
And one of the principles that they're supposed to hold is, uphold is a principle of fairness. And I like fairness. I think that's great. But the way that it gets applied is that essentially saying, we have all these very, very specific rules designe
27:41 / 28:55
from transcript27:41 – 28:55
And then they need to have freedom to act, to achieve that on their respective teams should have that independence to to basically decide the how, and then everybody's tied into the fortunes of the shareholders altogether. I think that's the system i
53:14 / 54:30
from transcript53:14 – 54:30
that it's fair. Okay? That the process is fair. It's not one person making a pronouncement of what another person is like. That as you go through the cases, and you say, oh, that case happened that way, and it happened again. What do you think? And s
54:33 / 55:56
from transcript54:33 – 55:56
But on a practical basis, no. They're not allowed to. Oh. So you you touched on this earlier, but part of the reasons all these requirements have been codified is for reasons of fairness. And The US presumably doesn't wanna go back to a system of pat
30:45 / 31:51
from transcript30:45 – 31:51
in your phone. So that's a big equalizer of the opportunity in a lot of ways that I don't think we've ever seen a bigger opportunity equalizer than AI. Every child can have, like, a super advanced, amazing tutor teacher. Great education is accessible
14:58 / 16:02
from transcript14:58 – 16:02
...you know, equity awards. One of the things we've learned from this compensation arena that's tough, but it's true is whatever it is that you ultimately do on compensation, you're not gonna make everyone happy.
53:53 / 55:03
from transcript53:53 – 55:03
When I'm like, it's 10:00 at night and I'm doing my email, I'll just put one of those playlists on from MIT OpenCourseWare and I'm like, I can't believe I can take a course at MIT for free anytime I want. And then you you know, flip it, you can build
37:38 / 38:42
from transcript37:38 – 38:42
of a purse of each person is so that they can play their role well? If you if you set that out as your aspiration, you'll find ways of doing that. Like, there may be tests. There may be you know, how do you pick your doctor? You know, you have you're
53:57 / 55:07
from transcript53:57 – 55:07
in the state of California. We can't use race or gender or affirmative action. It's literally illegal. We get audited for this all the time. So if that's what you meant by your question, we don't do it. And it's part of the California master plan for
12:35 / 13:52
from transcript12:35 – 13:52
negotiate your term sheet. The world is still unfair. I think I very. I think the key insight is, like, recognize that the world is unfair, and actually what that is is a game on the field and figure out how to play the game on the field. But, I mean
38:23 / 39:32
from transcript38:23 – 39:32
But what institution rejected Farm Boyce from Wisconsin? All of them. All of them. Of course. Okay. So we know this. We know this. The reason we know this is because of the Harvard and UNC court Supreme Court cases. So this was like three years ago.
2:47:16 / 2:48:26
from transcript2:47:16 – 2:48:26
In 1983, there was a case called Bob Jones University versus the IRS, in which the IRS challenged the tax exempt status of Bob Jones University because Bob Jones had this bizarre and reprehensible policy banning interracial dating on campus and inter
40:17 / 41:42
from transcript40:17 – 41:42
for artificial intelligence. It was passed all the way in May 2024, so it was one of the first to pass, even though they didn't really know what they were trying to regulate. No one's quite sure how to implement it, but what the law does is it bans s
1:11:15 / 1:12:15
from transcript1:11:15 – 1:12:15
This is the Supreme Court case a few years ago that said that affirmative action policies that use race as a factor in admissions are a violation of the fourteenth Amendment's protection against racial discrimination. So Harvard lost that case. They
41:07 / 42:20
from transcript41:07 – 42:20
Like, that's not, you know, that's not who you are. That doesn't mean that you're wrong, and it also doesn't mean that you have less of a moral stance. Yeah. And so it's just like, alright. Now by the way, look, I think there's there I I think there
3:00:44 / 3:01:50
from transcript3:00:44 – 3:01:50
So to make things work really well, you have to understand this this very kind of fat tail of human behavior. Along this AI thread, something that is really important to you clearly, something you talk a lot about is is The US being successful in AI
1:12:44 / 1:13:45
from transcript1:12:44 – 1:13:45
the magnitude of the problem we're talking about. We're talking about AI having a political bias built into it, and the bias can be so subtle that people don't even necessarily notice over time, but it has a huge impact on what people are allowed to
43:25 / 44:39
from transcript43:25 – 44:39
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