By Chris Pandolfo | FOX Business
The CEO of a hot artificial intelligence startup won praise from other chief executives, including Elon Musk, after he announced a hiring policy that focuses on merit.
Alexandr Wang, who founded Scale AI in 2016, shared on social media that his company has formalized an MEI hiring policy. That is, “Merit, Excellence and Intelligence,” in apparent contrast to DEI, or diversity, equity and inclusion policies popular at other companies.
“Scale is a meritocracy, and we must always remain one,” Wang wrote in an X post on Thursday. “Hiring on merit will be a permanent policy at Scale.”
Scale AI helps other businesses that want to deploy AI models by providing human workers and software services that label and test the data used to train those models. Without good data, generative AI will fail to deliver accurate responses to user queries — and Scale AI is a pioneer in the field of delivering good data.
The six-year-old startup, currently worth $14 billion, has partnered with OpenAI to develop GPT-2 with reinforcement learning from human feedback (RLHF), won government contracts with the Department of Defense and every major AI lab, and powered breakthroughs in self-driving technologies, according to Wang.
Scale AI generated buzz last month after securing $1 billion in funding from longtime investors including Wellington Management, Y Combinator, Spark Capital, Founders Fund, Greenoaks and Tiger Global Management. New investors include DFJ Growth, Elad Gil, Amazon, ServiceNow Ventures, Intel Capital and AMD Ventures, Fortune reported.
On the heels of this success, Wang said he’s received several questions about talent at Scale AI. He shared that he personally interviews every hire or signs off on every candidate packet at his company because, “Talent is our #1 input metric.”
“It’s a big deal whenever we invite someone to join our mission, and those decisions have never been swayed by orthodoxy or virtue signaling or whatever the current thing is.
“I think of our guiding principle as MEI: merit, excellence, and intelligence,” he wrote.
“That means we hire only the best person for the job, we seek out and demand excellence, and we unapologetically prefer people who are very smart.”
The CEO emphasized that Scale AI treats candidates as individuals, not representatives of groups.
“We do not unfairly stereotype, tokenize, or otherwise treat anyone as a member of a demographic group rather than as an individual.
“We believe that people should be judged by the content of their character — and, as colleagues, be additionally judged by their talent, skills, and work ethic.”
Widespread campaigns for social justice following the death of George Floyd in 2020 led to a boom in diversity, equity and inclusion (DEI) initiatives across the U.S. Supporters praise these initiatives as a means of ensuring representation of groups historically discriminated against in the workforce, though critics say hiring for diversity necessarily discriminates against other qualified candidates.
DEI-related job postings have recently fallen out of favor, declining by 44% in 2023, according to data from the job site Indeed. The decline has been attributed to a shift in priorities amid layoffs and the threat of discrimination lawsuits.
“There is a mistaken belief that meritocracy somehow conflicts with diversity. I strongly disagree,” Wang wrote. “No group has a monopoly on excellence. A hiring process based on merit will naturally yield a variety of backgrounds, perspectives, and ideas. Achieving this requires casting a wide net for talent and then objectively selecting the best, without bias in any direction. We will not pick winners and losers based on someone being the ‘right’ or ‘wrong’ race, gender, and so on. It should be needless to say, and yet it needs saying: doing so would be racist and sexist, not to mention illegal.”
The CEO said upholding meritocracy is not only good for business, but morally right.
“This approach not only results in the strongest possible team, but also ensures we’re treating our colleagues with fairness and respect.”
Wang’s X post won praise from several Silicon Valley business leaders.
“Thank you for being a shining beacon towards the light here,” wrote Y Combinator President and CEO Garry Tan.
“Great!” replied Tesla and SpaceX chief Elon Musk.
Palmer Luckey, the founder of Oculus VR and designer of the Oculus Rift, said Wang’s post was “powerful and persuasive.”
“Well said!” chimed in Brian Armstrong, CEO of Coinbase. “I expect others will follow.”
Scale AI’s annual recurring revenue is expected to hit $1.4 billion by the end of 2024, Wang told Fortune in an interview last month. He said revenues are growing 200% year-on-year and “we expect to be profitable by the end of this year as well.”
Wang said there are no immediate plans to take privately-held Scale AI public.
First published on Fox Business
Today we’ve formalized an important hiring policy at Scale. We hire for MEI: merit, excellence, and intelligence.
This is the email I’ve shared with our @scale_AI team.
———————————————————
MERITOCRACY AT SCALE
In the wake of our fundraise, I’ve been getting a lot of questions…
— Alexandr Wang (@alexandr_wang) June 13, 2024
Today we’ve formalized an important hiring policy at Scale. We hire for MEI: merit, excellence, and intelligence.
This is the email I’ve shared with our
@scale_AI team.
———————————————————
MERITOCRACY AT SCALE
In the wake of our fundraise, I’ve been getting a lot of questions about talent. All of our external success—powering breakthroughs in L4 autonomy, partnering with OpenAI on RLHF going back to GPT-2, supporting the DoD and every major AI lab, and the recent $1bn financing transaction—all of it is downstream from us hiring the best people for the job. Talent is our #1 input metric.
Because of this, I spend a lot of my time on recruiting. I either personally interview every hire or sign off on every candidate packet. It’s the thing I spend the plurality of my time on, easily. But everyone can and should contribute to this effort. There are almost a thousand of us now, and it takes a lot to hire quickly while maintaining, and continuing to raise, our bar for quality.
That’s why this is the time to codify a hiring principle that I consider crucial to our success:
Scale is a meritocracy, and we must always remain one.
Hiring on merit will be a permanent policy at Scale.
It’s a big deal whenever we invite someone to join our mission, and those decisions have never been swayed by orthodoxy or virtue signaling or whatever the current thing is. I think of our guiding principle as MEI: merit, excellence, and intelligence.
That means we hire only the best person for the job, we seek out and demand excellence, and we unapologetically prefer people who are very smart.
We treat everyone as an individual. We do not unfairly stereotype, tokenize, or otherwise treat anyone as a member of a demographic group rather than as an individual.
We believe that people should be judged by the content of their character — and, as colleagues, be additionally judged by their talent, skills, and work ethic.
There is a mistaken belief that meritocracy somehow conflicts with diversity. I strongly disagree. No group has a monopoly on excellence.
A hiring process based on merit will naturally yield a variety of backgrounds, perspectives, and ideas. Achieving this requires casting a wide net for talent and then objectively selecting the best, without bias in any direction.
We will not pick winners and losers based on someone being the “right” or “wrong” race, gender, and so on. It should be needless to say, and yet it needs saying: doing so would be racist and sexist, not to mention illegal.
Upholding meritocracy is good for business and is the right thing to do. This approach not only results in the strongest possible team, but also ensures we’re treating our colleagues with fairness and respect.
As a result, everyone who joins Scale can be confident that they were chosen for their outstanding talent, not any other reasons.
MEI has gotten us to where we are today. And it’s the same thing that’ll get us where we’re going, as we embark on our next chapter focusing on data abundance, frontier data, and reliable measurement to accelerate the development and adoption of AI models.
Alex
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