Frida Polli
Founder, Rosalind Ventures. On 1 show, 1 appearance. The Shows tab opens the full record on each.
founderscientistexecutiveinvestor@fridapolli ↗LinkedIn ↗Wikipedia ↗
A Harvard- and MIT-trained neuroscientist, Frida Polli co-founded and led pymetrics, a platform using gamified neuroscience and audited AI algorithms for bias-free recruitment until its 2022 acquisition by Harver. She currently focuses on ethical AI, women's health, and venture investing in female-led science and healthcare companies.
1shows
1appearances
15statements
2resolved
1supported
0contradicted
50%fully supported
Everything Frida Polli said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Neuroscience games lack inherent gender or ethnic bias
“Unlike some of the other data that people are using to predict fit in people, the games were generally, are generally not thought to have any inherent gender or ethnic bias, so they're not picking up on that if the training sample is biased.”
Resumes and questionnaires are subjective, low-density hiring tools
“Both of these are low density and also subjective.”
Candidate models require a broad baseline contrast group
“What we're saying is, no, you really need to collect a baseline that is representative of the people that you're, you know, trying to select from and use that as your contrast group.”
High-density objective data yields superior prediction of human outcomes
“And so what we just, what we learned in our, you know, 10 years at Harvard and MIT doing brain imaging is that if you collect better, more objective, more high density data on people, you can actually do a better job Of predicting research outcomes.”
Nonverbal neuroscience games avoid cultural biases found in questionnaires
“And we assess 90 different cognitive, emotional, and personality traits, and again, these are all nonverbal, ah, games, so they're not culturally anchored the way, you know, questionnaires or other things might be.”
Process metrics provide better algorithmic features than binary pass-fail outcomes
“This information is a lot more useful in terms of, ah, building algorithms for, as features for building algorithms than just sort of binary, binary outputs.”
Most recruitment startups simply apply machine learning to resumes
“So there are a handful of startups that are starting to do this type of work in the recruiting field. Many of them are focusing on the resume as a field, as a source of data.”
Behavioral data shows VCs chase high rewards while hedge fund managers hedge
“VCs are very motivated by that sort of high reward stuff. Versus the head fund managers, they're hedging, right? So of course they're going to put in effort for a variety of different things, including low reward situations.”
Predictive hiring tools are best suited for early-career candidates
“Yeah, so I think that this solution is honestly best suited for, let's say, the first 10, 15 years of this process. I don't think it definitely can work with experienced hires, but the reason I think it works better earlier on is a couple reasons. That's reall…”
Assessments may measure 90 traits, but only 10 determine job fit
“The second thing I would say to that is we measure 90 different traits, right? Of the things that are end up being important, it's usually maybe 10. Maybe, maybe fewer than that. The remaining 80 are left to vary tremendously, right?”
The average recruiter receives 250 applicants per job posting
“The average recruiter gets 250 applicants for every job that they post.”
Recruiters manually scan resumes for an average of six seconds
“If it's a person doing the scanning, they'll on average scan it for six seconds”
The most commonly used career instrument, Myers-Briggs, is 80 years old
“The most commonly used instrument is the Myers-Briggs and it is almost a century old at this point. It's 80 years old.”
One line per show, most statements first. The link opens Frida's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 MADLEDGER | Founder, Rosalind Ventures | 1 | 15 | 50% 1/2 | full record on the MAD Podcast → |