Frida Polli

Founder, Rosalind Ventures · 1 appearance on the record.

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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.

15statements → 9claims → 2claims resolved → 3.87/5average certainty → 2/5average debate potential →

1 supported 1 partly supported 0 contradicted 7 not checkable as stated how the 9 claims stand · each chip opens the sources

9 assertions · 1 opinion · 3 insights · 2 disclosures · every statement was checked. The predictions and assertions are the 9 claims: statements the public record can support or contradict. 2 are resolved, and 7 name no date, number or outcome precise enough to check. Everything else (opinions, insights, what ifs, disclosures) can never be settled by the record, so it carries no assessment.

The record, in short

What the tape says about how Frida argues and how the claims held up. Everything they said, and everything said about them, is in the tabs below.

Their most notable supported claim

Assertion Supported

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.”

Frida Polli Feb 3, 2017 ▶ 5:41 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

How they sound: speaking style how? →

263 words/min while actually speaking · 20.2 um and uh per 1k words

No argument clarity score for Frida Polli: no usable question→answer exchanges on raw tape (a fair score needs 8+). We do not score a sample that small. Roundtable and news formats yield far fewer direct exchanges than interviews.

Measured by listening to the audio itself: 5,002 words across 1 episode of raw-level tape, transcribed verbatim with every um and uh kept, each one attributed only where the alignment onto our timed stream is unambiguous. These are measurements of speaking style. We do not rank them: across this corpus, fluency and argument quality are nearly uncorrelated (ρ≈0.2), and smooth talking does not signal clear thinking. How it's measured →

What they said15 Episodes1

Everything Frida Polli said on the MAD Podcast that made the record, most notable first. Filter by type, assessment or year in the ledger →

Assertion Not checkable as stated

Between 30% and 50% of first-year hires fail

“30 to 50% of first year hires fail.”

Frida Polli Feb 3, 2017 ▶ 3:03 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

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.”

Frida Polli Feb 3, 2017 ▶ 6:08 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Opinion

Resumes and questionnaires are subjective, low-density hiring tools

“Both of these are low density and also subjective.”

Frida Polli Feb 3, 2017 ▶ 6:44 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Insight

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.”

Frida Polli Feb 3, 2017 ▶ 13:37 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Insight

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.”

Frida Polli Feb 3, 2017 ▶ 3:40 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Supported

Nonverbal neuroscience games avoid cultural biases found in questionnaires

Frida Polli Feb 3, 2017 ▶ 5:41 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Insight

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.”

Frida Polli Feb 3, 2017 ▶ 9:49 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

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.”

Frida Polli Feb 3, 2017 ▶ 12:28 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

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.”

Frida Polli Feb 3, 2017 ▶ 20:54 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Disclosure

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…”

Frida Polli Feb 3, 2017 ▶ 22:54 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

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?”

Frida Polli Feb 3, 2017 ▶ 24:36 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

The average recruiter receives 250 applicants per job posting

“The average recruiter gets 250 applicants for every job that they post.”

Frida Polli Feb 3, 2017 ▶ 1:58 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Not checkable as stated

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”

Frida Polli Feb 3, 2017 ▶ 2:06 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Assertion Partly supported

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.”

Frida Polli Feb 3, 2017 ▶ 17:08 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Disclosure

Algorithmic screening should replace the resume review, not the interview

“The problem we're trying to solve is that initial decision as to, like, who to bring in for an interview. Nothing more. We're not touching the interview. We're not touching the internship process.”

Frida Polli Feb 3, 2017 ▶ 27:03 Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)

Appearances (1)

Episode	Date	Speaking time
Matching People to Careers Bias-Free // Frida Polli, Pymetrics (FirstMark's Data Driven)	Feb 3, 2017	23m

Frida Polli

The record, in short

Their most notable supported claim

How they sound: speaking style how? →

Appearances (1)

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