Priya Raman

The question this score answers · How much do they care about the world beyond themselves, and how much does that care shape what they actually work on? AI safety is one place the care can land, not the definition of it.

A 9, nearest the 8, on this ladder means: Their choices only make sense as a series if you assume they are working for the problem, and they can tell you why this way of helping rather than the others. The thinking has a history: what they fear has changed shape and they can say what changed it. With or without a record, each answer goes a step further than the question asked.

Why a 9

Priya redirected their PhD in April 2023, costing a paper and six to nine months. Their sparse-autoencoder replication and 2024 sandbagging internship changed which safety methods they trust and pursue; recurring threat-model questions now guide their research.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya redirected their PhD toward safety despite academic and financial costs.¶
• ✓The sandbagging internship changed which safety research Priya chose to pursue.¶
• ✓Priya's experiments shaped their doubts about sparse autoencoders as safety evidence.¶
• ✓Priya describes routinely questioning evaluation awareness, distribution shift and scaffold effects.¶

The question this score answers · How well do they understand the field, in two halves? The state of play: what is wrong with how models are trained today, what people are trying and where each attempt breaks, what the latest findings from Anthropic and others show and where they stop, and whether they can take part in the live argument about it, for instance the case that training models hard to sound safe may not be doing what it claims and may make things worse. And the map of the space: how it came to be, what people argued at each stage and why it moved on, who does what now, and which people and programs get what done, both for planning their own route and for getting a thing done. What each technique is for and where it breaks sits underneath; deep technique knowledge is not needed for the top. Placed against the part of the field they say they want, with the state of play under everyone, governance and field-building people included.

An 8 on this ladder means: Both halves are current and partly theirs. Recent findings from the labs and others are held by what they license and do not; they can take a side in a live argument, such as whether today's alignment training does what it claims or makes things worse, with a reason; and they know what is unresolved and who is working on it. The map of the space comes with why: why each turn happened, who does what now, and which people and programs get what done, well enough to plan a route for themselves and to say who to go to for what. A newcomer who has read the older writing in six months and can argue it can sit here.

Why an 8

Priya distinguishes constructed alignment failures from deployment prevalence, explains sandbagging detection, and connects MIRI's arguments to the 2016 empirical turn. Their sparse-autoencoder critique rests on causal interventions; current organisational knowledge was probed only through internship contacts and Redwood.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya distinguishes context-induced sandbagging from evidence about its natural prevalence.¶
• ✓Priya explains the empirical turn through its disagreement with MIRI.¶
• ✓Priya challenges sparse-autoencoder safety claims using their own causal intervention results.¶
• ✗Priya discounts deliberate omissions too categorically when diagnosing the scaffold's truncation bug.¶

The question this score answers · How good is their taste for what to focus on and which ablations and experiments to run?

A 10 on this ladder means: Somewhere on the call they do something the plan did not invite: they see that the question as posed is not the one worth answering, or cannot be answered with what is available, and replace it with the smaller or truer one that can; or they find a cheap test that separates two explanations nobody had separated. You would fund the plan as they described it, with nothing added. One such moment is enough; it needs no record behind it.

Why a 10

Priya turned a 22-point apparent sandbagging effect into a token-cap diagnosis using unanswered-run counts. That explanatory separation carries the placement; their sparse-autoencoder comparison addressed activation rarity but used outcome-informed feature selection.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya explained the entire apparent sandbagging effect through truncation rather than strategic underperformance.¶
• ✓Priya redesigned the feature comparison to separate activation rarity from label-predicted causal effects.¶
• ✓The clamp-strength ablation tested whether intervention damage explained apparent feature effects.¶
• ✗Outcome-informed feature selection limits the sparse-autoencoder study's 17% causal-success estimate.¶

The question this score answers · Given a situation or an argument they have not seen before, do they see what it turns on, weigh that in the right proportion, and land on the call you would have wanted, and how far outside their own area would you still trust that call?

A 7, nearest the 6, on this ladder means: Inside what they know they see the main options and pick well, run the standard checks in a sensible order and fix what breaks. The reasoning is the reasoning a good course gives, and it stops where the course stops: outside their field they sometimes misjudge the situation and do not notice they have crossed the edge of what they know.

Why a 7

Priya isolated missing answers behind a 22-point sandbagging-evaluation drop and justified frequency matching in their SAE study. Under questioning, they proposed blinded judging, but their post-selection bias estimate lacked support; unfamiliar live problems were untested.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓They traced the sandbagging headline to missing outputs rather than increased wrong answers.¶
• ✓They identified activation frequency as a confound in the SAE causal comparison.¶
• ✗The SAE defense does not establish why post-selection warrants only a few points.¶
• ✓They identified unblinded SAE judging without the interviewer raising that problem.¶

The question this score answers · When a contrary point or a piece of evidence they had not weighed arrives, how far do they move toward what is true, and does what they would do move with it? And when they have learned something, have they changed what they think and do: an idea, their point of view, their career?

An 8 on this ladder means: They find the weak point in their own answer before you do, and it is the point the answer rests on, not a cosmetic one. When they agree it is fast and carries the change in the same breath; when they hold, it is with a reason, and they can say what evidence would move them off it. Their changes of mind came at the speed of the evidence, including on things they had put time or reputation into.

Why an 8

Their sparse-autoencoder study carries the placement: a public correction from 21% to 17%, proposed prespecified selection after criticism, and a volunteered unblinded-judging flaw with a 60-rating remedy. They defended a numerical discount without new evidence.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓They corrected the published SAE result after commenters exposed excluded empty labels.¶
• ✓The challenge changed their proposed SAE protocol to fix selection rules before interventions.¶
• ✓They volunteered unblinded SAE scoring and proposed independent judging with 60 blinded checks.¶
• ✗They accepted post-selection bias but estimated its size without a validating rerun.¶

The question this score answers · How much of their path did they decide rather than accept, and is the next move already moving without waiting on anyone's permission?

A 7, nearest the 6, on this ladder means: Somewhere they left the path laid out for them and it cost them something real by their own means, or they started something nobody asked for and kept at it after the novelty wore off. The next step exists as a plan, told as something that might happen rather than something already moving.

Why a 7

Priya negotiated an April 2023 PhD redirection, sacrificing a paper, six to nine months and €18,000, then independently completed an eight-month interpretability project. The interviewer never probed whether their next sandbagging project had started.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya negotiated a PhD redirection despite an already strained supervisor relationship.¶
• ✓Priya names time, publication and income sacrificed for the safety transition.¶
• ✓Priya sustained a self-directed replication and causal extension for eight months.¶

The question this score answers · When something went wrong in their work, is what they do now different because of it, and did they name the real cause? Follow each setback to what changed.

A 7, nearest the 6, on this ladder means: Something went wrong and you can follow a line from it to a concrete difference in how they now work: a check they run first, a design they dropped, a rule they keep. The change has a moment in it, what they noticed and what they did next, and both the old way and the new way come out in plain nouns. Scale does not matter; a script on a free notebook has versions like a paper does. What keeps it here is that the failure is told as a single event, and the cause named is either outside them or a flattering one.

Why a 7

Priya now writes structured paper notes after catching headline-only recall, and corrected sparse-autoencoder intervention success from 21% to 17% by counting empty labels. Safeguards against outcome-informed selection and unblinded judging remain hypothetical rerun changes rather than demonstrated research habits.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya changed their reading routine after noticing headline recall replaced experimental understanding.¶
• ✓Priya corrected their SAE denominator rather than merely acknowledging the criticism.¶
• ✓Priya changed the SAE comparison after diagnosing activation frequency as a confound.¶
• ✗Priya offers predeclared SAE selection as a hypothetical rerun change, not a current habit.¶

The question this score answers · How big is the future they are reaching for, and how much of what they are doing now is explained by it?

A 7, nearest the 6, on this ladder means: There is something specific they want to be true that is not true now, in their own words, and a step toward it that belongs to that aim and not to any aim, scaled to what they have. The aim is theirs, but it is modest next to their capacity or the step is small next to it, and the present is only partly arranged around it.

Why a 7

Priya wants sandbagging evaluations that remain informative when models recognize testing. Their April 2023 PhD redirection and lower-paid summer 2024 internship give that aim a history of choices, rather than just an intended job.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya names a concrete property they want safety evaluations to have.¶
• ✓Priya reports spending publication opportunities, time and income on the safety transition.¶
• ✓Priya's research direction changed through hands-on sandbagging work.¶
• ✓Priya connects the timing of evaluation-gaming research to experiments within their means.¶

The question this score answers · How are they with the people they work with, and under stress: open-minded in a conflict, warm, caring and friendly, easy to be around, in touch with others often, and at ease under someone else's authority?

A 9, nearest the 8, on this ladder means: Warm, caring and easy company in how they tell it and in what they choose to say others say of them; still close to the people after the work ended. In a conflict they can say where the other side was right and change course quickly once they see it, even after holding their own idea hard. Touches base often, and can work under someone else's lead while saying plainly where they disagree.

Why a 9

Priya's sparse-autoencoder discussion carries this placement: a correcting commenter still reviews drafts, and the interviewer's selection-bias objection enters their hypothetical redesign. Their reply also defends intent, although the interviewer challenged the method rather than motives.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓They retain a critic of their sparse-autoencoder work as a continuing draft reader.¶
• ✓They answer the interviewer's selection-bias objection specifically rather than offering empty agreement.¶
• ✗They briefly recast the interviewer's selection-bias concern as a question of flattering intent.¶
• ✓Their hypothetical sparse-autoencoder redesign explicitly incorporates the interviewer's objection.¶

The question this score answers · Set what they claimed on paper and in the opening beside what came out when asked: is it the same story at the same size, and who drew the edges of it, them or the interviewer?

A 9, nearest the 8, on this ladder means: The edges are drawn by them as they go: a range with a reason for it, 'that part was not mine', 'I don't know', before anyone asks. The story is the size it was on paper and stays that size under questioning, because it was already right. Invited to take more credit, they decline and name the part that was theirs.

Why a 9

Priya's sparse-autoencoder study carries the placement: they volunteered the 21% to 17% correction, failed steering on new prompts, and unblinded judging. Outcome-aware selection behind the 17% headline emerged through follow-ups, without a retraction of the measured result.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya volunteered their own analysis error while presenting their strongest project.¶
• ✓Priya disclosed the SAE study's transfer failure without a targeted challenge.¶
• ✗Priya disclosed choosing the SAE frequency band by eye after a direct challenge.¶
• ✓Priya volunteered that their SAE validation used their own unblinded judgments.¶

The question this score answers · How much do they take in of whole written works, how widely, how regularly, and does what they read stay with them as an argument with its setup and its limits rather than as a title? Any field counts and the form does not matter: a book, a paper, a report, a long essay, listened to or read. A summary of a work, however good, is not the work. Turning what they read into ideas is a different trait and is not asked for here.

A 7, nearest the 6, on this ladder means: They read whole works inside one area, papers or books, and finishing them is ordinary rather than an event. The last one comes back with its setup and roughly what it found, in their own words, hedged where memory is thin, and they can say what it does not show. Outside that area it is summaries, and they say so without being caught.

Why a 7

Priya reports two or three full papers weekly with notes and the Alignment Forum most mornings. They recall Alignment Faking’s intervention and approximate results, and distinguish constructed sandbagging from natural prevalence; their described reading concentrates on AI safety.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya describes a weekly full-paper habit with experiment-focused notes.¶
• ✓Priya recalls Alignment Faking's intervention, approximate rates, and deliberately legible conflict.¶
• ✓Priya distinguishes scheming evaluations' arithmetic setup from evidence of naturally occurring sandbagging.¶
• ✗Priya's recent paper reading concentrates on evaluations and control.¶

The question this score answers · How good are they at the technical work itself, in whatever field they have done it: what is the best thing they actually made, computed, proved or measured, how much of it was theirs, and how far down does their understanding of it go, to where the time and the error live?

An 8 on this ladder means: Something hard that works, or a hard piece of something, where the shape was theirs: they chose it against other ways and can say what the other way would have cost them, in time, memory, accuracy or money, because they tried it or worked it out. They know where the remaining time, error or cost goes, not by guessing but because they looked. Help and off-the-shelf parts are fine; they can explain the helped parts as if they had written them. Size does not matter here; depth does.

Why an 8

Priya independently trained SAEs on a 400-million-parameter model and measured causal interventions across sparsity, layers and clamp strengths. Outcome-informed frequency matching and unblinded judging limit the 17% estimate. Their evaluation-scaffold diagnosis independently traced failures to token truncation.

The quotes it rests on · ✓ raises it · ✗ lowers or bounds it

• ✓Priya measured a sparsity tradeoff between SAE label quality and causal steering.¶
• ✓Priya quantified the frequency-matched feature subset and its sampling uncertainty.¶
• ✓Priya traced an apparent sandbagging effect through truncation, parsing and scoring.¶
• ✗Outcome-informed frequency matching compromises the SAE causal-success estimate.¶