timshell

8 ms·

61.
Market research is built on fraudulent data
3 points by timshell 2y ago|0 comments
62.
by timshell 2y ago
For this study, I only analyzed data where it was an empty car and two sets of pedestrians. I haven't looked at the data where there are people in the car!
63.
Complex, but Robust Human Moral Decisions from Moral Machine
1 points by timshell 2y ago|2 comments
64.
by timshell 2y ago
Hey HN, Mayank Agrawal from Roundtable here. Happy to answer any questions. Survey fraud a big problem in the market research industry right now, and we're trying to ensure quality and automate manual processes (i.e. data cleaning). A
65.
Show HN: Roundtable (YC S23) – Survey Quality Control API(app.roundtable.ai)
8 points by timshell 2y ago|2 comments
66.
by timshell 3y ago
Thank you for this feedback! We'd love to contract you in the future to try and break our system
67.
by timshell 3y ago
We only track typing behavior in pre-specified text boxes. We are thinking of having version 2 track more data, but we need to determine the privacy implications of that
68.
by timshell 3y ago
Correct, it's only for open-ended survey questions! We are building functionality for multiple choice surveys, but it seems a bit harder to build
69.
by timshell 3y ago
Grounded in reinforcement learning. General idea is hippocampal replay is valuable, and a rational agent should arbitrate between work and replay in order to maximize future reward
70.
A new (computational) theory of cognitive fatigue [pdf](mayank-agrawal.com)
2 points by timshell 3y ago|1 comments
71.
Show HN: Roundtable – Survey fraud and bot detection API
21 points by timshell 3y ago|9 comments
72.
Automated Survey Bot Detection(blog.roundtable.ai)
1 points by timshell 3y ago|0 comments
73.
by timshell 3y ago
Blog post is user written. Surveys are built through an AI simulator trying to recapitulate user survey data
74.
Analyzing r/gaming and r/science through an LLM-based survey simulator(blog.roundtable.ai)
1 points by timshell 3y ago|2 comments
75.
by timshell 3y ago
Thank you, this is exactly where our headspace is too
76.
by timshell 3y ago
Thank you for sharing these results!
77.
by timshell 3y ago
Makes sense. The further away the target question is from the GSS training distribution, the more it relies on the ChatGPT prior. I assume if you click 'Investigate Results', the confidence is 'low' and the most similar
78.
by timshell 3y ago
> I imagine cleaning customer data to get it to the point that it's inputtable will be a big job for you. We're in the process of figuring that out. Hopefully that is another use case for LLMs :) > Are you then creating indi
79.
by timshell 3y ago
Thank you! Agree A, B, and C are big hurdles. Re: A - we have started adding transparency (vis-a-vis the 'Investigate Results' and the tSNE plots + similarity scores) but we still have a ways to go Re: B - agree that the survey re
80.
by timshell 3y ago
Thank you! Trust is one of the biggest issues we're trying to solve. This motivated the tSNE plots and similarity scores under 'Investigate Results', but we definitely have a long way to go. Generally speaking, survey practit
81.
by timshell 3y ago
Exactly where we're headed :) Thank you for the kind words / reference
82.
by timshell 3y ago
Link [6] should point to https://roundtable.ai/sandbox/eeafc6de644632af303896ec19feb6...
83.
by timshell 3y ago
The survey / behavior gap is very real. Short-term we're focused on surveys, but we'd like to integrate behavioral data long-term (and potentially be primarily behavioral data, but that is TBD)
84.
by timshell 3y ago
Going forward, the current business model (with caveat that pivots are always likely this early stage) is to train on companies' proprietary survey data so we can estimate how their specific users respond to questions. In the backend,
85.
by timshell 3y ago
We're trying to figure out the optimal use case for this, i.e. whether it's internal or client-facing (your example). Internal purposes include stuff like optimally rewording questions and getting priors. A hybrid approach would b
86.
by timshell 3y ago
To respond to Edits - that's a great example, thank you. One of the limitations of surveys more broadly is you're asking for people's opinions, which of course does not correspond to reality. So, what we're simulating is
87.
by timshell 3y ago
One of our major weaknesses right now is sensitivity to price
88.
by timshell 3y ago
Pasting below answer to niko001 The data we trained on has year, so we can specify the year you ask the question (the default is 2023). You can also see how answers change over time. [1] shows how the distribution for "Do you support t
89.
by timshell 3y ago
The data we trained on has year, so we can specify the year you ask the question (the default is 2023). You can also see how answers change over time. [1] shows how the distribution for "Do you support the President" changes from
90.
by timshell 3y ago
1. GPT out of the box was pretty biased (e.g. gender distribution). We fine-tuned on representative survey data to ameliorate this bias so we get Census-level estimates for conditions such as gender [a] and work status [b]. 2. We add the tr

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